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Network selection in heterogeneous wireless networks (HWNs) is a complex issue that requires a thorough understanding of service features and user preferences. This is because the various wireless access technologies have varying capabilities and limitations, and the best network for a voice, video, and data service depends on a variety of factors. For selecting the optimal network in HWNs, varying factors such as the user’s position, accessible network resources, service quality requirements, and user preferences must be considered. The classical decision making procedure is very difficult and uncertain to select the desirable HWNs for voice, video, and data. Therefore, we develop a novel decision making model based on feed-forward neural networks under the double hierarchy linguistic information for the selection of the best HWNs for voice, video, and data. In this article, we introduce a novel feed-forward double hierarchy linguistic neural network using the Hamacher t-norm and t-conorm. Further, the feed-forward double hierarchy linguistic neural network applies to the decision making model for the selection of the best HWNs for voice, video, and data. In this novel decision making model, we first take the given data about HWNs and use the converting function to convert the given data into a double hierarchy linguistic term set. We calculate the hidden layer and output layer information by using Hamacher aggregation operations. Finally, we use the sigmoid activation function on the output layer information to decide on the best HWNs for voice, video, and data according to ranking. The proposed approach is compared with other existing models of decision making and the results of the comparison show that the proposed technique is applicable and reliable for the decision support model. [ABSTRACT FROM AUTHOR]

Traditional fossil fuels and has become an important component of clean energy. Vigorously investing in and developing renewable energy projects is of great strategic significance for enhancing sustainable energy development. Due to the unique nature of energy project investment, evaluating the investment risks of renewable energy projects is crucial for enhancing project feasibility. Therefore, this study propounds a novel multiple-criteria group decision framework based on the extended TODIM method (an acronym in Portuguese for Interactive and Multi-criteria Decision Making) under q-rung orthopair fuzzy (q-ROF) set for the application of renewable energy project investment risk assessment. To begin with, a novel q-ROF Lance distance measure is propounded for conquering the deficiencies caused by the prior distances. Then, an improved weight model by the defined q-ROF Lance distance is applied for determining the weight of experts, and an integration model that incorporates the group individual best and worst (GIBWM) and criteria importance through inter-criteria correlation (CRITIC) is presented for ascertaining the synthetics weight of criteria. Afterward, an extended TODIM method based upon the prospect theory using the proposed Lance distance measure is developed to rank alternatives. Furthermore, a hybrid decision framework is constructed to assess the investment risk of renewable energy projects. The sensitivity analysis regarding the risk avoidance coefficient is conducted to explore the stability and robustness of the propounded assessment framework. Further, the extant methodologies are utilized to compare with the designed decision framework to highlight its strengths and superiorities. The outcomes exhibit that the propounded framework can provide efficient decision support for assessing renewable energy project investment risk by modeling the uncertainty and psychological behavior of the assessment procedure. [ABSTRACT FROM AUTHOR]

In current piece of writing, we bring in the new notion of induced bipolar neutrosophic (BN) AOs by utilizing Einstein operations as the foundation for aggregation operators (AOs), as well as to endow having a real-world problem-related application. The neutrosophic set can rapidly and more efficiently bring out the partial, inconsistent, and ambiguous information. The fundamental definitions and procedures linked to the basic bipolar neutrosophic (BN) set as well as the neutrosophic set (NS), are presented first. Our primary concern is the induced Einstein AOs, like, induced bipolar neutrosophic Einstein weighted average (I-BNEWA), induced bipolar neutrosophic Einstein weighted geometric (I-BNEWG), as well as their different types and required properties. The main advantage of employing the offered methods is that they give decision-makers a more thorough analysis of the problem. These strategies whenever compare to on hand methods, present complete, progressively precise, and accurate result. Finally, utilizing a numerical representation of an example for selection of robot, for a problem involving multi-criteria community decision making, we propose a novel solution. The suitability ratings are then ranked to select the most suitable robot. This demonstrates the practicality as well as usefulness of these novel approaches. [ABSTRACT FROM AUTHOR]

The primary objective of this research is to examine how the Russia–Ukraine war impacted the global economy. To achieve this goal, we propose operational laws, a score and accuracy function, and a divergence measure for complex dual hesitant fuzzy sets. Furthermore, we investigate the challenges associated with multi-criteria decision-making (MCR) using aggregation operators and the TODIM method with complex dual hesitant fuzzy (CDHF) information. Drawing inspiration from arithmetic aggregation operations, we introduce several aggregation operators for complex dual hesitant fuzzy information, including the complex dual hesitant fuzzy weighted average (CDHFWA) operator, complex dual hesitant fuzzy ordered weighted average (CDHFOWA) operator, and complex dual hesitant fuzzy hybrid average (CDHFHA) operator. We thoroughly analyze the unique characteristics of these proposed operators and use them in conjunction with the TODIM method to develop practical approaches for solving complex dual hesitant fuzzy multi-criteria decision-making problems. To validate our approach and demonstrate its applicability, we provide a practical example of how the Russia–Ukraine war affected the global economy. Our study confirms the effectiveness of our approach and highlights how it can be used to solve real-world problems. [ABSTRACT FROM AUTHOR]

