Fuzzy Logic-Based Adaptive Decision Support in Autonomous Vehicular Networks

2014 ◽  
pp. 215-236
Author(s):  
Chrysostomos Chrysostomou ◽  
Constantinos Djouvas ◽  
Lambros Lambrinos
Keyword(s):  
Fuzzy Logic ◽  
Decision Support ◽  
Vehicular Networks

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 A Decision Support System Coupling Fuzzy Logic and Probabilistic Graphical Approaches for the Agri-Food Industry: Prediction of Grape Berry Maturity

PLoS ONE ◽  
2015 ◽  
Vol 10 (7) ◽  
pp. e0134373 ◽  
Author(s):  
Nathalie Perrot ◽  
Cédric Baudrit ◽  
Jean Marie Brousset ◽  
Philippe Abbal ◽  
Hervé Guillemin ◽  
...  
Keyword(s):  
Fuzzy Logic ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Food Industry ◽  
Grape Berry ◽  
System Coupling

Decision Support System Based on Fuzzy Logic for Assessment of Expected Corporate Income Performance

2021 ◽  
pp. 2150009
Author(s):  
Arthur Yosef ◽  
Eli Shnaider ◽  
Rimona Palas ◽  
Amos Baranes
Keyword(s):  
Fuzzy Logic ◽  
Decision Support ◽  
Operating Income ◽  
Explanatory Variables ◽  
Section Model ◽  
Evaluation Mechanism ◽  
One Year ◽  
High Degree ◽  
Decision Support Method ◽  
Very High

This study presents a decision-support method to estimate the next year performance of corporate Operating Income Margin (OIM). It is based on a unique combination of cross-section model and the rules-based evaluation mechanism. The estimate is done in terms of broad categories, and not precise numerical values. The model is constructed as follows: its dependent variable (OIM) is one year ahead vs. the corresponding explanatory variables. This structure of the model allows us to view explanatory variables as reflecting financial potential of corporations. The evaluation component consists of a set of rules designed to identify the companies whose “potential” clearly points to an opportunity to invest. For the method presented here to succeed, it is necessary to utilize a highly reliable modeling method, even if it is “Fuzzy”. We apply Soft Regression (SR), which is a Soft Computing modeling tool based on Fuzzy Logic, and utilize all available proxy variables by creating intervals of values. Advantages of utilizing SR, and the intervals’-based modeling are extensively discussed. Modeling results for five consecutive years are consistent and stable, thus indicating high degree of reliability. Testing indicates very high success rate for the stock market related domain, the lowest being 87.9%.

Solution on Decision Support in Determining of Repair Actions Using Fuzzy Logic and Agent System

2014 ◽  
pp. 533-541 ◽  
Author(s):  
Maxim Denisov ◽  
Alexey Kizim ◽  
Valery Kamaev ◽  
Svetlana Davydova ◽  
Anna Matohina
Keyword(s):  
Fuzzy Logic ◽  
Decision Support ◽  
Agent System
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