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

2020 ◽  
Vol 16 (1) ◽  
Author(s):  
Hangyao Wu ◽  
Zeshui XU
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Decision Support ◽  
Human Perception ◽  
Future Trends ◽  
Comprehensive Overview ◽  
Practical Applications ◽  
Intelligent Decision Making ◽  
Wide Range ◽  
Basic Ideas

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.

Pengembangan Aplikasi Pendukung Keputusan Pemilihan Program Studi dengan Metode Fuzzy Logic (Studi Kasus: Universitas Multimedia Nusantara)

2016 ◽  
Vol 7 (1) ◽  
pp. 12-18
Author(s):  
Joko Haryanto ◽  
Seng Hansun
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
System Application ◽  
Prospective Students ◽  
Fuzzy Logic Method ◽  
Index Terms ◽  
Selection Of

This paper describes the development of decision support system application to assist students who want to enter college so that no one choose the majors incorrectly. This application uses fuzzy logic method because fuzzy logic is very flexible in data which are vague and can be represented as a linguistic variable. The purpose of this application is to assist students to choose available majors at University Multimedia Nusantara which are appropriate with his/her capabilities. This application accepts five kinds of input values i.e. Mathematics, Indonesian, English, Physics, and TIK. Received input will be processed by the calculation of the system for decision-making and the application will generate output that shows how great a match for each majors. With this application, prospective students can find out where the majors that match his/her capabilities. This application has ninety nine percentage of match result accuracy. Index Terms—fuzzy logic, decision support system, UMN, selection of major

scholarly journals Clinical decision support systems in hospital care using ubiquitous devices: Current issues and challenges

2017 ◽  
Vol 25 (3) ◽  
pp. 1091-1104 ◽  
Author(s):  
Mirza Mansoor Baig ◽  
Hamid GholamHosseini ◽  
Aasia A Moqeem ◽  
Farhaan Mirza ◽  
Maria Lindén
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Hospital Care ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Smartphone Applications ◽  
Clinical Workflow ◽  
Healthcare Applications ◽  
Wide Range

Supporting clinicians in decision making using advanced technologies has been an active research area in biomedical engineering during the past years. Among a wide range of ubiquitous systems, smartphone applications have been increasingly developed in healthcare settings to help clinicians as well as patients. Today, many smartphone applications, from basic data analysis to advanced patient monitoring, are available to clinicians and patients. Such applications are now increasingly integrating into healthcare for clinical decision support, and therefore, concerns around accuracy, stability, and dependency of these applications are rising. In addition, lack of attention to the clinicians’ acceptability, as well as the low impact on the medical professionals’ decision making, are posing more serious issues on the acceptability of smartphone applications. This article reviews smartphone-based decision support applications, focusing on hospital care settings and their overall impact of these applications on the wider clinical workflow. Additionally, key challenges and barriers of the current ubiquitous device-based healthcare applications are identified. Finally, this article addresses current challenges, future directions, and the adoption of mobile healthcare applications.

Comparison Analysis of TOPSIS and Fuzzy Logic Methods On Fertilizer Selection

2018 ◽  
Vol 7 (2.3) ◽  
pp. 109 ◽  
Author(s):  
Asmara Indahingwati ◽  
Muh Barid Nizarudin Wajdi ◽  
Dwi Ermayanti Susilo ◽  
Nuning Kurniasih ◽  
Robbi Rahim
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Multiple Criteria Decision Making ◽  
Fruit Trees ◽  
Chemical Fertilizer ◽  
Interactive System ◽  
Topsis Method

Decision Support System is an interactive system that supports decision in the decision-making process through alternatives derived from the processing of data, information and design of the models. Selection decision support system of chemical fertilizer in fruit plant is expected to help anyone who wants to cultivate fruit trees can determine the chemical fertilizer as expected based alternatives and criteria set by the user. In this research method used is TOPSIS Method and Method of Fuzzy Logic. TOPSIS method is one of multiple criteria decision making method that uses the principle that the alternatives selected must have the shortest distance. Fuzzy Logic is a methodology of control systems troubleshooting, the fuzzy logic stated that everything is a binary which means it is only two possibilities, "Yes or No", "True or False", "Good or Bad", and others. Therefore, all of these can have a membership value of 0 or 1.  

scholarly journals Ecosystem services mapping and assessment for policy- and decision-making: Lessons learned from a comparative analysis of European case studies

One Ecosystem ◽  
2020 ◽  
Vol 5 ◽  
Author(s):  
Davide Geneletti ◽  
Blal Adem Esmail ◽  
Chiara Cortinovis ◽  
Ildikó Arany ◽  
Mario Balzan ◽  
...  
Keyword(s):  
Decision Making ◽  
Ecosystem Services ◽  
Case Studies ◽  
Lessons Learned ◽  
Assessment Methods ◽  
Assessment Process ◽  
The European Union ◽  
Comprehensive Overview ◽  
Horizon 2020 ◽  
Wide Range