The distribution of emergency shelter materials in emergency cases around the world is a hard task, the goal of this research is to offer a Complex Non-linear Diophantine Fuzzy (C-NLDF) decision-making model for earthquake shelter construction. Essentially, the article is divided into three sections to acquire acceptable and precise measures in emergency decision-making situations. First, we present the Complex Non-Linear Diophantine Fuzzy Set (CN-LDFS), a new generalization of the complex linear Diophantine fuzzy set (CLDFS) and q-linear Diophantine fuzzy set (q-LDFS), as well as explore its key aspects. Furthermore, aggregation operators are useful for aggregating uncertainty in decision-making issues. As a result, algebraic norms for CN-LDFSs are produced based on certain operational laws. In the second section of the work, we offer a series of averaging and geometric aggregation operators under CN-LDFS that are based on defined operating laws. In the final section of the work, under complex Non-linear Diophantine fuzzy information, the ranking algorithms based on suggested aggregation operators are present to address the case study regarding emergency situation of earthquakes. In comparison section, results of existing and proposed operators explore the effectiveness of proposed methodologies and provide accurate emergency measures to address the global uncertainty about the construction of emergency shelters in earthquakes. [ABSTRACT FROM AUTHOR]

The main aim of this article is to present a novel hybridized idea of fuzzy Credibility Dombi Bonferroni mean aggregation operators to describe the fuzzy Credibility information. Next, we define operational laws of FCNs by using Dombi t-norms and Bonferroni mean operator. By using the proposed operation laws a series of aggregation operators are presented. The TODIM method plays an important rule in decision making problems, especially when the problems of multi criteria group decision making include more computing criteria. So the core of this study is that we have proposed a decision making algorithm based on aggregation information and TODIM method to handle the uncertainty in real life decision making problems under FCNs information. To show the superiority and the applicability of the proposed methods, a numerical case is study of real-life decision making problems in medical diagnosis is considered. Furthermore to indicate the proposed decision making models are much more reliable and efficient to tackle uncertain information based on FCNs information. [ABSTRACT FROM AUTHOR]

Electroencephalograms (EEG) is used to assess patients' clinical records of depression (EEG). The disorder of human thinking is a very complex problem caused by heavy-duty in daily life. We need some future and optimal classifier selection by using different techniques for depression data extraction using EEG. Intelligent decision support is a decision-making process that is automated based on some input information. The primary goal of this proposed work is to create an artificial intelligence-based fuzzy decision support system (AI-FDSS). Based on the given criteria, the AI-FDSS is considered for classifier selection for EEG under depression information. The proposed intelligent decision technique examines classifier alternatives such as Gaussian mixture models (GMM), k-nearest neighbor algorithm (k-NN), Decision tree (DT), Nave Bayes classification (NBC), and Probabilistic neural network (PNN). For analyzing optimal classifiers selection for EEG in depression patients, the proposed technique is criterion-based. First, we develop a general algorithm for intelligent decision systems based on non-linear Diophantine fuzzy numbers to examine the classifier selection technique using various criteria. We use classifier methods to obtain data from depression patients in normal and abnormal situations based on the given criteria. The proposed technique is criterion-based for analyzing optimal classifier selection for EEG in patients suffering from depression. The proposed model for analyzing classifier selection in EEG is compared to existing models. [ABSTRACT FROM AUTHOR]

The control of spreading of COVID-19 in emergency situation the entire world is a challenge, and therefore, the aim of this study was to propose a spherical intelligent fuzzy decision model for control and diagnosis of COVID-19. The emergency event is known to have aspects of short time and data, harmfulness, and ambiguity, and policy makers are often rationally bounded under uncertainty and threat. There are some classic approaches for representing and explaining the complexity and vagueness of the information. The effective tool to describe and reduce the uncertainty in data information is fuzzy set and their extension. Therefore, we used fuzzy logic to develop fuzzy mathematical model for control of transmission and spreading of COVID19. The fuzzy control of early transmission and spreading of coronavirus by fuzzy mathematical model will be very effective. The proposed research work is on fuzzy mathematical model of intelligent decision systems under the spherical fuzzy information. In the proposed work, we will develop a newly and generalized technique for COVID19 based on the technique for order of preference by similarity to ideal solution (TOPSIS) and complex proportional assessment (COPRAS) methods under spherical fuzzy environment. Finally, an illustrative the emergency situation of COVID-19 is given for demonstrating the effectiveness of the suggested method, along with a sensitivity analysis and comparative analysis, showing the feasibility and reliability of its results. [ABSTRACT FROM AUTHOR]

