Article
Computer Science, Artificial Intelligence
Guo-Niu Zhu, Jie Hu
Summary: In the context of smart product-service systems, evaluating co-creative sustainable value propositions becomes a critical issue. This paper proposes a framework integrating rough-Z-number, DEMATEL, and group decision-making strategy for evaluating these co-creative value propositions to ensure objective and reliable results. Experimental results demonstrate the superiority of the proposed approach in handling uncertainty, reliability, and subjectivity during the evaluation process.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2021)
Article
Green & Sustainable Science & Technology
Jung-Fa Tsai, Dinh-Hieu Tran, Phi-Hung Nguyen, Ming-Hua Lin
Summary: This study explores the barriers to the adoption of blockchain technology in the Vietnamese agricultural supply chain using a unique IVHF-DEMATEL approach. The findings highlight the lack of government regulation, scalability and system speed issues, resource and capital requirements, and lack of trust as the main barriers. The study also proposes a priority order for addressing these barriers to promote blockchain adoption in the Vietnamese agricultural supply chain.
Article
Computer Science, Artificial Intelligence
Xiaoyan Zhang, Jirong Li, Jusheng Mi
Summary: This article investigates the mechanisms of dynamic updating approximations caused by the variation of attributes in a multi-granulation interval-valued hesitant fuzzy information system (MG-IVHFIS) and proposes dynamic algorithms accordingly. Experimental results demonstrate that the dynamic method clearly outperforms the classical method when dealing with dynamic attribute sets.
KNOWLEDGE-BASED SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Quanyu Ding, Mark Goh, Ying-Ming Wang
Summary: This paper introduces a method to address dynamic emergency decision-making problems by using the interval evidential reasoning and interval-valued hesitant fuzzy TODIM method, combined with geometric area method and probability method to determine the ranking of decision alternatives. The effectiveness of the method is validated through a practical case study and comparative analysis.
Article
Computer Science, Interdisciplinary Applications
Wei Liang, Alvaro Labella, Ying-Ming Wang, Rosa M. Rodriguez
Summary: This paper introduces a consensus reaching process (CRP) that smooths disagreements between experts in a multi-criteria group decision-making problem to reach a solution of consensus. The experts' preferences are modeled using interval-valued hesitant fuzzy sets (IVHFS) to handle information scarcity and uncertainty. The proposal utilizes an extension of the ordered weight averaging operator under an IVHFS for reasonable aggregations. The CRP also includes a feedback mechanism to provide individual suggestions for increasing agreement within the group. The proposal is validated through a practical study on renewable energy selection in China under various scenarios.
COMPUTERS & INDUSTRIAL ENGINEERING
(2023)
Article
Green & Sustainable Science & Technology
Kenneth Nygaard, Stefan Schaper, Brian H. Jacobsen, Birgitte Hansen
Summary: This paper explores the formulation of value propositions connected to targeted nitrogen regulation in Danish agriculture. Through a comprehensive longitudinal ethnographic case study, it is found that the practical implementation of targeted regulation is not straightforward, and stakeholder-formulated value propositions can facilitate this process.
JOURNAL OF CLEANER PRODUCTION
(2022)
Article
Nuclear Science & Technology
Serhat Yuksel, Hasan Dincer
Summary: This study uses the hesitant 2-tuple interval-valued Pythagorean fuzzy DEMATEL method to evaluate nine different factors affecting nuclear energy projects in Turkey. The results suggest that factors related to security risk and technological infrastructure adequacy should be given the most consideration in nuclear energy investment decision-making. Turkey should focus on nuclear energy projects using thorium and invest in proton accelerator technology to minimize security risks in nuclear power plants.
PROGRESS IN NUCLEAR ENERGY
(2022)
Article
Mathematics
Tian Chen, Shiyao Li, Chun-Ming Yang, Wenting Deng
Summary: Global economic integration drives the development of dynamic competition. This study proposes a method for selecting enterprise diagnostic indicators based on interval-valued hesitant fuzzy clustering and constructs a rational and comprehensive enterprise diagnostic index system.
