Article
Computer Science, Artificial Intelligence
Linyu Li, Zichun Chen, Xiaowei Jiang
Summary: In this paper, a hybrid picture fuzzy similarity measure is proposed, which combines the Hamming distance and the transformed tetrahedral centroid distance. Numerical examples and applications of pattern recognition demonstrate the advantages of the proposed measure over existing similarity measures. Furthermore, the effectiveness and practicability of an improved VIKOR method based on the proposed similarity measure are illustrated through a case study.
INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Abdul Haseeb Ganie, Surender Singh
Summary: This study introduces a novel picture fuzzy (PF) similarity measure for modeling fuzzy sets and for multi-attribute decision-making, which overcomes some drawbacks of existing methods.
NEURAL COMPUTING & APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Amandeep Singh, Satish Kumar
Summary: Compared to fuzzy and intuitionistic fuzzy sets, picture fuzzy sets are considered effective tools for decision-making problems. This paper proposes a novel picture fuzzy knowledge measure and derives a new picture fuzzy accuracy measure, demonstrating their performance and validation in applications.
APPLIED SOFT COMPUTING
(2023)
Article
Computer Science, Artificial Intelligence
Jiulin Jin, Harish Garg, Taijie You
Summary: This study aims to develop a fuzzy evaluation system to overcome the limitations of existing picture fuzzy distance and similarity measures. By categorizing and restricting the score functions, the limitations of the measures are determined. A probability-based score function is proposed and applied to depict generalized picture fuzzy distance and similarity. Experimental results confirm the effectiveness of the proposed method.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Vikas Arya, Satish Kumar
Summary: The paper introduces a new entropy measure based on picture fuzzy sets (PFS) and discusses its properties in detail. It also proposes an entropy-based decision-making method for picture fuzzy MCDM problems with the integration of subjective and objective weights to provide more objective evaluation results.
COGNITIVE COMPUTATION
(2021)
Article
Mathematics, Applied
Jun Hu, Jie Wu, Mengzhe Wang
Summary: This study proposes a decision-making method based on interval Pythagorean triangular fuzzy numbers, which combines the advantages of interval Pythagorean fuzzy numbers and triangular fuzzy numbers to handle fuzzy information more accurately, thus improving the scientificity and effectiveness of decision-making.
Article
Computer Science, Information Systems
Minxia Luo, Yue Zhang, Li Fu
Summary: Picture fuzzy sets, as an extension of intuitionistic fuzzy sets, are able to handle vague, uncertain, incomplete and inconsistent information. This study proposes a similarity measure between picture fuzzy sets based on relationship matrix, which satisfies the axiomatic definition of similarity measure. Numerical experiments demonstrate the effectiveness of the new similarity measure, which is then applied to multiple-attribute decision making.
Article
Computer Science, Artificial Intelligence
Adeeba Umar, Ram Naresh Saraswat
Summary: Tools such as entropy, divergence measures, and similarity measures are widely applied to real-world problems in decision-making, robotics, pattern recognition, clustering, expert systems, and medical diagnosis. Picture fuzzy set (PFS) is a generalization of fuzzy set (FS) and intuitionistic fuzzy set (IFS) that shows better adaptation to various real-world problems. The development and application of a divergence measure for PFS in decision-making and machine learning have shown promising results in improving effectiveness and efficiency compared to existing methods.
NEURAL COMPUTING & APPLICATIONS
(2022)
Article
Computer Science, Artificial Intelligence
Abdul Haseeb Ganie, Surender Singh
Summary: The study introduces a novel picture fuzzy distance measure based on direct operations on membership functions, and discusses its advantages in pattern classification problems. Conversion formulae are derived to apply the proposed method in real data sets. Additionally, a new multi-attribute decision-making method using the proposed PF distance measure is introduced and its performance is compared with classical methods in a PF environment.
COMPLEX & INTELLIGENT SYSTEMS
(2021)
Article
Mathematics, Applied
R. R. Zhao, M. X. Luo, S. G. Li, L. N. Ma
Summary: This paper proposes a parametric similarity measure to handle unreasonable cases in picture fuzzy sets. The effectiveness of the proposed measure is demonstrated through numerical examples.