The significance of emergency decision-making (EmDM) has been experienced recently due to the continuous occurrence of various emergency situations that have caused significant social and monetary misfortunes. EmDM assumes a manageable role when it is important to moderate property and live misfortunes and to reduce the negative effects on the social and natural turn of events. Genuine world EmDM issues are usually described as complex, time-consuming, lack of data, and the effect of mental practices that make it a challenging task for decision-makers. This article shows the need to manage the various types of vulnerabilities and to monitor practices to resolve these concerns. In clinical analysis, how to select an ideal drug from certain drugs with efficacy values for coronavirus disease has become a common problem these days. To address this issue, we are establishing a multi-attribute decision-making approach (MADMap) based on the EDAS method under Pythagorean probabilistic hesitant fuzzy information. In addition, an algorithm is developed to address the uncertainty in the selection of drugs in EmDM issues with regards to clinical analysis. The actual contextual analysis of the selection of the appropriate drug to treat coronavirus ailment is utilized to show the practicality of our proposed technique. Finally, with the help of a comparative analysis of the TOPSIS technique, we demonstrate the efficiency and applicability of the established methodology. [ABSTRACT FROM AUTHOR]

Dominant emergency action should be adopted in the case of an emergency situation. Emergency is interpreted as limited time and information, harmfulness and uncertainty, and decision-makers are often critically bound by uncertainty and risk. This framework implements an emergency decision-making approach to address the emergency situation of COVID-19 in a spherical fuzzy environment. As the spherical fuzzy set (SFS) is a generalized framework of fuzzy structure to handle more uncertainty and ambiguity in decision-making problems (DMPs). Keeping in view the features of the SFSs, the purpose of this paper is to present some robust generalized operating laws in accordance with the Einstein norms. In addition, list of propose aggregation operators using Einstein operational laws under spherical fuzzy environment are developed. Furthermore, we design the algorithm based on the proposed aggregation operators to tackle the uncertainty in emergency decision making problems. Finally, numerical case study of COVID-19 as an emergency decision making is presented to demonstrate the applicability and validity of the proposed technique. Besides, the comparison of the existing and the proposed technique is established to show the effectiveness and validity of the established technique. [ABSTRACT FROM AUTHOR]

The emergency situation of COVID-19 is a very important problem for emergency decision support systems. Control of the spread of COVID-19 in emergency situations across the world is a challenge and therefore the aim of this study is to propose a q-linear Diophantine fuzzy decision-making model for the control and diagnose COVID19. Basically, the paper includes three main parts for the achievement of appropriate and accurate measures to address the situation of emergency decision-making. First, we propose a novel generalization of Pythagorean fuzzy set, q-rung orthopair fuzzy set and linear Diophantine fuzzy set, called q-linear Diophantine fuzzy set (q-LDFS) and also discussed their important properties. In addition, aggregation operators play an effective role in aggregating uncertainty in decision-making problems. Therefore, algebraic norms based on certain operating laws for q-LDFSs are established. In the second part of the paper, we propose series of averaging and geometric aggregation operators based on defined operating laws under q-LDFS. The final part of the paper consists of two ranking algorithms based on proposed aggregation operators to address the emergency situation of COVID-19 under q-linear Diophantine fuzzy information. In addition, the numerical case study of the novel carnivorous (COVID-19) situation is provided as an application for emergency decision-making based on the proposed algorithms. Results explore the effectiveness of our proposed methodologies and provide accurate emergency measures to address the global uncertainty of COVID-19. [ABSTRACT FROM AUTHOR]

In this paper, we introduce two new algebraic structures known as generalized BE-algebra and generalized BE-semigroup. We construct some examples to show the existence of the structures. Furthermore, we discuss different classes of generalized BE-semigroups and explore some of their properties. [ABSTRACT FROM AUTHOR]

The triangular linguistic cubic fuzzy sets (TLCFSs) can express the fuzzy data easily and is also very useful in modeling of uncertain data in decision making (DM) problems. First of all, on the basis of Dombi t-norm and t-conorm (DTT), we propose novel operational rules of triangular linguistic cubic fuzzy numbers (TLCFNs). We propose some new aggregation operators of TLCFNs based on the newly developed operations, i.e., triangular linguistic cubic fuzzy Dombi weighted averaging (TLCFDWA), triangular linguistic cubic fuzzy Dombi weighted geometric (TLCFDWG), triangular linguistic cubic fuzzy Dombi order weighted averaging (TLCFDOWA), triangular linguistic cubic fuzzy Dombi order weighted geometric (TLCFDOWG), triangular linguistic cubic fuzzy Dombi hybrid weighted averaging (TLCFDHWA), and triangular linguistic cubic fuzzy Dombi hybrid weighted geometric (TLCFDHWG) operators. Furthermore, a new method is proposed with the help of the proposed operators to solve the decision making problem. Finally, a numerical example is provided to illustrate the effectiveness of the new method. Comparative analysis is used to demonstrate the proposed method's superiority. [ABSTRACT FROM AUTHOR]

