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322 results on '"Nawi, Nazri Mohd"'

301. Forecasting of Malaysian Oil Production and Oil Consumption Using Fuzzy Time Series

Author

Efendi, Riswan, Deris, Mustafa Mat, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Herawan, Tutut, editor, Ghazali, Rozaida, editor, Nawi, Nazri Mohd, editor, and Deris, Mustafa Mat, editor

Published
2017
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302. Optimization of ANFIS Using Artificial Bee Colony Algorithm for Classification of Malaysian SMEs

Author

Salleh, Mohd. Najib Mohd., Hussain, Kashif, Naseem, Rashid, Uddin, Jamal, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Herawan, Tutut, editor, Ghazali, Rozaida, editor, Nawi, Nazri Mohd, editor, and Deris, Mustafa Mat, editor

Published
2017
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303. Training ANFIS Using Catfish-Particle Swarm Optimization for Classification

Author

Hassan, Norlida, Ghazali, Rozaida, Hussain, Kashif, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Herawan, Tutut, editor, Ghazali, Rozaida, editor, Nawi, Nazri Mohd, editor, and Deris, Mustafa Mat, editor

Published
2017
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304. Time Series Forecasting Using Ridge Polynomial Neural Network with Error Feedback

Author

Waheeb, Waddah, Ghazali, Rozaida, Herawan, Tutut, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Herawan, Tutut, editor, Ghazali, Rozaida, editor, Nawi, Nazri Mohd, editor, and Deris, Mustafa Mat, editor

Published
2017
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305. Cluster Validation Analysis on Attribute Relative of Soft-Set Theory

Author

Mamat, Rabiei, Noor, Ahmad Shukri Mohd, Herawan, Tutut, Deris, Mustafa Mat, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Herawan, Tutut, editor, Ghazali, Rozaida, editor, Nawi, Nazri Mohd, editor, and Deris, Mustafa Mat, editor

Published
2017
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306. An Implementation of Local Regression Smoothing on Evolving Fuzzy Algorithm for Planting Calendar Forecasting Based on Rainfall

Author

Saputro, Arizal Akbar Rahma, Nhita, Fhira, Adiwijaya, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Herawan, Tutut, editor, Ghazali, Rozaida, editor, Nawi, Nazri Mohd, editor, and Deris, Mustafa Mat, editor

Published
2017
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307. Computing the Metric Dimension of Hypercube Graphs by Particle Swarm Optimization Algorithms

Author

Murdiansyah, Danang Triantoro, Adiwijaya, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Herawan, Tutut, editor, Ghazali, Rozaida, editor, Nawi, Nazri Mohd, editor, and Deris, Mustafa Mat, editor

Published
2017
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308. Non-linear Based Fuzzy Random Regression for Independent Variable Selection

Author

Salikon, Mohd Zaki Mohd, Arbaiy, Nureize, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Herawan, Tutut, editor, Ghazali, Rozaida, editor, Nawi, Nazri Mohd, editor, and Deris, Mustafa Mat, editor

Published
2017
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309. Chebyshev Multilayer Perceptron Neural Network with Levenberg Marquardt-Back Propagation Learning for Classification Tasks

Author

Iqbal, Umer, Ghazali, Rozaida, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Herawan, Tutut, editor, Ghazali, Rozaida, editor, Nawi, Nazri Mohd, editor, and Deris, Mustafa Mat, editor

Published
2017
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310. A Review on Violence Video Classification Using Convolutional Neural Networks

Author

Ali, Ashikin, Senan, Norhalina, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Herawan, Tutut, editor, Ghazali, Rozaida, editor, Nawi, Nazri Mohd, editor, and Deris, Mustafa Mat, editor

Published
2017
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311. Modified Backpropagation Algorithm for Polycystic Ovary Syndrome Detection Based on Ultrasound Images

Author

Wisesty, Untari N., Nasri, Jondri, Adiwijaya, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Herawan, Tutut, editor, Ghazali, Rozaida, editor, Nawi, Nazri Mohd, editor, and Deris, Mustafa Mat, editor