IRANIAN JOURNAL OF FUZZY SYSTEMS
(2023)
Article
Automation & Control Systems
Mridul Krishna Gogoi, Rituparna Chutia
Summary: Crop selection involves various risk factors, and probabilistic methods and possibilistic analysis can be used to evaluate these risks, with linguistic variables observed as fuzzy numbers. The goal of fuzzy risk analysis is to transform final risks into communicable linguistic variables, using similarity measure as a tool for transformation.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2022)
Article
Computer Science, Artificial Intelligence
Xindong Peng, Huiyong Yuan
Summary: This paper introduces the application of Pythagorean fuzzy sets in big data industry decision-making, including scoring functions, distance measures, similarity measures, and weight determination. The fuzzy problem is solved through multiparametric similarity measure, and the effectiveness of the algorithm is elaborated.
COGNITIVE COMPUTATION
(2021)
Article
Green & Sustainable Science & Technology
Morteza Noruzi, Ali Naderan, Jabbar Ali Zakeri, Kamran Rahimov
Summary: This study evaluates and selects rail transportation projects according to sustainability criteria. Using the stochastic VIKOR approach, the projects are evaluated under different scenarios of demand changes and cost changes. The main contribution of this study is the introduction of the stochastic VIKOR approach and considering uncertainty in project evaluation.
Article
Engineering, Multidisciplinary
Ravinder Kumar, Gaurav Gupta, Muhammad Gulzar, Dragan Pamucar, Neeraj Gandotra, Md. Ashraful Alam
Summary: A novel entropy measure centered around PFS was proposed in this study to handle real-world problems related to the relative importance of attributes. The method provides a more accurate way to deal with uncertainty. The practicality of the method was demonstrated through validation proofs and application to polling data outcomes.
MATHEMATICAL PROBLEMS IN ENGINEERING
(2022)
Article
Computer Science, Artificial Intelligence
Vakkas Ulucay, Irfan Deli
Summary: This paper introduces the application of entropy measures in generalized hesitant trapezoidal fuzzy numbers and develops a new multi-criteria decision-making method based on this. The proposed method is not only a way to solve multi-criteria decision-making problems, but also contains important mathematical ideas. By solving an illustrative example and comparing the results with other methods, it is shown that the proposed method is more suitable for dealing with uncertain and imprecise information.
Article
Thermodynamics
Congjun Rao, Yue Zhang, Jianghui Wen, Xinping Xiao, Mark Goh
Summary: This paper analyzes the drivers of energy demand in China and predicts the future consumption of different forms of energy. The results indicate that China's energy demand will continue to grow in the next decade, with the highest growth rate observed in natural gas and primary electricity. However, the demand for coal is expected to decline gradually.
Article
Computer Science, Artificial Intelligence
Congjun Rao, Mingyun Gao, Mark Goh, Xinping Xiao
Summary: This paper presents a novel green supplier selection mechanism based on an uncertain information environment. By considering economic, environmental, and social factors, and using Z-numbers for ranking, the proposed mechanism improves the efficiency and feasibility of selecting green suppliers.
COGNITIVE COMPUTATION
(2023)
Article
Computer Science, Artificial Intelligence
Congjun Rao, Ying Liu, Mark Goh
Summary: This paper investigates the credit risk assessment mechanism for personal auto loans. A machine learning based model incorporating Smote-Tomek Link algorithm and Filter-Wrapper feature selection method is proposed. By combining Particle Swarm Optimization and eXtreme Gradient Boosting model, a superior PSO-XGBoost model is formed, showing better classification performance and effect.
COMPLEX & INTELLIGENT SYSTEMS
(2023)
Article
Computer Science, Interdisciplinary Applications
Zhang-peng Tian, He-ming Liang, Ru-xin Nie, Xiao-kang Wang, Jian-qiang Wang
Summary: This paper proposes a sentiment analysis-based multi-criteria decision-making method to help consumers make EV purchase choices. The sentiment analysis results are transformed into hesitant intuitionistic fuzzy elements to derive the group opinion for each alternative. A comprehensive weighting method is developed to determine the weights of criteria. The ranking of candidate EV series can be obtained through the extended ORESTE method based on hesitant intuitionistic fuzzy Chebyshev distance. The results of sentiment analysis can also be useful for companies to explore consumers' demand for EVs.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
Article
Biochemistry & Molecular Biology
Zhe Chen, Xiaolu Qu, Chungang Feng, Binbin Guo, Huanxi Zhu, Leyan Yan
Summary: The influence of monochromatic green light on hatching performance and embryo development in geese was investigated. The involvement of the liver in green light transduction and its underlying molecular mechanisms were also studied. The results showed that green light promoted embryonic development and hatching performance, with effects on myogenic regulatory factors and energy metabolism in the liver and muscle.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Article
Education & Educational Research
Wei Wang, Yongyong Zhao, Yenchun Jim Wu, Mark Goh
Summary: This study examined the impact of rhetoric in endorsement texts on public willingness to participate in citizen science projects. Four types of endorsers were studied: professors, students, industrial researchers, and amateur researchers. Using a corpus of 1243 endorsement texts from 543 citizen science projects, the study empirically analyzed the effects of standalone techniques (ethos, pathos, and logos) and mixed-rhetoric techniques of persuasion. The results showed that pathos and logos were more effective than ethos. A mixed-rhetoric approach with a combination of 55% pathos and 45% logos maximized the appeal of citizen science projects, with an inverted U-shaped effect. The rhetorical strategies used by professors, students, and amateur researchers were similar, while industrial researchers had a different approach. However, the influence of endorsement strategies differed between professors (positive for logos only) and students (positive for pathos only) compared to amateur and industrial researchers (both pathos and logos were positive). Furthermore, endorsement rhetoric had a greater impact on humanities and social science projects compared to natural science projects.