In this paper, we generalize the concept of interval valued (∈ , ∈ ∨ q k ~) -fuzzy left (right) filters in ordered semigroups introducing and studying the notion of an interval valued (∈ , ∈ ∨ q k ~ δ ~ ) -fuzzy left (right) filter. Several properties and characterizations are investigated and obtained on ordered semigroups by an interval valued (∈ , ∈ ∨ q k ~ δ ~ ) -fuzzy left (right) filter. Characterizations of interval valued fuzzy left (resp. right) filters and interval valued (∈ , ∈ ∨ q k ~ δ ~ ) -fuzzy left (resp. right) filters are considered by using implication operators and the notion of implication-based interval valued fuzzy left (resp. right) filters. [ABSTRACT FROM AUTHOR]

This article is an advanced approach to linguistic intuitionistic fuzzy variable through application of cubic set theory. For instance, we establish the idea of the linguistic intuitionistic cubic fuzzy variable (LICFV) theory and define several operations for LICFV; also establish a series of weighted aggregation operators under linguistic intuitionistic cubic fuzzy information, so called linguistic intuitionistic cubic fuzzy weighted averaging (LICFWA) operator, linguistic intuitionistic cubic fuzzy order weighted averaging (LICFOWA) operator, linguistic intuitionistic cubic fuzzy weighted geometric (LICFWG) operator, linguistic intuitionistic cubic fuzzy order weighted geometric (LICFOWG) operator, linguistic intuitionistic cubic fuzzy hybrid averaging (LICFHA) operator, and linguistic intuitionistic cubic fuzzy hybrid geometric (LICFHG) operator; and further study their fundamental properties and showed the relationship among these aggregation operators. In order to demonstrate the feasibility and practicality of the mentioned new technique, we develop multi-criteria decision-making algorithm under linguistic intuitionistic cubic fuzzy environment. Further, the proposed method applied to mobile phone selection, consider numerical application of mobile phone. Comparing the proposed techniques with other pre-existing aggregation operators, we concluded that the proposed technique is better, reliable, and effective. [ABSTRACT FROM AUTHOR]

Spherical fuzzy sets have recently become more popular in various fields. It was proposed as a generalization of picture fuzzy sets and Pythagorean fuzzy sets in order to deal with uncertainty and fuzziness information. This paper presents a multi-attribute group decision making method based on novel sine aggregation operators to help decision makers choose the optimal alternative. Moreover, the well-known sine trigonometry function preserves the periodic and symmetric nature about the origin, and hence, it satisfies the decision makers preferences over the multi-time phase parameters. Keeping these features and the importance of the spherical fuzzy (SF) sets, the objective of this paper is to present some robust sine trigonometric (ST) operation laws for SF sets. Associated with these laws, we define some series of new aggregation operators (AOs) named as ST-weighted averaging and geometric operators to aggregate the spherical fuzzy information. Afterward, we present group decision making techniques to solve the multi-attribute group decision making problems based on proposed AOs and illustrate with a numerical example of an internet finance soft power evaluation problem to validate it. Also, we conduct some comparison analysis to study the reasonability and practicality of the proposed method. [ABSTRACT FROM AUTHOR]

Information fusion of fuzzy numbers has played a vital role in the decision support systems under the environment of q-rung orthopair fuzzy set (q-ROFS), which is an effective extension of intuitionistic fuzzy set and fuzzy set. The goals of the present work are to build a family of new aggregation operators (AOs) under q-ROF environment and apply them to MADM problems. First, the extended Archimedean copula (EAC) and extended Archimedean co-copula (EACC) are proposed to handle q-ROF information; consequently, the operational law of q-ROFNs is defined based on EAC and EACC. In order to comprehensively consider the relationship between attributes, the q-rung orthopair fuzzy Banzhaf–Choquet-copula AOs ( B C C A q ) and q-rung orthopair fuzzy Banzhaf–Choquet-copula geometric operators ( B C C G q ) are introduced on the basis of the operation of q-rung orthopair fuzzy numbers (q-ROFNs); consequently, some special cases of B C C A q / B C C G q operators are investigated when the generators of copula take different functions which satisfy the condition of the generators of copulas. In addition, to determine the fuzzy measure (FM) of attribute sets objectively, the improved maximum deviation method and Banzhaf function model are built. Finally, the corresponding decision-making approaches are constructed based on the proposed AOs and proposed models. Proposed approaches can effectively address the some decision-making problems (DMPs), in which the weights of attributes are incompletely unknown (completely unknown), and the correlation also exists among all attribute sets. [ABSTRACT FROM AUTHOR]

