Article
Mathematics
Pere Josep Pons-Vives, Mateu Morro-Ribot, Carles Mulet-Forteza, Oscar Valero
Summary: This paper proposes an improved algorithm, OWA-based K-means, for clustering customers based on their spending propensity. Experiments show that the use of OWA operator improves the performance of classical K-means significantly. The OWA-based K-means can be applied to classify customers in different seasons without requiring radical changes in the implementation of the classical method or additional implementation costs in real hotel management.
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, Artificial Intelligence
Emile van Krieken, Erman Acar, Frank van Harmelen
Summary: The AI community is increasingly focusing on combining symbolic and neural approaches, with a recent trend towards weakly supervised learning techniques using fuzzy logic operators. The study finds that many logical operators from fuzzy logic literature are unsuitable in differentiable learning settings and introduces a new family of fuzzy implications to address this issue. Empirical results show the possibility of using Differentiable Fuzzy Logics for semi-supervised learning and the need for non-standard combinations of logical operators to achieve performance improvement.
ARTIFICIAL INTELLIGENCE
(2022)
Article
Computer Science, Artificial Intelligence
Antonio J. Rueda, Carmen Martinez-Cruz, Angeles Diaz-Fernandez, Maria Catalina Osuna-Perez
Summary: Computers are widely used for training and simulating hazardous tasks or tasks that require expensive or difficult to access equipment. In this study, we present a system for evaluating clinical practices involving electrotherapy. The system, implemented as a serious game, provides supervised clinical practice since opportunities for using real equipment are limited. The system mimics expert assessment of electrotherapy treatments and computes an overall treatment score based on various aspects such as electrical parameters and electrode placement.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Mathematics
Luciano Barcellos-Paula, Anna Maria Gil-Lafuente, Aline Castro-Rezende
Summary: Scientific studies confirm the crisis caused by climate change, with global causes leading to local effects. Despite climate agreements, greenhouse gas emissions are still not meeting the targets to limit global warming. Comparable data for Sustainable Development Goal 13-Climate Action is still needed. The research aims to provide data for decision-making and propose solutions to address the climate crisis.
Article
Automation & Control Systems
Chengju Gong, Liwen Jiang, Li Hou
Summary: This paper explores the key role of aggregating fuzzy information in dealing with uncertainties, and proposes distance-induced fuzzy operators to solve the problem of inability to directly aggregate distance values in the aggregation process. By analyzing the concepts, properties, and generalized forms of these operators, frameworks for multi-criteria group decision-making situations are constructed, with an example illustrating the detailed application process of these frameworks.
INTERNATIONAL JOURNAL OF FUZZY SYSTEMS
(2022)
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
Business
Luciano Barcellos-Paula, Carlos Aguero Olivos
Summary: This research contributes to the field of corporate governance by using a quantitative approach to assess the corporate governance level of 28 enterprises listed on the Lima Stock Exchange. The study proposes actions to strengthen governance and reduces knowledge gaps.
CORPORATE SOCIAL RESPONSIBILITY AND ENVIRONMENTAL MANAGEMENT
(2022)
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
Computer Science, Artificial Intelligence
Wen-Huang Li, Feng Qin
Summary: This article partially solves an open problem related to the law of importation, focusing on the general form of the law with specific characteristics. By analyzing a fixed operator, the fuzzy implications that satisfy the law of importation and have specific properties are identified.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2022)
Article
Biodiversity Conservation
Bowen Huang, Ruibo Zha, Shifa Chen, Xuan Zha, Xingxue Jiang
Summary: Evaluation of ecological vulnerability is important for ecological protection and management. A comprehensive evaluation system and analysis method were developed, using Fujian Province, China as a case study. The results were validated and provide guidance for ecological protection and sustainable development.
ECOLOGICAL INDICATORS
(2023)
Article
Computer Science, Artificial Intelligence
Yaser Donyatalab, Fatma Kutlu Gundog, Fariba Farid, Seyed Amin Seyfi-Shishavan, Elmira Farrokhizadeh, Cengiz Kahraman
Summary: Spherical fuzzy sets have gained popularity in various fields as a generalization of picture fuzzy sets and Pythagorean fuzzy sets. This study proposes novel distances and similarity measures for spherical fuzzy sets and applies them to medical diagnosis for COVID-19. The newly defined similarity measures provide advantages and contribute to the understanding of similarity between objects.