INTERNATIONAL JOURNAL OF SCIENCE EDUCATION PART B-COMMUNICATION AND PUBLIC ENGAGEMENT
(2023)
Article
Operations Research & Management Science
Junliang Du, Naiming Xie, Sifeng Liu, Mark Goh
Summary: In the era of Big Data, decision-making has become more complex and uncertain. The fuzzy linguistic approach provides a closer representation to natural language and people's cognitive habits. The concept of grey linguistic term set (GLTS) is proposed to describe uncertain linguistic terms and can effectively support data generation, processing, and fusion in Big Data.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Education & Educational Research
Wei Wang, Haiwang Liu, Yenchun Jim Wu, Mark Goh
Summary: This study examines the consistency of online course reviews and the determinants of learner satisfaction in MOOCs. The results suggest a strong disconfirmation effect between textual reviews and learner satisfaction, with negative reviews having a stronger impact.
EDUCATION AND INFORMATION TECHNOLOGIES
(2023)
Article
Social Sciences, Interdisciplinary
Qun Wang, Kai Huang, Mark Goh, Zeyu Jiao, Guozhu Jia
Summary: Smart data selection improves decision-making efficiency by quickly identifying valuable information from initial data. This study introduces a modified Decision-Making Trial and Evaluation Laboratory (DEMATEL) method based on objective data grey relational analysis (GRA) to enhance the analysis of time-series data. The results of applying this method to predict the remaining useful life (RUL) of aircraft engines indicate its accuracy and potential applications.
Article
Green & Sustainable Science & Technology
Mingyun Gao, Lixin Xia, Qinzi Xiao, Mark Goh
Summary: With the increasing climate disasters, consumers have a growing interest in low-carbon products. This paper analyzes incentive strategies for low-carbon supply chains considering the updating of low-carbon preferences. It describes information updating in low-carbon supply chains and analyzes the response decisions of the supply chain under the given incentive strategies. An optimal model of carbon reduction is designed for the government based on these decisions, and the best incentive strategies are optimized using a heuristic algorithm. The results show that cooperation among profit-driven supply chain members improves both their profits and carbon reduction efficiency.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Mathematics
Zhiping Hou, Sangsang He, Ruxia Liang, Junbo Li, Ruilu Huang, Jianqiang Wang
Summary: Evaluation of hotel website service quality has received extensive attention, but previous studies have overlooked human hesitance and uncertainty in judgments, as well as the simultaneous consideration of hotel managers and customers' psychological behaviors. This study explores criteria for evaluating the service quality of economy hotel websites and proposes a hybrid evaluation model to address hesitation and uncertainty. The model utilizes probabilistic linguistic term sets to capture qualitative assessments and applies analytical network process to prioritize website features. It further integrates the TODIM-PROMETHEE II method to rank alternatives considering psychological factors. The effectiveness of the model is illustrated through a case study of economy hotel websites in China, highlighting service competence and customer relationship as the most important performance features. Conclusions and implications are derived from the results.
Article
Transportation
Yaoming Zhou, Tanmoy Kundu, Mark Goh, Shankar Chakraborty, Xiwen Bai
Summary: This paper proposes a comprehensive multi-stage multi-criteria data analytics approach that combines data envelopment analysis, best-worst method, and multi-attributive border approximation area comparison method to provide a robust ranking framework for commercial service airports. The proposed method ranks the shortlisted airports based on seven criteria and evaluates their strengths and weaknesses. A real-world example in China is used to validate the applicability of the proposed approach and generate insights for airport benchmarking.