Interval-valued picture fuzzy linguistic variable concept is introduced in this article, in which we consider principal component and proposed a generalized interval-valued picture fuzzy linguistic induced hybrid aggregation (GIVPLIHA) operator with entropic order-inducing variable and TOPSIS method. Then, we discussed some basic properties of the GIVPLIHA operator. We also discussed an algorithm for linguistic group decision-making based on GIVPLIHA operator and TOPSIS technique. To prove the validity and applicability of the developed method, finally, we solved a decision-making problem of a company to make a policy for the selection of the best investment strategy. We conclude from the comparison and sensitive analysis that the proposed decision-making method is more effective and reliable than other existing models. [ABSTRACT FROM AUTHOR]

This paper contributes to cubic aggregation operator and applications in decision-making problem. In this paper, we use Dombi operational laws and Heronian mean operators, to develop a new concept of cubic fuzzy Heronian mean Dombi aggregation operators, i.e., cubic fuzzy Heronian mean Dombi aggregation (CFHMDA), cubic fuzzy weighted Heronian mean Dombi aggregation (CFWHMDA), cubic fuzzy geometric Heronian mean Dombi aggregation (CFGHMDA), and cubic fuzzy weighted geometric Heronian mean Dombi aggregation (CFWGHMDA) operators. The proposed operators are not deal single aspect, but also deal with the relation between multi-aspects making them more effectively solving decision-making (MADM) problems. We proposed a new algorithm to solve a multi-attribute decision-making problem based on the developed operators. Finally, we solved a MADM problems with the cubic fuzzy Heronian mean Dombi aggregation operators. [ABSTRACT FROM AUTHOR]

The fuzzy aggregation information plays an important role in the group decision support system under the interval-valued hesitant fuzzy information and interval-valued probabilistic hesitant fuzzy information. Therefore, in this paper, we develop a new approach of the interval-valued hesitant fuzzy Frank aggregation (IVHFFA) and interval-valued probabilistic hesitant fuzzy aggregation (IVPHFFA) operators. First, we define some operational laws of IVHEs and IVPHFEs by using Frank t-norm and t-conorm. Furthermore, we develop a series of IVHFFA and IVPHFFA operators based on these operational laws under the IVHF and IVPHF information. Also, discuss some fundamental properties and relations of the proposed aggregation operators for IVHF and IVPHF information. In order to implement the proposed aggregation operators of IVHF and IVPHF information in group decision-making problem, we construct general algorithms for multi-attribute group decision-making problem based on the proposed IVHFFA and IVPHFFA. Finally, from the comparative and sensitivity analysis, the proposed fuzzy decision-making model is more effective and reliable as compared with existing method. [ABSTRACT FROM AUTHOR]

The Pythagorean fuzzy set (PFS) is one of the most important concepts to accommodate more uncertainties than the intuitionistic fuzzy sets, fuzzy sets and hence its applications are more extensive. The well-known sine trigonometric function ensures the periodicity and symmetry of the origin in nature and thus satisfies the expectations of decision-makers over the parameters of the multi-time process. Keeping the features of sine function and the importance of the PFS, introduce the novel sine trigonometric operational laws (STOLs) under Pythagorean Fuzzy Settings. In addition, novel sine-trigonometric Pythagorean fuzzy aggregation operators are established based on these STOLs. The core of the study is the decision-making algorithm for addressing multi-attribute decision-making problems based on the proposed aggregation operators with unknown weight information of the given criteria. Finally, an illustrative example on internet finance soft power evaluation is provided to verify the effectiveness. Sensitivity and comparative analyses are also implemented to assess the stability and validity of our method. [ABSTRACT FROM AUTHOR]

The objective of this manuscript is to present the notion of probabilistic hesitant fuzzy rough (PHFR) set and their basic operations. As a generalization of the sets, PHFR set is a more profitable way to express the uncertainties in the data. For it, firstly, we define the basic operational laws like, the union, intersection and the composition of probabilistic hesitant fuzzy approximation spaces with some basic properties are discussed in details. Secondly, presented the novel decision-making technique based on the PHFR sets over two nonempty fixed sets to deal with uncertainty in decision-making problems. Finally, two numerical examples are provided with some comparative study to validate the proposed approach. [ABSTRACT FROM AUTHOR]

