Development of a Fuzzy Rule-based Decision-making System for Evaluating the Lifetime of a Rubber Fender

2014 ◽  
Vol 31 (5) ◽  
pp. 811-828 ◽  
Author(s):  
Sehee Lee ◽  
Sang-Uk Cheon ◽  
Jeongsam Yang
Keyword(s):  
Decision Making ◽  
Fuzzy Rule ◽  
Rule Based ◽  
Decision Making System

Fuzzy-Rule Based Adaptive Data Warehouse

2012 ◽  
Vol 3 (1) ◽  
pp. 47-65 ◽  
Author(s):  
Rajdev Tiwari ◽  
Anubhav Tiwari ◽  
Manu Pratap Singh
Keyword(s):  
Decision Making ◽  
Fuzzy Inference ◽  
Knowledge Workers ◽  
Fuzzy Rule ◽  
Data Warehouses ◽  
Large Reservoir ◽  
Inference System ◽  
Rule Based ◽  
Neuro Fuzzy ◽  
New Generation

Data Warehouses (DWs) are aimed to empower the knowledge workers with information and knowledge which helps them in decision making. Technically, the DW is a large reservoir of integrated data that does not provide the intelligence or the knowledge demanded by users. The burden of data analysis and extraction of information and knowledge from integrated data still lies upon the analyst’s shoulder. The overhead of analysts can be taken off by architecting a new generation data warehouses systems those shall be capable of capturing, organizing and representing knowledge along with the data and information in it. This new generation DW may be called as Knowledge Warehouse (KW) shall exhibit decision making capabilities themselves and can also supplement the Decision Support Systems (DSS) in making decisions quickly and effortlessly. This paper proposes and simulates a fuzzy-rule based adaptive knowledge warehouse with capabilities to learn and represent implicit knowledge by means of adaptive neuro fuzzy inference system (ANFIS).

scholarly journals Fuzzy Rule based Quality of Service Provisioning in Cognitive Radio Network

2018 ◽  
Vol 11 (1) ◽  
pp. 55-63
Author(s):  
Nisar A Lala ◽  
G M Mir ◽  
Altaf A Balkhi ◽  
N A Sofi
Keyword(s):  
Quality Of Service ◽  
Cognitive Radio ◽  
Fuzzy Rule ◽  
Fuzzy Decision Making ◽  
Rule Based ◽  
Decision Making System ◽  
Wireless Spectrum ◽  
Relationship Of ◽  
Idle Channel

Cognitive radio (CR) is a novel technology to resolve the issue of under-utilization of wireless spectrum. Quality of service (QoS) provisioning in CR networks to large number of traffic as per their need is not an easy task since no wireless spectrum is available on permanent basis for its operation. In this paper, few critical QoS parameters namely dynamic-availability-of-idle-channels (avail-idle-channel), expected-holding-time-of-idle-channel (HT-idle-channel) and user-mobility are chosen to analyze their impact over quality of service of the communicating cognitive users using rule-based fuzzy decision-making system. The results indicate the relationship of chosen parameters over the QoS of the communicating cognitive users.

scholarly journals Optimization Model of Fuzzy Rule Based Expert System Using Max-Min Composition and Schema Mapping Translation

INSIST ◽  
2017 ◽  
Vol 2 (1) ◽  
pp. 30 ◽  
Author(s):  
Hartono Hartono ◽  
Tiarma Simanihuruk
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Expert System ◽  
Membership Function ◽  
Fuzzy Rule ◽  
Fuzzy Decision Making ◽  
Schema Mapping ◽  
Fuzzy Decision ◽  
Rule Based ◽  
Knowledge Based

Abstract— Fuzzy Decision Making involves a process of selecting one or more alternatives or solutions from a finite set of alternatives which suits a set of constraints. In the rule-based expert system, the terms following in the decision making is using knowledge based and the IF Statements of the rule are called the premises, while the THEN part of the rule is called conclusion. Membership function and knowledge based determines the performance of fuzzy rule based expert system. Membership function determines the performance of fuzzy logic as it relates to represent fuzzy set in a computer. Knowledge Based in the other side relates to capturing human cognitive and judgemental processes, such as thinking and reasoning. In this paper, we have proposed a method by using Max-Min Composition combined with Genetic Algorithm for determining membership function of Fuzzy Logic and Schema Mapping Translation for the rules assignment.Keywords— Fuzzy Decision Making, Rule-Based Expert System, Membership Function, Knowledge Based, Max-Min Composition, Schema Mapping Translation

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