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The massive spread of COVID-19 and the crash of China Eastern Airlines MU5735 have negatively impacted the public's perception of civil aviation safety, which further affects the progress of the civil aviation industry and economic growth. The aim of research is to investigate the public's perception of China's civil aviation safety and give the authorities corresponding suggestions. First, we use online comment collection and sentiment analysis techniques to construct a novel evaluation index system reflecting the public's greatest concern for civil aviation safety. Then, we propose two novel large-scale group decision-making (LSGDM) models for aggregating evaluation: (1) K-means clustering with a novel distance measure for evaluators combined with unsupervised K-means clustering in two-stage, (2) unsupervised K-means clustering for evaluators combined with unsupervised K-means clustering for processing evaluation in two-stage. Finally, we compare the characteristics of different models and use the average of the two models as the final evaluation results. [ABSTRACT FROM AUTHOR]

With the rapid development of the construction industry, buildings have become the single largest consumer of energy in the world. The retrofitting of existing buildings offers an excellent opportunity to reduce global energy consumption and promote sustainable development. As the retrofit strategy determines the success of the retrofitting process, this paper proposes a decision support framework for retrofitting that integrates the building information modeling (BIM) with large-scale group decision-making, which is a new application of digital technology to the retrofitting of existing buildings. Within this framework, BIM provides massive geometric and non-geometric data for the multi-criteria large-scale group decision-making process. Taking into account the needs of various stakeholder groups and sustainable principle, we establish a comprehensive and innovative evaluation index system for community retrofitting, and use the group best-worst method to determine the criteria weights. The stakeholers evaluate alternative retrofit strategies through distribution linguistic preferences, with a consistency-driven optimization model used to personalize the stakeholers' numerical evaluation scales. Through k-means clustering and the consensus-reaching process, combined with objective data from BIM, we obtain the ranking of the alternative strategies. Finally, we apply the abovementioned decision support framework to the retrofitting of the Suifeng Garden community in China to demonstrate the rationality and superiority of the proposed approach. • We propose a building information modeling (BIM)-aided large-scale group decision-making framework. • We evaluate the weights of diverse stakeholder groups in terms of power, legitimacy, and urgency. • We integrate k-means clustering and multi-objective optimization models for consensus reaching process. • We establish a comprehensive evaluation criteria system for community retrofitting. [ABSTRACT FROM AUTHOR]

The byproduct gas in steel industry is one of the most significant energy resources of an enterprise. Due to the large quantity of yield, fluctuation, and various categories of users encountered in a blast furnace gas (BFG) system, it is very difficult to accurately predict the amount of gas to be generated and forecast the users' consumption demand. In this paper, a two-stage online prediction method based on an improved echo state network (ESN) is proposed to realize forecasting in the BFG system. In this method, one completes the prediction realized at the levels of BFG generation and consumption using a class of ESN with input compensation and parameter optimization. At the second stage, to predict gas holder level of the BFG system, the energy flows being predicted at the first stage are denoised, and their correlation with the holder level are determined by using a concept of grey correlation with time delay. Then the effect factors exhibiting high correlation levels are extracted to construct the model of the gas holder. The prediction system designed in this manner is applied in the Energy Center of Baosteel Co., Ltd, China. The results demonstrate that the prediction system exhibits high accuracy and can provide an effective guidance for balancing and scheduling of the byproduct energy. [ABSTRACT FROM PUBLISHER]

· Proposing a novel 3WD-GMCR framework under hesitant fuzzy environment. · Improving the option prioritization to explain the ranking strength of states. · Redefining the concepts of conflict stability. · Embedding the DMs' preference differences into the stability analysis. Multi-criteria decision aiding/making (MCDA/M) approach and three-way decisions (3WD) are embedded into the framework of graph model for conflict resolution (GMCR). The objective of this study is to develop more reasonable preference ranking for decision makers (DMs) produced from the perspective of options. This implies further simplification of the underlying computing behind conflict resolution. More specifically, DMs' original option statements are evaluated by hesitant fuzzy sets (HFSs), then a three-way decisions approach is used to screen out the infeasible and rank the feasible option statements, and the feasible option statements' loss values of three-way decisions approach are determined based on the hesitant fuzzy (HF) evaluation values. In addition, based on the value of conditional probability of the feasible option statements, an improved option prioritization technique with objective weights is developed to efficiently rank the conflict states, so that it can efficiently reflect the intensity of the ranking. Then, considering the preference thresholds of DMs, new definitions of threshold stabilities are proposed. As demonstrated by the case study in the problem of a carbon emission conflict in supply chain under "3060 carbon peak and neutrality" goal in China, the proposed novel three-way decisions graph model for conflict resolution (3WD-GMCR) framework can be widely applied to the realistic scenarios of decision-making. Compared with previous studies, the proposed approach can not only obtain the intensity ranking of conflict states, but also resolve complex large-scale conflicts effectively. [ABSTRACT FROM AUTHOR]

High-speed rail (HSR) has become an essential mode of public transportation in China and is likely to remain so for the foreseeable future. To promote the development of the HSR industry, a high level of passenger satisfaction must be ensured, which means that passenger satisfaction must be assured. Focusing on HSR in-cabin factors that affect the travel experience of HSR passengers, this study aims to determine passenger demands (PDs) and to evaluate passenger satisfaction by using a combination of online review analysis and large-scale group decision-making (LSGDM). By using web crawler technology, online reviews related to HSR were harvested from a microblogging platform to extract PD data and information. The six PDs that reflect the most frequent concerns of passengers were identified by analyzing the online reviews. The level of satisfaction of passengers with respect to these PDs was analyzed based on the online responses from 100 HSR passengers and by adopting the interval-valued two-tuple linguistic representation model. The final degrees of satisfaction and rankings of the PDs were then determined by using the LSGDM approach with the k -means clustering method and a consensus-reaching process. This research thus constructs an index system of HSR passenger satisfaction evaluation based on online-review analysis and evaluates the process by using LSGDM approaches. The conclusions provide insights into the improvements desired by HSR passengers for in-cabin services and to improve passenger satisfaction. • Six passenger demands (PDs) of high-speed rail (HSR) are identified using online review analysis. • The linguistic representation model is applied for the expression of satisfaction degrees regarding PDs. • The final satisfaction degrees and ranking orders of the PDs are determined using a novel LSGDM approach. • Useful insights are provided for the desired improvement of service quality and passenger satisfaction of HSR. [ABSTRACT FROM AUTHOR]