Article
Computer Science, Artificial Intelligence
Vikas Srivastava, Amar Kishor, Amit K. Singh
Summary: In this paper, a novel representative of the existing family of ordered weighted aggregation (OWA) operators with constant orness is presented. The proposed OWA operator is based on the beta function and has two different types of operators with respect to optimism and pessimism. It provides flexibility for decision making and comparisons with other OWA operators are discussed. The properties and applications of the proposed operators are also analyzed in detail.
INTERNATIONAL JOURNAL OF APPROXIMATE REASONING
(2023)
Article
Computer Science, Artificial Intelligence
Raul Perez-Fernandez, Gustavo Ochoa, Susana Montes, Irene Diaz, Javier Fernandez, Daniel Paternain, Humberto Bustince
Summary: The notion of orness measure for aggregation functions has a history dating back to the early 1970s and has since evolved to include axiomatic definitions for various types of aggregation functions, with proposed construction methods and detailed studies on specific examples like the discrete Choquet integral and uninorms.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2021)
Article
Computer Science, Theory & Methods
Vicenc Torra
Summary: This paper discusses the concept of andness directed aggregation, presents aggregation functions from the OWA and WOWA families, and explores how to select appropriate parameters based on families of fuzzy quantifiers.
FUZZY SETS AND SYSTEMS
(2021)
Article
Chemistry, Multidisciplinary
Iris Dominguez-Catena, Daniel Paternain, Mikel Galar
Summary: In this study, OWA operators are integrated into Convolutional Neural Networks through the OWA layer for image classification, enabling the CNN to leverage global information about the image in the early stages of processing. The OWA layer also serves as a practical method for determining OWA operator weights, which can be challenging in other fields. The weights learned for OWA operators within the OWA layer are characterized based on their orness and dispersion, with comparisons made to other families of OWA operators to highlight unique examples that cannot be generalized through current parameterizations.
APPLIED SCIENCES-BASEL
(2021)
Article
Computer Science, Artificial Intelligence
Victor G. Alfaro-Garcia, Jose M. Merigo, Anna M. Gil-Lafuente, Rodrigo Gomez Monge
Summary: This paper introduces a new weighted aggregation operator, IGOWLA, which takes into account the complex attitudes of decision makers and has strong practicality. In addition to presenting the general form of the operator and some special cases, an example of group decision-making using the IGOWLA operator in the field of innovation management is analyzed.
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
(2021)
Article
Mathematics
Emili Vizuete-Luciano, Sefa Boria-Reverter, Jose M. Merigo-Lindahl, Anna Maria Gil-Lafuente, Maria Luisa Sole-Moro
Summary: This paper introduces a new assignment algorithm using the OWA operator and its extensions in the Branch-and-bound algorithm, providing more detailed information. The algorithm is applied in a consumer decision-making model in Barcelona, aiding in selecting grocery districts that best suit their needs, while considering different sources of information independently.
Article
Mathematics
Rodrigo Gomez Monge, Evaristo Galeana Figueroa, Victor G. Alfaro-Garcia, Jose M. Merigo, Ronald R. Yager
Summary: This paper introduces variance logarithmic averaging operators and analyzes their properties, families, and particular cases, providing an illustrative example from financial markets to showcase the design of these operators. Results show that the use of variance measures aids decision-making by offering new tools for information analysis and extends the available tools for decision-making under ignorance, uncertainty, and subjective environments.
Article
Computer Science, Theory & Methods
Oihana Aristondo, Ainhoa Iniguez
Summary: This note discusses the distribution-sensitivity of two families of rank-dependent poverty measures and introduces an orness value to measure distribution-sensitivity. It expands the classification of these families to cover all real parameters and provides a ranking between them. The findings show that for higher parameter values, the families are more sensitive to the bottom part of the distribution, and the Kakwani index is more sensitive to poor incomes than the S-Gini index. The proposed ranking based on the orness value is analogous to other distribution-sensitivity criteria in the literature.
FUZZY SETS AND SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
ShaoLin Zhang, Xia Li, FanYong Meng
Summary: This paper proposes a group decision making method based on intuitionistic triangular fuzzy information, including new ranking method, aggregation operator, and distance measure. The optimal measure results can be obtained by constructing programming models. The example demonstrates the applicability of the proposed method.