Published
2017
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312. A Study of Data Imputation Using Fuzzy C-Means with Particle Swarm Optimization

Author

Samat, Nurul Ashikin, Salleh, Mohd Najib Mohd, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Herawan, Tutut, editor, Ghazali, Rozaida, editor, Nawi, Nazri Mohd, editor, and Deris, Mustafa Mat, editor

Published
2017
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313. One-Way ANOVA Model with Fuzzy Data for Consumer Demand

Author

Lin, Pei Chun, Arbaiy, Nureize, Hamid, Isredza Rahmi Abd., Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Herawan, Tutut, editor, Ghazali, Rozaida, editor, Nawi, Nazri Mohd, editor, and Deris, Mustafa Mat, editor

Published
2017
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314. Utilizing Clonal Selection Theory Inspired Algorithms and K-Means Clustering for Predicting OPEC Carbon Dioxide Emissions from Petroleum Consumption

Author

Lasisi, Ayodele, Ghazali, Rozaida, Chiroma, Haruna, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Herawan, Tutut, editor, Ghazali, Rozaida, editor, Nawi, Nazri Mohd, editor, and Deris, Mustafa Mat, editor

Published
2017
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315. Erratum to: Text Detection in Low Resolution Scene Images Using Convolutional Neural Network

Author

Risnumawan, Anhar, Sulistijono, Indra Adji, Abawajy, Jemal, Kacprzyk, Janusz, Series Editor, Pal, Nikhil R., Advisory Editor, Bello Perez, Rafael, Advisory Editor, Corchado, Emilio S., Advisory Editor, Hagras, Hani, Advisory Editor, Kóczy, László T., Advisory Editor, Kreinovich, Vladik, Advisory Editor, Lin, Chin-Teng, Advisory Editor, Lu, Jie, Advisory Editor, Melin, Patricia, Advisory Editor, Nedjah, Nadia, Advisory Editor, Nguyen, Ngoc Thanh, Advisory Editor, Wang, Jun, Advisory Editor, Herawan, Tutut, editor, Ghazali, Rozaida, editor, Nawi, Nazri Mohd, editor, and Deris, Mustafa Mat, editor

Published
2017
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316. Global Warming: Predicting OPEC Carbon Dioxide Emissions from Petroleum Consumption Using Neural Network and Hybrid Cuckoo Search Algorithm.

Author

Chiroma, Haruna, Abdul-kareem, Sameem, Khan, Abdullah, Nawi, Nazri Mohd., Gital, Abdulsalam Ya’u, Shuib, Liyana, Abubakar, Adamu I., Rahman, Muhammad Zubair, and Herawan, Tutut

Subjects
*CARBON dioxide mitigation, *GLOBAL warming, *PETROLEUM & the environment, *ARTIFICIAL neural networks, *SEARCH algorithms
Abstract

Background: Global warming is attracting attention from policy makers due to its impacts such as floods, extreme weather, increases in temperature by 0.7°C, heat waves, storms, etc. These disasters result in loss of human life and billions of dollars in property. Global warming is believed to be caused by the emissions of greenhouse gases due to human activities including the emissions of carbon dioxide (CO2) from petroleum consumption. Limitations of the previous methods of predicting CO2 emissions and lack of work on the prediction of the Organization of the Petroleum Exporting Countries (OPEC) CO2 emissions from petroleum consumption have motivated this research. Methods/Findings: The OPEC CO2 emissions data were collected from the Energy Information Administration. Artificial Neural Network (ANN) adaptability and performance motivated its choice for this study. To improve effectiveness of the ANN, the cuckoo search algorithm was hybridised with accelerated particle swarm optimisation for training the ANN to build a model for the prediction of OPEC CO2 emissions. The proposed model predicts OPEC CO2 emissions for 3, 6, 9, 12 and 16 years with an improved accuracy and speed over the state-of-the-art methods. Conclusion: An accurate prediction of OPEC CO2 emissions can serve as a reference point for propagating the reorganisation of economic development in OPEC member countries with the view of reducing CO2 emissions to Kyoto benchmarks—hence, reducing global warming. The policy implications are discussed in the paper. [ABSTRACT FROM AUTHOR]

