[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-124808-en":3,"doc-seo-124808-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},124808,4810365810221,"Aurora","https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d",8,"Research & Report","Intelligent Decision Support Systems - An Analysis of Machine Learning and Multicriteria Decision-Making Methods","Complex decision-making requires selecting appropriate multi-criteria decision making (MCDM) methods for solving real-world problems under uncertainty. This research investigates how machine learning and MCDM can be integrated within intelligent decision support systems (IDSS), with attention to the significance of decision support systems and the methods, approaches, frameworks, or algorithms used. Literature from 2015 to early 2020 is reviewed using quality assessment criteria to identify application domains and contributions, guiding early-stage researchers toward more intelligent and cost-effective solution design.","2.7  \n4.5  \nReview  \nIntelligent Decision Support Systems—An Analysis of Machine Learning and Multicriteria DecisionMaking Methods  \nRahman Ali, Anwar Hussain, Shah Nazir, Sulaiman Khan and Habib Ullah Khan  \nSpecial Issue  \nMulti-Criteria Decision Making (MCDM) Using Artificial Intelligence (AI)  \nEdited by  \nDr. Rahman Ali, Dr. Asad Masood Khattak and Dr. Farkhund Iqbal  \n[https://doi.org/10.3390/app132212426](https://doi.org/10.3390/app132212426)  \napplied sciences  \nReview  \nIntelligent Decision Support Systems—An Analysis of Machine Learning and Multicriteria Decision-Making Methods  \nRahman Ali 1, Anwar Hussain 2, *, Shah Nazir 2, Sulaiman Khan 2 and Habib Ullah Khan 3  \nCitation: Ali, R.; Hussain, A.; Nazir, S.; Khan, S.; Khan, H.U. Intelligent Decision Support Systems—An Analysis of Machine Learning and Multicriteria Decision-Making Methods. Appl. Sci. 2023, 13, 12426 . [https://doi.org/10.3390/](https://doi.org/10.3390/)[ ](https://doi.org/10.3390/)app132212426  \nAcademic Editors: Andrea Prati, Panagiotis G. Asteris and Yudong Zhang  \nReceived: 3 January 2023  \nRevised: 24 January 2023  \nAccepted: 1 March 2023  \nPublished: 17 November 2023  \nCopyright: © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ([https://](https://)[ ](https://)[creativecommons.org/licenses/by/](creativecommons.org/licenses/by/)[ ](creativecommons.org/licenses/by/)[4.0/](4.0/)) .  \n1 Quaid-e-Azam College of Commerce, University of Peshawar, Peshawar 25120, Pakistan  \n2 Department of Computer Science, University of Swabi, Swabi 23430, Pakistan  \n3 College of Business and Economics, Qatar University, Doha 2713, Qatar  \n* Correspondence: [anwar@uoswabi.edu.pk](anwar@uoswabi.edu.pk)  \nAbstract: Context: The selection and use of appropriate multi-criteria decision making (MCDM) methods for solving complex problems is one of the challenging issues faced by decision makers in the search for appropriate decisions. To address these challenges, MCDM methods have effectively been used in the areas of ICT, farming, business, and trade, for example. This study explores the integration of machine learning and MCDM methods, which has been used effectively in diverse application areas. Objective: The objective of the research is to critically analyze state-of-the-art research methods used in intelligent decision support systems and to further identify their application areas, the signi􀀂cance of decision support systems, and the methods, approaches, frameworks, or algorithms exploited to solve complex problems. The study provides insights for early-stage researchers to design more intelligent and cost-effective solutions for solving problems in various application domains. Method: To achieve the objective, literature from the years 2015 to early 2020 was searched and considered in the study based on quality assessment criteria. The selected relevant literature was studied to respond to the research questions proposed in this study. To 􀀂nd answers to the research questions, pertinent literature was analyzed to identify the application domains where decision support systems are exploited, the impact and signi􀀂cance of the contributions, and the algorithms, methods, and techniques which are exploited in various domains to solve decisionmaking problems. Results: Results of the study show that decision support systems are widely used as useful decision-making tools in various application domains. The research has collectively studied machine learning, arti􀀂cial intelligence, and multi-criteria decision-making models used to provide ef􀀂cient solutions to complex decision-making problems. In addition, the study delivers detailed insights into the use of AI, ML and MCDM methods to the early-stage researchers to start their research in the right direction and provide them with a clear roadmap of research. Hence, the development of","cbCaipBq6tdBklqp","https://ap.wps.com/l/cbCaipBq6tdBklqp","pdf",2150547,1,32,"English","en",105,"# Abstract\n# Introduction\n## Multi-criteria decision making and decision support systems\n## Scope and challenges of intelligent decision support systems\n# Keywords\n# Review Focus","[{\"question\":\"What problem does the research focus on?\",\"answer\":\"The research focuses on selecting and using appropriate multi-criteria decision making methods to solve complex problems within intelligent decision support systems.\"},{\"question\":\"What is the main objective of the study?\",\"answer\":\"The study aims to critically analyze state-of-the-art research methods used in intelligent decision support systems and identify their application areas and the role of decision support methods and algorithms.\"},{\"question\":\"How is the study conducted?\",\"answer\":\"The study searches and evaluates literature from 2015 to early 2020 using quality assessment criteria, then analyzes selected sources to address the proposed research questions and identify application domains and methods used.\"}]","Intelligent Decision Support Systems - 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