APPLIED INTELLIGENCE
(2023)
Article
Computer Science, Artificial Intelligence
Wan Syahimi Afiq Wan Ahlim, Nor Hanimah Kamis, Sharifah Aniza Sayed Ahmad, Francisco Chiclana
Summary: Trust relation and similarity are integrated in constructing a similarity-trust network for consensus group decision-making. Experts are grouped using hierarchical clustering, and their similarity-trust centrality index is determined using centrality concept for deriving a consensus solution. The study shows promising results with potential application in certain consensus group decision-making problems.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Dejian Yu, Tianxing Pan, Zeshui Xu, Ronald R. R. Yager
Summary: In recent years, the OWA operator has received increasing attention in the academic community. Growth curve analysis, commonly used in ecosystem studies, suggests that this trend will continue. However, previous literature has not provided a comprehensive overview of the field's development and evolution. This study employed classic main path analysis and its variations on a citation network of 1474 papers to uncover the development trajectories and research topics of OWA. The findings reveal the pervasive presence of weight generation and operator generalization in the OWA domain, the dynamic and multi-period nature of the multiple criteria decision-making process, and the incorporation of theories like social network theory and expanded applications of the OWA operator.
ARTIFICIAL INTELLIGENCE REVIEW
(2023)
Article
Computer Science, Artificial Intelligence
Jose Carlos R. Alcantud, Gustavo Santos-Garcia, Muhammad Akram
Summary: This work improves the theoretical basis of N-soft sets and demonstrates their practical applications in a multiagent context. It presents a novel theory of aggregation of N-soft sets using OWA operators and applies it to multi-agent decision-making, resulting in the first algorithms for such decisions based on N-soft sets.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Computer Science, Artificial Intelligence
Ruonan Zhang, Jing Huang, Yejun Xu, Enrique Herrera-Viedma
Summary: Consensus costs are crucial in group decision making to reach an acceptable consensus. This study examines the use of quadratic cost functions and aggregation operators to analyze minimum cost consensus models. The research provides desirable properties and demonstrates the validity of the proposed models through examples and comparative analysis.
APPLIED INTELLIGENCE
(2023)
Article
Computer Science, Artificial Intelligence
Vikas Srivastava, Amit K. Singh
Summary: This article proposes a new biparametric OWA operator called beta-Bezier OWA operator, which provides an infinite number of weight vectors. The orness value of this operator is its most essential characteristic and can be predetermined based on the decision-maker's choice.
INTERNATIONAL JOURNAL OF APPROXIMATE REASONING
(2023)
Article
Computer Science, Information Systems
Kamal Kumar, Shyi-Ming Chen
Summary: In this paper, we propose the advanced intuitionistic fuzzy Heronian mean (AIFHM) aggregation operator and the advanced intuitionistic fuzzy weighted Heronian mean (AIFWHM) aggregation operator, which consider the interrelationships among aggregating inputs. We also propose a new group decision making (GDM) method based on the AIFWHM operator and show its advantages over existing methods.
INFORMATION SCIENCES
(2022)
Article
Computer Science, Artificial Intelligence
Jinpei Liu, Yun Zheng, Feifei Jin, Huayou Chen
Summary: This paper proposes a novel decision-making method that can handle complex decision information, especially applied to fog-haze weather issues. By introducing consistency adjustment strategy and data envelopment analysis, a fuzzy priority weight vector that effectively ranks alternatives is developed, demonstrating the effectiveness of the proposed method.
APPLIED INTELLIGENCE
(2022)
Article
Computer Science, Artificial Intelligence
Zicheng Wang, Huayou Chen, Jiaming Zhu, Zhenni Ding
Summary: A novel multi-scale hybrid learning framework based on RLMD and MW ensemble strategy is developed for PM2.5 and PM10 forecasting, which outperforms other methods in terms of forecasting accuracy and generalization ability, demonstrating great application value in the field of PMCTS prediction.