Spherical fuzzy sets (SFSs), recently proposed by Ashraf, is one of the most important concept to describe the fuzzy information in the process of decision making. In SFSs the sum of the squares of memberships grades lies in close unit interval and hence accommodate more uncertainties. Thus, this set outperforms over the existing structures of fuzzy sets. In real decision making problems, there is often a treat regarding a neutral character towards the membership and non-membership degrees expressed by the decision-makers. To get a fair decision during the process, in this paper, we define some new operational laws by Dombi t-norm and t-conorm. In the present study, we propose Spherical fuzzy Dombi weighted averaging (SFDWA), Spherical fuzzy Dombi ordered weighted averaging (SFDOWA), Spherical fuzzy Dombi hybrid weighted averaging (SFDHWA), Spherical fuzzy Dombi weighted geometric (SFDWG), Spherical fuzzy Dombi ordered weighted geometric (SFDOWG) and Spherical fuzzy Dombi hybrid weighted geometric (SFDHWG) aggregation operators and discuss several properties of these aggregation operators. These aforesaid operators are enormously used to help a successful solution of the decision problems. Then an algorithm by using spherical fuzzy set information in decision-making matrix is developed and applied the algorithm to decision-making problem to illustrate its applicability and effectiveness. Through this algorithm, we proved that our proposed approach is practical and provides decision makers a more mathematical insight before making decisions on their options. Besides this, a systematic comparison analysis with other existent methods is conducted to reveal the advantages of our method. Results indicate that the proposed method is suitable and effective for decision process to evaluate their best alternative. [ABSTRACT FROM AUTHOR]

The Pythagorean fuzzy number is a new tool for uncertainty and vagueness. It is a generalization of fuzzy numbers and intuitionistic fuzzy numbers. In this paper, we define some Einstein operations on Pythagorean trapezoidal fuzzy set and develop two averaging aggregation operators, which is an induced Pythagorean trapezoidal fuzzy Einstein ordered weighted averaging operator and an induced Pythagorean trapezoidal fuzzy Einstein hybrid averaging (I-PTFEHA) operator. We presented some new methods to deal with the multi-attribute group decision-making problems under the Pythagorean trapezoidal fuzzy environment. Finally, we used some practical examples to illustrate the validity and feasibility of the proposed methods by comparing with existing method. It shows that the proposed I-PTFEHA operator is much better and reliable than the existing one. [ABSTRACT FROM AUTHOR]

This article is an advanced approach to intuitionistic fuzzy set through application of cubic set theory. For instance, we establish the idea of the intuitionistic cubic fuzzy set (ICFS) theory and define several operations for ICFS ; also establish a series of weighted aggregation operators under intuitionistic cubic fuzzy information, so-called intuitionistic cubic fuzzy weighted averaging (ICFWA) operator, intuitionistic cubic fuzzy order weighted averaging (ICFOWA) operator, intuitionistic cubic fuzzy weighted geometric (ICFWG) operator, intuitionistic cubic fuzzy order weighted geometric (ICFOWG) operator, intuitionistic cubic fuzzy hybrid averaging (ICFHA) operator, and intuitionistic cubic fuzzy hybrid geometric (ICFHG) operator; and further study their fundamental properties and showed the relationship among these aggregation operators. In order to demonstrate the feasibility and practicality of the mentioned new technique, we develop multicriteria group decision-making algorithm under intuitionistic cubic fuzzy environment. Further, the proposed method applied to supply chain management and for implementation, consider numerical application of supply chain management. Also the selected supplier by ICFD aggregation operators is verified by VIKOR method. Comparing the proposed techniques with other pre-existing aggregation operators, we concluded that the proposed technique is better, reliable, and effective. [ABSTRACT FROM AUTHOR]

In this paper, we define aggregation operators for trapezoidal cubic linguistic fuzzy sets which includes generalized cubic linguistic fuzzy averaging (geometric) operator, generalized trapezoidal cubic linguistic fuzzy weighted averaging (GTrCLFWA) operator, generalized trapezoidal cubic linguistic fuzzy weighted geometric (GTrCFWG) operator, generalized trapezoidal cubic linguistic fuzzy ordered weighted average (GTrCLFOWA) operator, generalized trapezoidal cubic linguistic fuzzy ordered weighted geometric (GTrCLFOWG) operator, generalized trapezoidal cubic linguistic fuzzy hybrid averaging (GTrCLFHA) operator and generalized trapezoidal cubic linguistic fuzzy hybrid geometric (GTrCLFHG) operator. Furthermore, we relate these aggregation operators to develop an approach to multiple attribute group decision-making with trapezoidal cubic linguistic fuzzy information. Finally, a numerical example is providing to demonstrate the submission of the established approach. [ABSTRACT FROM AUTHOR]