JOURNAL OF AIR TRANSPORT MANAGEMENT
(2023)
Article
Business
Jun-Liang Du, Si-Feng Liu, Saad Ahmed Javed, Mark Goh, Zhen-Song Chen
Summary: This article presents a novel rough set theory-based ordinal priority approach (OPA-R) methodology to enhance traditional Quality Function Deployment (QFD) by eliminating the need for fuzzy linguistic variables and pairwise comparison matrices. The proposed methodology uses experts' ordinal priorities to evaluate customer requirements and the interrelations between requirements and engineering characteristics. The validity and advantages of the proposed model are demonstrated through a case study in the manufacturing of electric vehicles.
IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT
(2023)
Article
Business
Xu Zhang, Mark Goh, Sijun Bai, Zonghan Wang, Qun Wang
Summary: This study provides a decision model for making robust risk response decisions for single projects within project portfolios under uncertain project interdependencies. The model uses a four-stage interval optimization model based on a two-tier risk-project network. The results show that considering project interdependencies is more beneficial for decision makers compared to ignoring interdependencies or considering them with certainty.
IEEE TRANSACTIONS ON ENGINEERING MANAGEMENT
(2023)
Article
Environmental Sciences
Congjun Rao, Qifan Huang, Lin Chen, Mark Goh, Zhuo Hu
Summary: The impact of global greenhouse gas emissions is increasingly serious, and the development of green low-carbon circular economy has become an inevitable trend for the development of all countries in the world. To achieve emission peak and carbon neutrality is the primary goal of energy conservation and emission reduction. This paper analyzes the future development trend of carbon emissions in Hubei Province, predicts the emission peak value and carbon peak time, and provides corresponding suggestions on carbon emission reduction.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2023)
Article
Green & Sustainable Science & Technology
Lars odegaard Bentsen, Narada Dilp Warakagoda, Roy Stenbro, Paal Engelstad
Summary: This study investigates uncertainty modeling in wind power forecasting using different parametric and non-parametric methods. Johnson's SU distribution is found to outperform Gaussian distributions in predicting wind power. This research contributes to the literature by introducing Johnson's SU distribution as a candidate for probabilistic wind forecasting.
JOURNAL OF CLEANER PRODUCTION
(2024)
Article
Green & Sustainable Science & Technology
Xing Liu, Qiuchen Wang, Yunhao Wen, Long Li, Xinfang Zhang, Yi Wang
Summary: This study analyzes the characteristics of process parameters in three lean gas ethane recovery processes and establishes a prediction and multiobjective optimization model for ethane recovery and system energy consumption. A new method for comparing ethane recovery processes for lean gas is proposed, and the addition of extra coolers improves the ethane recovery. The support vector regression model based on grey wolf optimization demonstrates the highest prediction accuracy, and the multiobjective multiverse optimization algorithm shows the best optimization performance and diversity in the solutions.
JOURNAL OF CLEANER PRODUCTION
(2024)
Article
Green & Sustainable Science & Technology
Cairong Song, Haidong Yang, Xian-Bing Meng, Pan Yang, Jianyang Cai, Hao Bao, Kangkang Xu
Summary: The paper proposes a novel deep learning-based prediction framework, aTCN-LSTM, for accurate cooling load predictions. The framework utilizes a gate-controlled multi-head temporal convolutional network and a sparse probabilistic self-attention mechanism with a bidirectional long short-term memory network to capture both temporal and long-term dependencies in the cooling load sequences. Experimental results demonstrate the effectiveness and superiority of the proposed method, which can serve as an effective guide for HVAC chiller scheduling and demand management initiatives.
JOURNAL OF CLEANER PRODUCTION
(2024)
Article
Green & Sustainable Science & Technology
Zhe Chen, Xiaojing Li, Xianli Xia, Jizhou Zhang
Summary: This study uses survey data from the Loess Plateau in China to evaluate the impact of social interaction on the adoption of soil and water conservation (SWC) technology by farmers. The study finds that social interaction increases the likelihood of farmers adopting SWC, and internet use moderates this effect. The positive impact of social interaction on SWC adoption is more pronounced for farmers in larger villages and those who join cooperative societies.
JOURNAL OF CLEANER PRODUCTION
(2024)
Article
Green & Sustainable Science & Technology
Chenghua Zhang, Yunfei Yan, Kaiming Shen, Zongguo Xue, Jingxiang You, Yonghong Wu, Ziqiang He
Summary: This paper reports a novel method that significantly improves combustion performance, including heat transfer enhancement under steady-state conditions and adaptive stable flame regulation under velocity sudden increase.
JOURNAL OF CLEANER PRODUCTION
(2024)