APPLIED SOFT COMPUTING
(2022)
Article
Computer Science, Artificial Intelligence
Chengli Zheng, Yuanyuan Zhou, Ligang Zhou, Huayou Chen
Summary: This paper focuses on the clustering and consensus reaching of hesitant fuzzy linguistic preference relations (HFLPRs) in large-scale group decision making (LSGDM). A new similarity measure and compatibility measure are proposed, and a clustering process combining these measures is used to assign experts into clusters. A compatibility adjusting process with self-selected feedback mechanism is presented to improve the compatibility level of clusters. The weights of subgroups are determined based on the number of members and the compatibility level. The proposed method is validated through a case study on e-waste recycling.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Management
Peng Wu, Jinpei Liu, Ligang Zhou, Huayou Chen
Summary: This paper proposes a new method for evaluating the resilience of cities, integrating data envelopment analysis (DEA) and a distance-based priority aggregation (DPA) model to avoid the loss of decision-making information. By introducing DEA and DPA models, the method aims to find the priority vector that minimizes the distance among evaluation factors.
GROUP DECISION AND NEGOTIATION
(2022)
Article
Computer Science, Artificial Intelligence
Zicheng Wang, Hao Li, Huayou Chen, Zhenni Ding, Jiaming Zhu
Summary: In order to forecast the fluctuation and uncertainty of PM2.5 concentrations, this paper proposes a new hybrid modeling framework that combines the elastic net and multivariate relevance vector machine. The model considers the linear relationship between PM2.5 and its related factors and models the nonlinear patterns at multiple scales.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Computer Science, Cybernetics
Shahid Hussain Gurmani, Huayou Chen, Yuhang Bai
Summary: This article presents the concept of a T-spherical hesitant fuzzy set associated with probability and develops an extended multi-attributive border approximation area comparison (MABAC) method under probabilistic T-spherical hesitant fuzzy (Pt-SHF) settings. The proposed method can overcome the drawbacks and limitations of conventional MABAC methods in group decision making scenarios. By establishing the notion of probabilistic t-spherical hesitant fuzzy set, this work fills a gap in literature in dealing with ambiguity and uncertainty in decision making problems.
Article
Computer Science, Artificial Intelligence
Yuanyuan Zhou, Chengli Zheng, Ligang Zhou, Huayou Chen
Summary: This paper presents a best-worst large-scale group decision making approach based on hesitant fuzzy linguistic preference relations (HFLPRs) for the selection of solar water heaters. The method includes an optimization model for normalizing hesitant fuzzy linguistic term sets (HFLTSs), a satisfaction degree function based on additive consistency, and a clustering process to classify experts into subgroups. The weights of the subgroups are determined using a best-worst model based on credibility measure. The proposed method is demonstrated through a numerical example.
APPLIED INTELLIGENCE
(2023)
Article
Computer Science, Artificial Intelligence
Liyuan Jiang, Zhifu Tao, Jiaming Zhu, Junting Zhang, Huayou Chen
Summary: This paper proposes a hybrid interval-valued time series prediction model that accurately predicts high concentrations of PM2.5, and improves the prediction accuracy by addressing the edge effects and transformation issues.
APPLIED INTELLIGENCE
(2023)
Article
Computer Science, Artificial Intelligence
Shahid Hussain Gurmani, Huayou Chen, Yuhang Bai
Summary: This paper proposes a multi-attribute group decision-making (MAGDM) model for selecting the most suitable construction company. By introducing the notion of a linguistic interval-valued T-spherical fuzzy set, the model is able to handle vague information and uncertainty more effectively. Computational results demonstrate that the model is capable of handling complex decision-making situations.
APPLIED INTELLIGENCE
(2023)
Article
Economics
Zhenni Ding, Huayou Chen, Ligang Zhou
Summary: This paper proposes an algorithm based on the Shapley value method to select a superior subset from a group of multiple individual forecasts. The algorithm evaluates the contribution of each forecast in the combination by calculating its Shapley value, and determines the order of forecasts entering the screening process based on these values until all redundant forecasts are removed. The effectiveness, superiority, and robustness of the algorithm are verified through empirical studies.
JOURNAL OF FORECASTING
(2023)
Article
Automation & Control Systems
Jingmiao Song, Peng Wu, Jinpei Liu, Huayou Chen
Summary: The aim of this study is to propose a new approach to group decision making (GDM) using multi-plicative DEA cross-efficiency and stochastic acceptability analysis with hesitant fuzzy linguistic preference relations (HFLPRs), which can ensure credible decision-making results by avoiding information distortion. The proposed method involves defining a transform function to extract effective information from the hesitant fuzzy linguistic term set (HFLTS), deriving occurring probabilities of HFLTS elements using an optimization model, evaluating the relative efficiency of alternatives using the Maximum Log DEA Cross Efficiency model, and solving the GDM problem using the stochastic weight space acceptability analysis method. Numerical examples are provided to demonstrate the validity and applicability of the proposed method, which is the first attempt to apply multiplicative DEA cross-efficiency to GDM with HFLPRs.