The linguistic picture fuzzy set (LPFS) is an extension of the linguistic intuitionistic fuzzy set (LIFS), and can contain more information than the LIFS. In this paper, the degrees of positive, neutral and non-membership of PFSs are expressed in linguistic terms, which can more easily describe the uncertain and vague information existing in the real world. By combining the PFS and the linguistic term, we define the LPFS and propose operational rules for linguistic picture fuzzy numbers (LPFNs). We further propose weighted averaging and weighted geometric operators and discuss their properties. Additionally, we propose an approach to deal with a multiple-attribute group decision-making (MAGDM) problem based on the developed aggregation operators. Finally, we present an illustrative example to demonstrate the effectiveness and advantages of the developed method by comparing it with existing methods. In addition, our method can be utilized not only to solve problems with linguistic intuitionistic fuzzy numbers (LIFNs), but also to deal with problems with LPFNs, and is a generalization of a number of existing methods. [ABSTRACT FROM AUTHOR]

For the multi-attribute group decision-making problems where attribute values are the interval-valued Pythagorean fuzzy numbers, the group decision-making method based on induced Einstein averaging aggregation operators are developed. Firstly, induced interval-valued Pythagorean fuzzy Einstein ordered weighted averaging (I-IVPFEOWA) aggregation operator and induced interval-valued Pythagorean fuzzy Einstein hybrid weighted averaging (I-IVPFEHWA) aggregation operator, were proposed. Some general properties of these operators, such as idempotency, commutativity, monotonicity and boundedness, were discussed, and some special cases in these operators were analyzed. Furthermore, the method for multi-attribute group decision-making problems based on these operators was developed, and the operational progressions were explained in detail. These methods provide more general, more accurate and precise results as compared to the existing methods. Therefore these methods play a vital role in daily life problems. At the end of the paper the proposed operators have been applied to decision making problems to show the weight, practicality and effectiveness of the new approach. [ABSTRACT FROM AUTHOR]

Faced with the contradiction between economic growth and environmental pollution, to implement cleaner production has become a good choice for many mining companies in order to achieve sustainable development. This study aims to explore applicable decision-making methods to evaluate the cleaner production for gold mines. First, the CPFNs (cubic picture fuzzy numbers) are adopted to describe experts' assessment information under complicated fuzzy environment. Thereafter, the mean-squared deviation models are combined to obtain the comprehensive criteria weights. Meanwhile, a novel evaluation method, which integrates the ranking of CPFNs and distance measure, is proposed to judge the cleaner production level. Subsequently, according to the characteristics of gold mines, the evaluation criteria system of cleaner production is constructed. Finally, a case of evaluating the cleaner production performance for three gold mines is provided to explain the application of the proposed method. Besides this, a systematic comparison analysis with other existent methods is conducted to reveal the advantages of our method. Results indicate that the proposed method is suitable and effective for gold mines to evaluate their cleaner production performance and has important reference values for the cleaner production management and implementation. [ABSTRACT FROM AUTHOR]

The information aggregation operator plays a key rule in the group decision making problems. The aim of this paper is to investigate the information aggregation operators method under the picture fuzzy environment with the help of Einstein norms operations. The picture fuzzy set is an extended version of the intuitionistic fuzzy set, which not only considers the degree of acceptance or rejection but also takes into the account of neutral degree during the analysis. Under these environments, some basic aggregation operators namely picture fuzzy Einstein weighted and Einstein ordered weighted operators are proposed in this paper. Some properties of these aggregation operators are discussed in detail. Further, a group decision making problem is illustrated and validated through a numerical example. A comparative analysis of the proposed and existing studies is performed to show the validity of the proposed operators. [ABSTRACT FROM AUTHOR]

In this paper, we define some Einstein operations on trapezoidal cubic fuzzy set and develop three arithmetic averaging operators, that is trapezoidal cubic fuzzy Einstein weighted averaging (TrCFEWA) operator, trapezoidal cubic fuzzy Einstein ordered weighted averaging (TrCFEOWA) operator and trapezoidal cubic fuzzy Einstein hybrid weighted averaging (TrCFEHWA) operator, for aggregating trapezoidal cubic fuzzy information. The TrCFEHWA operator generalizes both the TrCFEWA and TrCFEOWA operators. Furthermore, we establish various properties of these operators and derive the relationship between the proposed operators and the exiting aggregation operators. We apply on the TrCFEHWA operator to multiple attribute decision making with trapezoidal cubic fuzzy information. Finally, a numerical example is providing to demonstrate the submission of the established approach. [ABSTRACT FROM AUTHOR]

In this paper, we describe the idea of trapezoidal cubic hesitant fuzzy number. We discuss some basic operational laws of trapezoidal cubic hesitant fuzzy number and hamming distance of trapezoidal cubic hesitant fuzzy numbers (TrCHFNs). We introduce the new concept of the trapezoidal cubic hesitant fuzzy TOPSIS method. Furthermore, we extend the classical trapezoidal cubic hesitant fuzzy TOPSIS method to solve the MCDM method based on the trapezoidal cubic hesitant fuzzy TOPSIS method. The new ranking method for TrCHFNs is used to rank the alternatives. Finally, an illustrative example is given to verify and prove the practicality and effectiveness of the proposed method. We compared the proposed method to the existing methods, which shows the trapezoidal cubic hesitant Fuzzy TOPSIS method is more flexible to deal uncertainties and fuzziness. The main advantage of these operators is that it is to provide more accurate and significant results. [ABSTRACT FROM AUTHOR]