This paper analyses and compares a set of case studies on ecosystem services (ES) mapping and assessment with the purpose of formulating lessons learned and recommendations. Fourteen case studies were selected during the EU Horizon 2020 “Coordination and Support Action” ESMERALDA to represent different policy- and decision-making processes throughout the European Union, across a wide range of themes, biomes and scales. The analysis is based on a framework that addresses the key steps of an ES mapping and assessment process, namely policy questions, stakeholder identification and involvement, application of mapping and assessment methods, dissemination and communication and implementation. The analysis revealed that most case studies were policy-orientated or gave explicit suggestions for policy implementation in different contexts, including urban, rural and natural areas. Amongst the findings, the importance of starting stakeholder engagement early in the process was confirmed in order to generate interest and confidence in the project and to increase their willingness to cooperate. Concerning mapping and assessment methods, it was found that the integration of methods and results is essential for providing a comprehensive overview from different perspectives (e.g. social, economic). Finally, lessons learned for effective implementation of ES mapping and assessment results are presented and discussed. Graphical Abstarcat in Fig. 1.

scholarly journals Expert Evaluation of Ecological and Economic Risks of Implementing Engineering Innovations by Coal-Mining Enterprises Based on Fuzzy Logic

2019 ◽  
Vol 297 ◽  
pp. 07005
Author(s):  
Elena Raevskaya ◽  
Alexander Pimonov ◽  
Vladimir Mihailov
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Decision Support ◽  
Coal Mining ◽  
Mining Industry ◽  
Risk Indicators ◽  
Qualitative Assessment ◽  
Expert Evaluation ◽  
Fuzzy Logics ◽  
Complex Approach

The article is about a complex approach based on the method of analyzing hierarchies and using of fuzzy logics for assessment of risks deals with engineering innovations in coal-mining industry. This approach allows evaluating both quantitative and qualitative risk indicators of compared alternative innovative mechanisms and equipment, does not depend on a field of expertise, thus it makes possible to attract specialists with competencies in various fields of knowledge. Such kind of approach allows making a qualitative assessment of the situation on the basis of formalized logical conclusions, making decision making comfortable and accessible to any specialist. The proposed methodology is implemented as a part of a decision support system.

Improving Intelligent Decision Making in Urban Planning

2021 ◽  
Vol 8 (3) ◽  
pp. 40-58
Author(s):  
Abderrazak Khediri ◽  
Mohamed Ridda Laouar ◽  
Sean B. Eom
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Urban Planning ◽  
Agglomerative Clustering ◽  
New Techniques ◽  
Intelligent Decision Support System ◽  
Intelligent Decision Making ◽  
Intelligent Decision ◽  
Urban Issues ◽  
Intelligent Decision Support

Generally, decision making in urban planning has progressively become difficult due to the uncertain, convoluted, and multi-criteria nature of urban issues. Even though there has been a growing interest to this domain, traditional decision support systems are no longer able to effectively support the decision process. This paper aims to elaborate an intelligent decision support system (IDSS) that provides relevant assistance to urban planners in urban projects. This research addresses the use of new techniques that contribute to intelligent decision making: machine learning classifiers, naïve Bayes classifier, and agglomerative clustering. Finally, a prototype is being developed to concretize the proposition.

An Intelligent Support System Integrating Data Mining and Online Analytical Processing

2011 ◽  
pp. 141-156
Author(s):  
Rahul Singh ◽  
Richard T. Redmond ◽  
Victoria Yoon
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Decision Support ◽  
Decision Makers ◽  
Online Analytical Processing ◽  
Intelligent Decision Making ◽  
Course Of Action ◽  
Intelligent Decision ◽  
Analytical Processing ◽  
Intelligent Decision Support

Intelligent decision support requires flexible, knowledge-driven analysis of data to solve complex decision problems faced by contemporary decision makers. Recently, online analytical processing (OLAP) and data mining have received much attention from researchers and practitioner alike, as components of an intelligent decision support environment. Little that has been done in developing models to integrate the capabilities of data mining and online analytical processing to provide a systematic model for intelligent decision making that allows users to examine multiple views of the data that are generated using knowledge about the environment and the decision problem domain. This paper presents an integrated model in which data mining and online analytical processing complement each other to support intelligent decision making for data rich environments. The integrated approach models system behaviors that are of interest to decision makers; predicts the occurrence of such behaviors; provides support to explain the occurrence of such behaviors and supports decision making to identify a course of action to manage these behaviors.