Article
Computer Science, Artificial Intelligence
Ozgur Yanmaz, Cigdem Kadaifci, Erhan Bozdag
Summary: Correspondence Analysis is a multivariate statistical technique used to visually represent the association between categorical variables. However, the classical approach does not demonstrate the uncertainty in real-life problems. Therefore, a new Interval-valued Hesitant Fuzzy CA approach is proposed to address this issue and represent the uncertainty caused by human doubt.
INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING
(2022)
Article
Computer Science, Interdisciplinary Applications
Wei Liang, Ying-Ming Wang
Summary: This paper proposes a new decision-making method using probabilistic interval-valued hesitant fuzzy sets to handle uncertain information. The interval evidential reasoning approach is used to deal with uncertainties in evaluations, while an interval projection measure is proposed to address the problem of information losses.
COMPUTERS & INDUSTRIAL ENGINEERING
(2021)
Article
Computer Science, Artificial Intelligence
Deeba R. Naqvi, Geeta Sachdev, Izhar Ahmad
Summary: Game theory has been widely used in various domains to handle competitive environments. However, most studies focus on matrix games that only consider numeric components. This work proposes a new approach that quantifies the payoffs in matrix games using qualitative variables. An aggregation operator supported by linguistic scale function and a score function are used to solve these games. The proposed approach is validated by applying it to electric vehicle sales.
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(2023)
Article
Mathematics
Yanru Zhong, Zhengshuai Lu, Yiyuan Li, Yuchu Qin, Meifa Huang
Summary: In this paper, an improved interval-valued hesitant fuzzy weighted geometric (IIVHFWG) operator is proposed for multi-criterion decision-making. This operator overcomes the limitations of existing operators, which are prone to being influenced by extreme values. A new method to solve multi-criterion decision-making problems with interval-valued hesitant fuzzy elements is presented based on the proposed IIVHFWG operator. Numerical examples and comparisons demonstrate the effectiveness and advantages of this method.
Article
Computer Science, Artificial Intelligence
Tongtong Zhou, Xinguo Ming, Ting Han, Yuguang Bao, Xiaoqiang Liao, Qingfei Tong, Shangwen Liu, Hao Guan, Zhihua Chen
Summary: Smart product service system (PSS) is crucial for manufacturing companies to transform towards digital servitization. The paper proposes a methodology to elicit and analyze diverse and inter-related smart experience-oriented customer requirements (SEO-CRs) in smart PSS context. A two-dimensional SEO-CR system and a HFLC-DEMATEL method are introduced to effectively evaluate the priority and interaction of SEO-CRs. The proposed method is validated through a real case of smart vehicle service system (SVSS).
ADVANCED ENGINEERING INFORMATICS
(2023)
Article
Computer Science, Artificial Intelligence
Seyed Meysam Mousavi
Summary: This paper proposes a novel group decision-making approach to evaluate IS-outsourcing candidates under IVHF-uncertainty, helping IS-DMs with decision-making. By converting preferences judgments of IS-experts into IVHF-elements, it reduces errors in the evaluation process.
NEURAL COMPUTING & APPLICATIONS
(2021)
Article
Computer Science, Artificial Intelligence
Qiuyan Zhan, Lesheng Jin, Ronald R. R. Yager, Radko Mesiar
Summary: This paper explores a novel approach to solve multi-attribute decision-making problems under the interval-valued hesitant fuzzy environment using the three-way decision theory. It defines the RLF under the IVHF environment and establishes the relationship between the loss function and the evaluation value. Additionally, it provides an aggregated loss function to reflect the overall loss of the alternative and establishes the mixed information table based on this function. Furthermore, it discusses the choice of line site in detail through a case study of a traffic expressway, considering factors such as project cost, traffic safety, and economic development.
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)