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
(2023)
Article
Computer Science, Artificial Intelligence
Zhenni Ding, Huayou Chen, Ligang Zhou, Zicheng Wang
Summary: This study proposes a novel combined model that integrates different forecasting methods to improve the accuracy of air quality prediction. It also provides interval forecasts using the quantile regression method to reflect more uncertain information.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Economics
Piao Wang, Zhifu Tao, Jinpei Liu, Huayou Chen
Summary: This paper proposes an interval-valued carbon price forecasting method based on new data processing techniques, and discusses the effects of different combinations of interval variables on the forecasting results. The results show that the developed framework surpasses other comparison models in terms of forecasting precision and stability.
Article
Business
Zicheng Wang, Ruobin Gao, Piao Wang, Huayou Chen
Summary: Accurate forecasting of the AQI is crucial for preventing air pollution risks. Existing approaches often lose valuable information on air quality status. This paper proposes a new paradigm that combines TITS, MVMD, MVRVM, MCPSO, and meteorological factors to capture AQI trend and volatility changes. Experimental results demonstrate that the proposed paradigm outperforms other models and has potential for application in AQI forecasting systems.
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
(2023)
Article
Automation & Control Systems
Xi Liu, Zhifu Tao, Huayou Chen, Ligang Zhou
Summary: This thesis introduces the probabilistic linguistic term ordered weighted distance (PLTOWD) operator, enhancing the distance theory in the context of probabilistic linguistic terms. It also proposes a method of multiple attribute group decision making (MAGDM) based on the PLTOWD operator.
JOURNAL OF CONTROL AND DECISION
(2022)
Article
Engineering, Multidisciplinary
A. A. Aganin, A. I. Davletshin
Summary: A mathematical model of interaction of weakly non-spherical gas bubbles in liquid is proposed in this paper. The model equations are more accurate and compact compared to existing analogs. Five problems are considered for validation, and the results show good agreement with experimental data and numerical solutions. The model is also used to analyze the behavior of bubbles in different clusters, providing meaningful insights.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
Hao Wu, Jie Sun, Wen Peng, Lei Jin, Dianhua Zhang
Summary: This study establishes an analytical model for the coupling of temperature, deformation, and residual stress to explore the mechanism of residual stress formation in hot-rolled strip and how to control it. The accuracy of the model is verified by comparing it with a finite element model, and a method to calculate the critical exit crown ratio to maintain strip flatness is proposed.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
Shengwen Tu, Naoki Morita, Tsutomu Fukui, Kazuki Shibanuma
Summary: This study aimed to extend the finite element method to cope with elastic-plastic problems by introducing the s-version FEM. The s-version FEM, which overlays a set of local mesh with fine element size on the conventional FE mesh, simplifies domain discretisation and provides accurate numerical predictions. Previous applications of the s-version FEM were limited to elastic problems, lacking instructions for stress update in plasticity. This study presents detailed instructions and formulations for addressing plasticity problems with the s-version FEM and analyzes a stress concentration problem with linear/nonlinear material properties.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
Bo Fan, Zhongmin Wang
Summary: A 3D rotating hyperelastic composite REF model was proposed to analyze the influence of tread structure and rotating angular speed on the vibration characteristics of radial tire. Nonlinear dynamic differential equations and modal equations were established to study the effects of internal pressure, tread pressure sharing ratio, belt structure, and rotating angular speed on the vibration characteristics.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
X. W. Chen, Z. Q. Yue, Wendal Victor Yue
Summary: This paper examines the axisymmetric problem of a flat mixed-mode annular crack near and parallel to an arbitrarily graded interface in functionally graded materials (FGMs). The crack is modeled as plane circular dislocation loop and an efficient solution for dislocation in FGMs is used to calculate the stress field at the crack plane. The analytical solutions of the stress intensity factors are obtained and numerical study is conducted to investigate the fracture mechanics of annular crack in FGMs.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
Xumin Guo, Jianfei Gu, Hui Li, Kaihua Sun, Xin Wang, Bingjie Zhang, Rangwei Zhang, Dongwu Gao, Junzhe Lin, Bo Wang, Zhong Luo, Wei Sun, Hui Ma