EXPERT SYSTEMS WITH APPLICATIONS
(2022)
Article
Mathematics, Applied
Kaiyan Yang, Lan Shu, Guowu Yang
Summary: Compared with CFS and IFS, CIFS can handle two-dimensional and uncertain information simultaneously, and its importance in capturing useful information is considered. The CIFOWD measure provides a parameterized family of aggregation distance measures, including special types like CIFOWGD, CIFOWHD, and CIFOWED. A multiple criteria group decision-making approach is presented under CIFSs environment, and its effectiveness is demonstrated through an illustrative example of coronavirus vaccine selection.
COMPUTATIONAL & APPLIED MATHEMATICS
(2022)
Article
Green & Sustainable Science & Technology
Betzabe Ruiz-Morales, Irma Cristina Espitia-Moreno, Victor G. Alfaro-Garcia, Ernesto Leon-Castro
Summary: This study proposes a new method using OWA operators to analyze the SDGs index. By evaluating the relative importance of each SDG and using OWA and POWA operators, rankings were generated, showing that country rankings can change depending on the weights of each SDG.
Article
Computer Science, Artificial Intelligence
Paul Augustine Ejegwa, Yuming Feng, Shuyu Tang, Johnson Mobolaji Agbetayo, Xiangguang Dai
Summary: Pythagorean fuzzy set is a broader concept with higher application prospects compared to IFS. This paper proposes a new distance measure method under Pythagorean fuzzy environment, which outperforms existing measures in terms of performance indexes. The proposed method takes into account the three parameters of PFSs and avoids error due to exclusion. The applications in pattern classification and disease diagnosis demonstrate the superiority of the proposed Pythagorean fuzzy distance measures.
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Computer Science, Information Systems
Walayat Hussain, J. M. Merigo, M. R. Raza, Honghao Gao
Summary: The study proposes a novel fuzzy time series prediction model, the CI-ANFIS model, which reduces data dimension, handles the nonlinear relationship of cloud QoS dataset, and outperforms all current techniques in terms of prediction accuracy.
INFORMATION SCIENCES
(2022)
Article
Computer Science, Artificial Intelligence
Walayat Hussain, Jose M. Merigo, Muhammad Raheel Raza
Summary: This paper introduces a new forecasting method that combines fuzzy time series and neural network structure to efficiently handle complex nonlinear relationships and large datasets. By introducing the IOWA operator and weighted average, the method is able to adapt to fuzzy nonlinear prediction in specific problems.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2022)
Review
Economics
Shashi, Piera Centobelli, Roberto Cerchione, Jose M. Merigo
Summary: This paper presents a comprehensive bibliometric and network analysis on knowledge management (KM) to understand its development from the perspective of academic communities. The study evaluates 8,721 KM papers published in the last 30 years and uses co-citation analysis to identify associations between themes and predict emerging trends. The findings provide valuable insights for researchers and academicians in specific sub-fields.
TECHNOLOGICAL AND ECONOMIC DEVELOPMENT OF ECONOMY
(2022)
Article
Computer Science, Cybernetics
Miriam Edith Perez-Romero, Victor G. Alfaro-Garcia, Jose M. Merigo, Martha Beatriz Flores-Romero
Summary: The objective of this study is to introduce the covariance ordered weighted logarithmic averaging (Cov-OWLA) operators for decision-making processes in uncertain environments. An illustrative example using real-world data shows a positive linear relation between the introduced variables. The aggregation using Cov-OWLA operators demonstrates a better fit compared to traditional methods.
CYBERNETICS AND SYSTEMS
(2023)
Article
Business
Leslier Valenzuela-Fernandez, Ignacio Munoz Quezada, Jose M. Merigo
Summary: This research presents a bibliometric analysis of advertising trends in the business area and provides valuable information for future research. The study shows a growing trend in the number of advertising publications and identifies the most cited and influential journals in the field, such as the Journal of Advertising and the Journal of Advertising Research.