Published
2015
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317. Enhanced Bat Algorithm for Solving Non-Convex Economic Dispatch Problem

Author

Hussain, Kashif, Zhu, William, Salleh, Mohd Najib Mohd, Ali, Haseeb, Talpur, Noreen, Naseem, Rashid, Ahmad, Arshad, Ullah, Ayaz, Ghazali, Rozaida, Nawi, Nazri Mohd, Deris, Mustafa Mat, and Abawajy, Jemal H.

Abstract

Bat algorithm lags behind other modern metaheuristic algorithms in terms of search efficiency, due to premature convergence. Once trapped in any sub-optimal region, the algorithm is unable to escape because of deficiency in population diversity. To address this, an enhanced Bat Algorithm (EBA) is introduced in this paper. The EBA algorithm comes with adaptive exploration and exploitation capability, as well as, additional population diversity. This enables EBA improve its convergence ability to find even better solutions towards the end of search process, where standard BA is often trapped. To illustrate effectiveness of the proposed method, EBA is applied on non-linear, non-convex economic dispatch problem with a power generation system comprising of twenty thermal units. The experimental results suggest that EBA not only saved power generation cost but also reduced transmission losses, more efficiently as compared to original BA and other methods reported in literature. The EBA algorithm also showed enhanced convergence ability than BA towards the end of iterations.

Published
2019

318. Training ANFIS Using Catfish-Particle Swarm Optimization for Classification

Author

Hassan, Norlida, Ghazali, Rozaida, Hussain, Kashif, Herawan, Tutut, Ghazali, Rozaida, Nawi, Nazri Mohd, and Deris, Mustafa Mat

Abstract

ANFIS performance depends on the parameters it is trained with. Therefore, the training mechanism needs to be faster and reliable. Many have trained ANFIS parameters using GD, LSE, and metaheuristic techniques but the efficient one are still to be developed. Catfish-PSO algorithm is one of the latest successful swarm intelligence based technique which is used in this research for training ANFIS. As opposed to standard PSO, Catfish-PSO has string exploitation and exploration capability. The experimental results of training ANFIS network for classification problems show that Catfish-PSO algorithm achieved much better accuracy and satisfactory results.

Published
2016

319. Optimization of ANFIS Using Artificial Bee Colony Algorithm for Classification of Malaysian SMEs

Author

Salleh, Mohd. Najib Mohd., Hussain, Kashif, Naseem, Rashid, Uddin, Jamal, Herawan, Tutut, Ghazali, Rozaida, Nawi, Nazri Mohd, and Deris, Mustafa Mat

Abstract

Adaptive Neuro-Fuzzy Inference System (ANFIS) has been widely applied in industry as well as scientific problems. This is due to its ability to approximate every plant with proper number of rules. However, surge in auto-generated rules, as the inputs increase, adds up to complexity and computational cost of the network. Therefore, optimization is required by pruning the weak rules while, at the same time, achieving maximum accuracy. Moreover, it is important to note that over-reducing rules may result in loss of accuracy. Artificial Bee Colony (ABC) is widely applied swarm-based technique for searching optimum solutions as it uses few setting parameters. This research explores the applicability of ABC algorithm to ANFIS optimization. For the practical implementation, classification of Malaysian SMEs is performed. For validation, the performance of ABC is compared with one of the popular optimization techniques Particle Swarm Optimization (PSO) and recently developed Mine Blast Algorithm (MBA). The evaluation metrics include number of rules in the optimized rule-base, accuracy, and number of iterations to converge. Results indicate that ABC needs improvement in exploration strategy in order to avoid trap in local minima. However, the application of any efficient metaheuristic with the modified two-pass ANFIS learning algorithm will provide researchers with an approach to effectively optimize ANFIS when the number of inputs increase significantly.

