876 research outputs found

    Investigation on soft computing techniques for airport environment evaluation systems

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    Spatial and temporal information exist widely in engineering fields, especially in airport environmental management systems. Airport environment is influenced by many different factors and uncertainty is a significant part of the system. Decision support considering this kind of spatial and temporal information and uncertainty is crucial for airport environment related engineering planning and operation. Geographical information systems and computer aided design are two powerful tools in supporting spatial and temporal information systems. However, the present geographical information systems and computer aided design software are still too general in considering the special features in airport environment, especially for uncertainty. In this thesis, a series of parameters and methods for neural network-based knowledge discovery and training improvement are put forward, such as the relative strength of effect, dynamic state space search strategy and compound architecture. [Continues.

    Fuzzy Logic in Decision Support: Methods, Applications and Future Trends

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    During the last decades, the art and science of fuzzy logic have witnessed significant developments and have found applications in many active areas, such as pattern recognition, classification, control systems, etc. A lot of research has demonstrated the ability of fuzzy logic in dealing with vague and uncertain linguistic information. For the purpose of representing human perception, fuzzy logic has been employed as an effective tool in intelligent decision making. Due to the emergence of various studies on fuzzy logic-based decision-making methods, it is necessary to make a comprehensive overview of published papers in this field and their applications. This paper covers a wide range of both theoretical and practical applications of fuzzy logic in decision making. It has been grouped into five parts: to explain the role of fuzzy logic in decision making, we first present some basic ideas underlying different types of fuzzy logic and the structure of the fuzzy logic system. Then, we make a review of evaluation methods, prediction methods, decision support algorithms, group decision-making methods based on fuzzy logic. Applications of these methods are further reviewed. Finally, some challenges and future trends are given from different perspectives. This paper illustrates that the combination of fuzzy logic and decision making method has an extensive research prospect. It can help researchers to identify the frontiers of fuzzy logic in the field of decision making

    The evaluation performance for commercial banks by intuitionistic fuzzy numbers: the case of Spain

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    In a globalized world, the banking sector has been forced to advance not only in financial performance, but also in non-financial performance, especially in sustainability criteria. For this purpose, multicriteria decision methods are especially suited to evaluate efficiency and to make a stable ranking of the most outstanding banks in the Spanish financial system. However, we are aware of the difficulties involved due to the inherent uncertainty and subjectivity of this process. For this reason, the use of fuzzy models is proposed, especially intuitionistic fuzzy numbers combined with the Analytic Hierarchy Process and the TOPSIS. The combination of financial criteria based on the CAMELS rating system with non-financial sustainability criteria makes it possible to order the Spanish banking system based on global efficiency. The most relevant contributions are: first, the use of intuitionistic fuzzy numbers in the performance evaluation process, whereby the quality of the information available can be quantified; and the most important one, a simplification of the process in the implementation of the intuitionistic fuzzy TOPSIS. Finally, through a sensibility analysis, it is possible to isolate the relevance of the sustainability process to obtain the global performance evaluation

    Detecting and predicting the topic change of Knowledge-based Systems: A topic-based bibliometric analysis from 1991 to 2016

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    © 2017 The journal Knowledge-based Systems (KnoSys) has been published for over 25 years, during which time its main foci have been extended to a broad range of studies in computer science and artificial intelligence. Answering the questions: “What is the KnoSys community interested in?” and “How does such interest change over time?” are important to both the editorial board and audience of KnoSys. This paper conducts a topic-based bibliometric study to detect and predict the topic changes of KnoSys from 1991 to 2016. A Latent Dirichlet Allocation model is used to profile the hotspots of KnoSys and predict possible future trends from a probabilistic perspective. A model of scientific evolutionary pathways applies a learning-based process to detect the topic changes of KnoSys in sequential time slices. Six main research areas of KnoSys are identified, i.e., expert systems, machine learning, data mining, decision making, optimization, and fuzzy, and the results also indicate that the interest of KnoSys communities in the area of computational intelligence is raised, and the ability to construct practical systems through knowledge use and accurate prediction models is highly emphasized. Such empirical insights can be used as a guide for KnoSys submissions