Summary: In this study, a novel approach combining the transfer matrix method and lumped parameter method is proposed to analyze the vibration response of aero-engine pipelines under base harmonic and random excitations. The characteristics of the pipelines are investigated through simulation and experiments, validating the effectiveness of the proposed method.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
Xiangyu Sha, Aizhong Lu, Ning Zhang
Summary: This paper investigates the stress and displacement of a layered soil with a fractional-order viscoelastic model under time-varying loads. The correctness of the solutions is validated using numerical methods and comparison with existing literature. The research findings are of significant importance for exploring soil behavior and its engineering applications under time-varying loads.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
Thuy Dong Dang, Thi Kieu My Do, Minh Duc Vu, Ngoc Ly Le, Tho Hung Vu, Hoai Nam Vu
Summary: This paper investigates the nonlinear torsional buckling of corrugated core sandwich toroidal shell segments with functionally graded graphene-reinforced composite (FG-GRC) laminated coatings in temperature change using the Ritz energy method. The results show the significant beneficial effects of FG-GRC laminated coatings and corrugated core on the nonlinear buckling responses of structures.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
Zhihao Zhai, Chengbiao Cai, Qinglai Zhang, Shengyang Zhu
Summary: This paper investigates the effect of localized cracks induced by environmental factors on the dynamic performance and service life of ballastless track in high-speed railways. A mathematical approach for forced vibrations of Mindlin plates with a side crack is derived and implemented into a train-track coupled dynamic system. The accuracy of this approach is verified by comparing with simulation and experimental results, and the dynamic behavior of the side crack under different conditions is analyzed.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
James Vidler, Andrei Kotousov, Ching-Tai Ng
Summary: The far-field methodology, developed by J.C. Maxwell, is utilized to estimate the effective third order elastic constants of composite media containing random distribution of spherical particles. The results agree with previous studies and can be applied to homogenization problems in other fields.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
Kim Q. Tran, Tien-Dat Hoang, Jaehong Lee, H. Nguyen-Xuan
Summary: This study presents novel frameworks for graphene platelets reinforced functionally graded triply periodic minimal surface (GPLR-FG-TPMS) plates and investigates their performance through static and free vibration analyses. The results show that the mass density framework has potential for comparing different porous cores and provides a low weight and high stiffness-to-weight ratio. Primitive plates exhibit superior performance among thick plates.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
Bence Hauck, Andras Szekrenyes
Summary: This study explores several methods for computing the J-integral in laminated composite plate structures with delamination. It introduces two special types of plate finite elements and a numerical algorithm. The study presents compact formulations for calculating the J-integral and applies matrix multiplication to take advantage of plate transition elements. The models and algorithms are applied to case studies and compared with analytical and previously used finite element solutions.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
Wu Ce Xing, Jiaxing Wang, Yan Qing Wang
Summary: This paper proposes an effective mathematical model for bolted flange joints to study their vibration characteristics. By modeling the flange and bolted joints, governing equations are derived. Experimental studies confirm that the model can accurately predict the vibration characteristics of multiple-plate structures.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
Pingchao Yu, Li Hou, Ke Jiang, Zihan Jiang, Xuanjun Tao
Summary: This paper investigates the imbalance problem in rotating machinery and finds that mass imbalance can induce lateral-torsional coupling vibration. By developing a model and conducting detailed analysis, it is discovered that mass imbalance leads to nonlinear time-varying characteristics and there is no steady-state torsional vibration in small unbalanced rotors. Under largely unbalanced conditions, both resonant and unstable behavior can be observed, and increasing lateral damping can suppress instability and reduce lateral amplitude in the resonance region.
APPLIED MATHEMATICAL MODELLING
(2024)
Article
Engineering, Multidisciplinary
Yong Cao, Ziwen Guo, Yilin Qu
Summary: This paper investigates the mechanically induced electric potential and charge redistribution in a piezoelectric semiconductor cylindrical shell. The results show that doping levels can affect the electric potentials and mechanical displacements, and alter the peak position of the zeroth-order electric potential. The doping level also has an inhibiting effect on the first natural frequency. These findings are crucial for optimizing the design and performance of cylindrical shell-shaped sensors and energy harvesters.
APPLIED MATHEMATICAL MODELLING
(2024)