EBDMSS

2012 ◽  
pp. 265-284
Author(s):  
Fen Wang ◽  
Natalie Lupton ◽  
David Rawlinson ◽  
Xingguo Zhang
Keyword(s):  
Decision Making ◽  
Real Time ◽  
Support System ◽  
Balanced Scorecard ◽  
Business Strategy ◽  
Business Managers ◽  
Web Based ◽  
Intelligent Decision Making ◽  
Intelligent Decision ◽  
Wide Range

This paper describes a Web-based intelligent decision making support system (DMSS) to deliver balanced scorecard (BSC) based modelling and analysis in support of strategic E-business management. This framework supports E-business managers during the strategy making process in a comprehensive, integrated, and continuous manner. The paper demonstrates how practitioners can use this system to deliver a wide range of embodied E-business strategy expertise in support of real-time decision making.

SYSTEMATIC LOCATION OF THE PUBLIC LOGISTIC CENTRES IN CZECH REPUBLIC

Transport ◽  
2012 ◽  
Vol 26 (4) ◽  
pp. 425-432 ◽  
Author(s):  
Rudolf Kampf ◽  
Petr Průša ◽  
Christopher Savage
Keyword(s):  
Decision Making ◽  
Czech Republic ◽  
Decision Support ◽  
Decision Making Process ◽  
The Czech Republic ◽  
The Public ◽  
Suitable Tool ◽  
Wide Range ◽  
Suitable Location

This article is focusing on exploring parameters, which are needed to determine the most suitable location for public logistic centres in the Czech Republic. There is a wide range of factors, which will have an impact on the chosen location. It is not easy to define all the factors and include them into one model, especially because some of them are difficult to quantify. The aim of the research is to design a suitable tool to support the decision making process for the location of the public logistic centres. As public logistic centres will be partly financed by the Czech government, it is necessary to find a sensible tool as decision support.

scholarly journals Development of a decision making model for diagnosing diseases based on fuzzy logic

2019 ◽  
Vol 80 (4) ◽  
pp. 80-89
Author(s):  
L. A. Korobova ◽  
T. V. Gladkikh
Keyword(s):  
Mathematical Model ◽  
Decision Making ◽  
Fuzzy Logic ◽  
Decision Support ◽  
Decision Support System ◽  
Fuzzy Sets ◽  
Support System ◽  
Statistical Data ◽  
Eye Diseases ◽  
Diagnosis Of Diseases

The aim of the study is computer-aided decision-making support system (DSS) based on statistical data processing for the diagnosis of diseases. The modern pace of life leaves little time for a person to be able to see a doctor, sometimes even when a person falls ill. With regard to medical services, the introduction and dissemination of information technologies are becoming more and more relevant and relevant. A visit to the doctor takes a lot of time. To obtain any information, not to mention the actual examination with the need to communicate with the doctor, in some medical institutions it takes a lot of time, nerves and energy. Today, modern man cannot afford to waste time. With the emergence of various ailments in the human user there is a need for rapid diagnosis of the state of health. The problem here is to recognize the disease in time, prescribe the correct treatment and still force the user to see a doctor, a specialist for examination with the help of special medical technologies, continued diagnosis and subsequent treatment. This paper presents a mathematical model using fuzzy logic, which became the basis for the development of an application program designed to conduct a primary diagnosis of a possible disease. The program issues a recommendation for further treatment to a specialist. Baseline data, on the basis of which the development of the model was carried out, are related to eye diseases. Any discomfort causes inconvenience to the person. Eye disease is considered as a defeat of the organic and physical abilities of a person, sharpness and clarity of vision deteriorate. A person loses the ability to visually analyze the surrounding reality. A huge amount of statistics has been accumulated confirming the negative impact of adverse factors on the human visual organs. The studied statistics are related to the field of medicine, namely eye diseases. This area of research was the basis for consideration. The analysis of the collected data showed that their character is quite diverse and almost all of them have only a linguistic description. Therefore, for their processing it was necessary to choose a mathematical apparatus that would allow for their description, structuring and systematization. To do this, you can use a model based on fuzzy logic. Thus, the subject of research is the analysis of statistical data conducted using elements of fuzzy sets, which will allow to develop a mathematical model for determining the class of the disease. And then, with the help of a direct chain of reasoning, establish a presumptive diagnosis, as a recommendation of a decision support system. This approach to developing a decision support system for diagnosing diseases has not yet been applied. The objectives of the study is to study the diagnosis of diseases as an information process, the analysis of statistical data, description, structuring and systematization of data using elements of fuzzy sets and the development of a mathematical model using the inference rules. The result of the study is information on the determination of the belonging of the ailments (symptoms) to the class of diseases.

Sign in / Sign up

Export Citation Format

Share Document