    Fuzzy Sets, Fuzzy Logic and Their Applications

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    The present book contains 20 articles collected from amongst the 53 total submitted manuscripts for the Special Issue “Fuzzy Sets, Fuzzy Loigic and Their Applications” of the MDPI journal Mathematics. The articles, which appear in the book in the series in which they were accepted, published in Volumes 7 (2019) and 8 (2020) of the journal, cover a wide range of topics connected to the theory and applications of fuzzy systems and their extensions and generalizations. This range includes, among others, management of the uncertainty in a fuzzy environment; fuzzy assessment methods of human-machine performance; fuzzy graphs; fuzzy topological and convergence spaces; bipolar fuzzy relations; type-2 fuzzy; and intuitionistic, interval-valued, complex, picture, and Pythagorean fuzzy sets, soft sets and algebras, etc. The applications presented are oriented to finance, fuzzy analytic hierarchy, green supply chain industries, smart health practice, and hotel selection. This wide range of topics makes the book interesting for all those working in the wider area of Fuzzy sets and systems and of fuzzy logic and for those who have the proper mathematical background who wish to become familiar with recent advances in fuzzy mathematics, which has entered to almost all sectors of human life and activity

    Development of Causal Model of Sustainable Hospital Supply Chain Management Using the Intuitionistic Fuzzy Cognitive Map (IFCM) Method

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    Purpose: Service industry is a massive sector accounting for about two-thirds of GDP of developed economies and is the field of an intensive competition between service companies and their supply chains. As a result, service supply chain management has become a subject of growing interest to researchers and business analysts. Healthcare industry is among the largest service industries with the highest potential for improvement in sustainability performance. The purpose of this study was to identify the concepts influencing the sustainability of hospital supply chain and provide a causal model for sustainable supply chain of hospital service. two aspects of contribution are identified for this research. Design/methodology/approach: In this study, concepts that influence the sustainability of a hospital service supply chain were identified by in-depth interviewing of 18 experts in hospitals of Kerman, Iran. Delphi method was used to reorganize the initial concepts into 15 concepts, Thus, a framework for sustainable supply chain of the hospital is proposed in the present study. This is the first contribution of this study. The second contribution is using the intuitive fuzzy cognitive map method for the relationship between extracted concepts. Findings: Delphi method was used to reorganize 68 initial concepts into 15 concepts Contains: demand management, resource and capacity management, customer relationship management, supplier relationship management, service management, information management, financial performance management, Attention to the environment, contamination, energy consumption, legal requirements, employees, community and stakeholders, social accountability and business ethics. The results indicate that service delivery management is highly central among other concepts. Originality/value: with focusing on concepts such as service management, and capacity and resources management, The sustainability of the hospital supply chain can be improved.Peer Reviewe

    Reverse Logistics Network Design with a 3-Phase Interactive Intuitionistic Fuzzy Goal Programming Approach: A Case Study of Covid-19 in Pathum Thani, Thailand

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    During outbreaks, a vast quantity of Infected Medical Waste (IMW) can be substantially generated in a short period, which poses a massive risk to medical personnel and surrounding communities. This study proposes an Intuitionistic Fuzzy Multi-Objective Multi-Period Mixed-Integer Linear Programming (IFMOMILP) model for effective IMW management in outbreaks under uncertainty, considering financial and risk factors subject to a priority from Decision Makers (DMs). The primary emphasis is on determining the optimal locations and capacity levels for temporary facilities, including temporary storage and treatment centers, as well as the optimal transportation routes. A 3-phase interactive Intuitionistic Fuzzy Goal Programming (i-IFGP) approach is developed to solve this IFMOMILP model. First, the Jiménez approach is applied to handle the uncertainties. Then, the problem is solved by Intuitionistic Fuzzy Goal Programming (IFGP). An actual case study of the COVID-19 outbreak in Pathum Thani province in Thailand was carried out to demonstrate the effectiveness of the proposed approach. The proposed approach yields solutions with varying feasibility degrees and scaling factors, providing alternatives for DMs. Then, the score function is utilized to imply DMs’ satisfaction with the outcomes, which is a concrete measure since it can reflect the intention of the DMs

    VIKOR Technique:A Systematic Review of the State of the Art Literature on Methodologies and Applications

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    The main objective of this paper is to present a systematic review of the VlseKriterijuska Optimizacija I Komoromisno Resenje (VIKOR) method in several application areas such as sustainability and renewable energy. This study reviewed a total of 176 papers, published in 2004 to 2015, from 83 high-ranking journals; most of which were related to Operational Research, Management Sciences, decision making, sustainability and renewable energy and were extracted from the “Web of Science and Scopus” databases. Papers were classified into 15 main application areas. Furthermore, papers were categorized based on the nationalities of authors, dates of publications, techniques and methods, type of studies, the names of the journals and studies purposes. The results of this study indicated that more papers on VIKOR technique were published in 2013 than in any other year. In addition, 13 papers were published about sustainability and renewable energy fields. Furthermore, VIKOR and fuzzy VIKOR methods, had the first rank in use. Additionally, the Journal of Expert Systems with Applications was the most significant journal in this study, with 27 publications on the topic. Finally, Taiwan had the first rank from 22 nationalities which used VIKOR technique
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