The cubic uncertain fuzzy linguistic variable can easily express the fuzzy information, and the power average (PA) operator is a useful tool which provides more versatility in the information aggregation procedure. In this paper, we will combine the PA operator and Einstein operations to cubic uncertain linguistic environment and propose some new PA operators. Firstly, the definition and some basic operations of cubic uncertain linguistic number, power aggregation (PA) operator and Einstein operations are introduced. Then, we propose cubic uncertain linguistic fuzzy powered Einstein averaging operator, cubic uncertain linguistic fuzzy powered Einstein weighted (CULFPEWA) operator, cubic uncertain linguistic fuzzy Einstein geometric operator and cubic uncertain linguistic fuzzy Einstein weighted geometric (CULFPEWG) operator and discuss some properties of these in detail. Furthermore, we develop the decision-making methods for multi-attribute group decision-making problems with cubic uncertain linguistic information and give the detail decision steps. At last, an illustrate example is given to show the process of decision making and the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The main objective of proposed work is to introduce a series of picture fuzzy weighted geometric aggregation operators by using t-norm and t-conorm. In this paper, we discussed generalized form of weighted geometric aggregation operator for picture fuzzy information. Further, the proposed geometric aggregation operators of picture fuzzy number are applied to multi-attribute group decision making problems. Also, we propose the TOPSIS method to aggregate the picture fuzzy information. To implement the proposed models, we provide some numerical applications of group decision making problems. Also compared with previous model, we conclude that the proposed technique is more effective and reliable. [ABSTRACT FROM AUTHOR]

The objective of the present work is divided into two folds. Firstly, interval-valued Pythagorean fuzzy Einstein hybrid weighted averaging aggregation operator has been introduced along with their several properties, namely idempotency, boundedness and monotonicity. Secondly, we apply the proposed operator to deal with multi-attribute group decision-making problem under Pythagorean fuzzy information. For this, we construct an algorithm for multi-attribute group decision making. At the last, we construct a numerical example for multi-attribute group decision making. The main advantage of using the proposed operator is that this operator provides more accurate and precise results is compared to the existing methods. [ABSTRACT FROM AUTHOR]

Pythagorean hesitant fuzzy sets play a vital role in decision-making as it permits a set of possible elements in membership and non-membership degrees and satisfy the condition that the square sum of its memberships degree is less than or equal to 1. While aggregation operators are used to aggregate the overall preferences of the attributes, under Pythagorean hesitant fuzzy environment and fuzzy measure in the paper we develop Pythagorean hesitant fuzzy Choquet integral averaging operator, Pythagorean hesitant fuzzy Choquet integral geometric operator, generalized Pythagorean hesitant fuzzy Choquet integral averaging operator and generalized Pythagorean hesitant fuzzy Choquet integral geometric operator. We also discuss some properties such as idempotency, monotonicity and boundedness of the developed operators. Moreover, we apply the developed operators to multi-attribute decision-making problem to show the validity and effectiveness of the developed operators. Finally, a comparison analysis is given. [ABSTRACT FROM AUTHOR]

The key objective of the proposed work in this paper is to introduce a new version of picture linguistic fuzzy set, so-called spherical linguistic fuzzy sets. The novel concept of spherical linguistic fuzzy set consists of linguistic term, positive, neutral and negative membership degrees which satisfies the conditions that the square sum of its membership degrees is less than or equal to 1. In this paper, we investigate the basic operations of spherical linguistic fuzzy sets and discuss some related results. We extend operational laws of aggregation operators and propose spherical linguistic fuzzy Choquet integral weighted averaging (SLFCIWA) operator based on spherical fuzzy numbers. Further, the proposed SLFCIWA operator of spherical fuzzy number is applied to multi-attribute group decision-making problems. Also, we propose the GRA method to aggregate the spherical fuzzy information. To implement the proposed models, we provide some numerical applications of group decision-making problems. Also compared with the previous model, we conclude that the proposed technique is more effective and reliable. [ABSTRACT FROM AUTHOR]

In this paper, some fundamental relationships of a Γ-semihypergroup and its operator semihypergroup in terms of fuzzy subsets, fuzzy hyperideals and fuzzy hyperideal extension are obtained. Using these in obtaining some characterization theorems of Γ-semihypergroups in terms of fuzzy subsets, we highlight the effectiveness of operator semihypergroups in the study of Γ-semihypergroups in terms of fuzzy subsets. [ABSTRACT FROM AUTHOR]

In the original article, the affiliation of first author has been incorrectly published. [ABSTRACT FROM AUTHOR]