JOURNAL OF GLOBAL SCHOLARS OF MARKETING SCIENCE
(2023)
Article
Computer Science, Artificial Intelligence
Walayat Hussain, Muhammad Raheel Raza, Mian Ahmad Jan, Jose M. Merigo, Honghao Gao
Summary: This article proposes an SLA violation risk mitigation model that uses OWA and LSTM for complex QoS prediction. The approach considers all possible attitudinal behavior of the service provider and provides intelligent recommendations for mitigating actions.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2022)
Article
Computer Science, Interdisciplinary Applications
Gustavo Zurita, Carles Mulet-Forteza, Jose Merigo, Valeria Lobos-Ossandon, Hiroaki Ogata
Summary: This article provides a lifetime overview of IEEE Transactions on Learning Technologies through bibliometric analysis and science mapping. The results show that this journal is highly influential in the fields of computer science and education, with wide-ranging citations from authors, institutions, and countries across the world.
IEEE TRANSACTIONS ON LEARNING TECHNOLOGIES
(2022)
Correction
Business
Alicia Mas-Tur, Norat Roig-Tierno, Shikhar Sarin, Christophe Haon, Trina Sego, Mustapha Belkhouja, Alan Porter, Jose M. Merigo
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
(2023)
Article
Business, Finance
Emili Vizuete-Luciano, Oktay Guzel, Jose M. Merigo
Summary: This study utilizes bibliometric analyses to examine the research field of Pay-What-You-Want (PWYW) pricing strategy. The analysis identifies influential cited works and authors, and reveals the intellectual and thematic structure of the field. Based on the findings, future research paths are suggested.
JOURNAL OF REVENUE AND PRICING MANAGEMENT
(2023)
Article
Computer Science, Artificial Intelligence
Walayaty Hussain, Jose M. Merigo, Jaime Gil-Lafuente, Honghao Gao
Summary: Neural network methods are widely used in business for prediction, clustering, and risk management. This paper proposes a neural network sorting mechanism to handle complex nonlinear relationships in datasets, reducing computational complexities. The research opens up a new area for complex nonlinear predictions with large datasets.
Article
Computer Science, Information Systems
Walayat Hussain, Jose M. Merigo, Honghao Gao, Asma Musabah Alkalbani, Fethi A. Rabhi
Summary: Due to the lack of a common framework, the selection of cloud providers and allocation of marginal resources have become complicated. Existing frameworks have ignored the complex nonlinear relationships between service evaluation criteria, leading to ineffective decision-making systems. This paper proposes a centralized framework that considers consumer's customized priority criteria, determines relative importance, and intelligently assigns weights to each criterion. The framework enables optimal service provider selection and wise resource management, fostering sustainable and trusted relationships.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2023)
Article
Management
Christian A. Cancino, Jose M. Merigo, David Urbano, J. Ernesto Amoros
Summary: This study analyzes the journals and universities that published research on entrepreneurship and innovation by Ibero-American authors between 1986 and 2015. The results show that the most outstanding researchers in the region are mainly from Spain and Portugal. Spanish researchers, in particular, are the most productive and influential authors in the region. A small group of researchers from Chile, Argentina, and Mexico are also highly influential. Latin American researchers need to deepen their international academic networks.
JOURNAL OF SMALL BUSINESS MANAGEMENT
(2023)
Proceedings Paper
Business, Finance
Veronica Pizarro, Jose M. Merigo, Leslier Valenzuela, Sebastian Aciares
Summary: The purpose of this study is to investigate and present the evolution of academic research and publications on corporate social responsibility (CSR) between 1990 and 2014. Results show a strong increase in research and study of CSR in recent years.
COMPUTATIONAL AND DECISION METHODS IN ECONOMICS AND BUSINESS
(2022)
Proceedings Paper
Business, Finance
Agustin Torres Martinez, Anna Maria Gil-Lafuente, Aras Keropyan, Jose M. MerigoLindahl
Summary: This paper explores the challenges of Basel II's second agreement for financial institutions, risk managers, and researchers in terms of operational risk management, as well as how to use the forgotten effects theory to determine causal relationships between the causes and effects of operational losses.
COMPUTATIONAL AND DECISION METHODS IN ECONOMICS AND BUSINESS
(2022)
Review
Business, Finance
Martha Flores-Sosa, Ezequiel Aviles-Ochoa, Jose M. Merigo
Summary: This article proposes a bibliometric analysis of exchange rate volatility (ERV) and compares it with two databases, Web of Science and Scopus. The analysis demonstrates the importance of ERV in scientific research and identifies influential authors, institutions, and countries studying currency volatility. The study also reveals an increasing attention to this topic over time.
INTERNATIONAL JOURNAL OF FINANCE & ECONOMICS
(2022)