Published
2016

320. Recent advancement in VM task allocation system for cloud computing: review from 2015 to2021.

Author

Ullah A, Nawi NM, and Ouhame S

Abstract

Cloud computing is new technology that has considerably changed human life at different aspect over the last decade. Especially after the COVID-19 pandemic, almost all life activity shifted into cloud base. Cloud computing is a utility where different hardware and software resources are accessed on pay per user ground base. Most of these resources are available in virtualized form and virtual machine (VM) is one of the main elements of visualization.VM used in data center for distribution of resource and application according to benefactor demand. Cloud data center faces different issue in respect of performance and efficiency for improvement of these issues different approaches are used. Virtual machine play important role for improvement of data center performance therefore different approach are used for improvement of virtual machine efficiency (i-e) load balancing of resource and task. For the improvement of this section different parameter of VM improve like makespan, quality of service, energy, data accuracy and network utilization. Improvement of different parameter in VM directly improve the performance of cloud computing. Therefore, we conducting this review paper that we can discuss about various improvements that took place in VM from 2015 to 20,201. This review paper also contain information about various parameter of cloud computing and final section of paper present the role of machine learning algorithm in VM as well load balancing approach along with the future direction of VM in cloud data center., Competing Interests: Competing interestThe authors declare that they have no competing interests., (© The Author(s), under exclusive licence to Springer Nature B.V. 2021.)

Published
2022
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321. A novel state space reduction algorithm for team formation in social networks.

Author

Rehman MZ, Zamli KZ, Almutairi M, Chiroma H, Aamir M, Kader MA, and Nawi NM

Subjects
Computer Graphics, Computer Heuristics, Databases, Factual, Humans, Motion Pictures, Algorithms, Cooperative Behavior, Social Networking
Abstract

Team formation (TF) in social networks exploits graphs (i.e., vertices = experts and edges = skills) to represent a possible collaboration between the experts. These networks lead us towards building cost-effective research teams irrespective of the geolocation of the experts and the size of the dataset. Previously, large datasets were not closely inspected for the large-scale distributions & relationships among the researchers, resulting in the algorithms failing to scale well on the data. Therefore, this paper presents a novel TF algorithm for expert team formation called SSR-TF based on two metrics; communication cost and graph reduction, that will become a basis for future TF's. In SSR-TF, communication cost finds the possibility of collaboration between researchers. The graph reduction scales the large data to only appropriate skills and the experts, resulting in real-time extraction of experts for collaboration. This approach is tested on five organic and benchmark datasets, i.e., UMP, DBLP, ACM, IMDB, and Bibsonomy. The SSR-TF algorithm is able to build cost-effective teams with the most appropriate experts-resulting in the formation of more communicative teams with high expertise levels., Competing Interests: The authors have declared that no competing interests exist.

Published
2021
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322. A new Multi Sine-Cosine algorithm for unconstrained optimization problems.

Author

Rehman MZ, Khan A, Ghazali R, Aamir M, and Nawi NM

Abstract

The Sine-Cosine algorithm (SCA) is a population-based metaheuristic algorithm utilizing sine and cosine functions to perform search. To enable the search process, SCA incorporates several search parameters. But sometimes, these parameters make the search in SCA vulnerable to local minima/maxima. To overcome this problem, a new Multi Sine-Cosine algorithm (MSCA) is proposed in this paper. MSCA utilizes multiple swarm clusters to diversify & intensify the search in-order to avoid the local minima/maxima problem. Secondly, during update MSCA also checks for better search clusters that offer convergence to global minima effectively. To assess its performance, we tested the MSCA on unimodal, multimodal and composite benchmark functions taken from the literature. Experimental results reveal that the MSCA is statistically superior with regards to convergence as compared to recent state-of-the-art metaheuristic algorithms, including the original SCA., Competing Interests: The authors have declared that no competing interests exist.

Published
2021
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