A Model for Detecting Customer Level Intentions to Purchase in B2C Websites Using TOPSIS and Fuzzy Logic Rule-Based System

2013 ◽  
Vol 39 (3) ◽  
pp. 1907-1922 ◽  
Author(s):  
Mehrbakhsh Nilashi ◽  
Othman Bin Ibrahim
Keyword(s):  
Fuzzy Logic ◽  
Rule Based ◽  
Rule Based System ◽  
Logic Rule

A fuzzy logic rule-based system for chromosome recognition

2002 ◽  
Author(s):  
J.M. Keller ◽  
P. Gader ◽  
O. Sjahputera ◽  
C.W. Caldwell ◽  
H.-M.T. Huang
Keyword(s):  
Fuzzy Logic ◽  
Rule Based ◽  
Rule Based System ◽  
Logic Rule

scholarly journals An Application Expert System for Evaluating Effective Factors on Trust in B2C WebsitesTrust, Security, ANFIS, Fuzzy Logic, Rule Based Systems, Electronic Commerce

Engineering ◽  
2011 ◽  
Vol 03 (11) ◽  
pp. 1063-1071 ◽  
Author(s):  
Mehrbakhsh Nilashi ◽  
Karamollah Bagherifard ◽  
Othman Ibrahim ◽  
Nasim Janahmadi ◽  
Mousa Barisami
Keyword(s):  
Fuzzy Logic ◽  
Expert System ◽  
Electronic Commerce ◽  
Rule Based ◽  
Effective Factors ◽  
Logic Rule ◽  
Rule Based Systems

Rule-Based Systems for Medical Diagnosis

2015 ◽  
pp. 21-44
Author(s):  
V. S. Giridhar Akula
Keyword(s):  
Fuzzy Logic ◽  
Decision Support ◽  
Support System ◽  
Medical Diagnosis ◽  
Intelligent Systems ◽  
Inference Rules ◽  
Rule Based ◽  
Rule Based System ◽  
Fault Monitoring ◽  
Design Scheduling

A rule-based system is a set of “if-then” statements that uses a set of assertions, to which rules on how to act upon those assertions are created. Rule-based expert systems have played an important role in modern intelligent systems and their applications in strategic goal setting, planning, design, scheduling, fault monitoring, diagnosis, and so on. The theory of decision support system is explained in detail. This chapter explains how the concepts of fuzzy logic are used for forward and backward chaining. Patient data is analyzed with the help of inference rules.

ECG Diagnostics by Fuzzy Decision Making

1998 ◽  
Vol 06 (02) ◽  
pp. 201-210 ◽  
Author(s):  
Adolf Grauel ◽  
Lars A. Ludwig ◽  
Georg Klene
Keyword(s):  
Fuzzy Logic ◽  
Medical Knowledge ◽  
Practical Experience ◽  
Fuzzy Logic System ◽  
Fuzzy Decision Making ◽  
Medical Expert ◽  
Rule Based ◽  
Rule Based System ◽  
Cardiac Diagnosis ◽  
Logic System

The analysis of electrocardiograms (ECGs) helps physicians make their cardiac diagnosis. Therefore a large store of medical knowledge and practical experience is required. In this paper we report on our investigations of a rule-based fuzzy logic system that processes ECG data using the knowledge of a medical expert. The aim is to give support to the physician for his diagnosis. In this first consideration we discuss single modules of the rule-based system proposed and moreover we present the used input and output variables of the rulebases. The performance of the implemented rule-based fuzzy logic system is tested using ECGs with abnormalities in the P and T wave as well as in the QRS complex. The system's output corresponds to the analysis of these ECGs by a medical expert.

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