Optimal Inventory of Computer Repair Parts: A Fuzzy Systems Approach

2010 ◽  
Author(s):  
Les M. Sztandera
Keyword(s):  
Fuzzy Systems ◽  
Systems Approach

scholarly journals An Exploratory Study of Hierarchical Fuzzy Systems Approach in A Recommendation System

2019 ◽  
Vol 14 (2) ◽  
pp. 174-186
Author(s):  
Tajul Rosli Razak ◽  
Iman Hazwam Abd Halim ◽  
Muhammad Nabil Fikri Jamaludin ◽  
Mohammad Hafiz Ismail ◽  
Shukor Sanim Mohd Fauzi
Keyword(s):  
Fuzzy Logic ◽  
Fuzzy Systems ◽  
Recommendation System ◽  
Systems Approach ◽  
Fuzzy Logic Systems ◽  
Input Variables ◽  
Hierarchical Fuzzy System ◽  
Hierarchical Fuzzy Systems ◽  
Insight Into ◽  
Logic System

Recommendation system, also known as a recommender system, is a tool to help the user in providing asuggestion of a specific dilemma. Recently, the interest in developing a recommendation system in manyfields has increased. Fuzzy Logic system (FLSs) is one of the approaches that can be used to model therecommendation systems as it can deal with uncertainty and imprecise information. However, one of thefundamental issues in FLS is the problem of the curse of dimensionality. That is, the number of rules inFLSs is increasing exponentially with the number of input variables. One effective way to overcome thisproblem is by using Hierarchical Fuzzy System (HFSs). This paper aims to explore the use of HFSs forRecommendation system. Specifically, we are interested in exploring and comparing the HFS and FLS forthe Career path recommendation system (CPRS) based on four key criteria, namely topology, the numberof rules, the rules structures and interpretability. The findings suggested that the HFS has advantagesover FLS towards improving the interpretability models, in the context of a recommendation systemexample. This study contributes to providing an insight into the development of interpretable HFSs in theRecommendation systems. Keywords: Fuzzy Logic Systems, Hierarchical Fuzzy Systems, Recommendation Systems

Collaborative Control of Multiple Robots Using Genetic Fuzzy Systems Approach

2018 ◽  
Author(s):  
Anoop Sathyan ◽  
Ou Ma
Keyword(s):  
Fuzzy Systems ◽  
Systems Approach ◽  
Target Position ◽  
Multiple Robots ◽  
Fuzzy Logic Systems ◽  
Genetic Fuzzy Systems ◽  
Elastic Strings ◽  
Collaborative Control ◽  
Invaluable Tool ◽  
Extensive Test

This paper introduces a decentralized approach of collaborative control between multiple robots. A dynamic problem is considered to illustrate the effectiveness of this approach. The objective of this problem is to control three robots that are connected to a ball through elastic strings to bring the ball to a pre-defined target position. Since there is no communication between the robots, each robot does not know how the other robots are going to react at any instant. The only information available to the robots are the current and target positions of the ball. Genetic Fuzzy Systems (GFSs) are used to develop controllers for individual robots to tackle this problem. The nonlinearity of fuzzy logic systems coupled with the search capability of Genetic Algorithm (GA) provides an invaluable tool to design controllers for such tasks. The system is first trained through a set of scenarios and then applied to an extensive test set to test the effectiveness of the approach.

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