AN ALTERNATIVE APPROACH IN APPROXIMATE REASONING USING FUZZY PRODUCTION RULES IN EXPERT SYSTEMS

1991 ◽  
Vol 05 (03) ◽  
pp. 485-502 ◽  
Author(s):  
M. HALIM ◽  
K. M. HO ◽  
A. LIU
Keyword(s):  
Expert Systems ◽  
Rheumatic Fever ◽  
Medical Diagnosis ◽  
Acute Rheumatic Fever ◽  
Modus Ponens ◽  
Approximate Reasoning ◽  
Production Rules ◽  
Alternative Approach ◽  
Fuzzy Production Rules

This paper outlines an alternative approach using fuzzy production rules to handle approximate reasoning in expert systems without using the Generalised Modus Ponens (GMP) model by Zadeh. The proposed approach provides a method whereby a collection of rules is used to specify the properties of the inference as required by the expert. An example on the medical diagnosis of Acute Rheumatic Fever is used for illustration.

scholarly journals Approximate Reasoning in Supervised Classification Systems

2006 ◽  
Vol 10 (4) ◽  
pp. 586-593 ◽  
Author(s):  
Hamid Seridi ◽  
◽  
Herman Akdag ◽  
Rachid Mansouri ◽  
Mohamed Nemissi ◽  
...  
Keyword(s):  
Modus Ponens ◽  
Classification Systems ◽  
Approximate Reasoning ◽  
Production Rules ◽  
Training Set ◽  
Inference System ◽  
Degree Of Belief ◽  
Knowledge Based ◽  
Symbolic Approach ◽  
Iris Data

In knowledge-based systems, uncertainty in propositions can be represented by various degrees of belief encoded by numerical or symbolic values. The use of symbolic values is necessary in areas where the exact numerical values associated with a fact are unknown by experts. In this paper we present an expert system of supervised automatic classification based on a symbolic approach. This last is composed of two sub-systems. The first sub-system automatically generates the production rules using training set; the generated rules are accompanied by a symbolic degree of belief which characterizes their classes of memberships. The second is the inference system, which receives in entry the base of rules and the object to classify. Using classical reasoning (Modus Ponens), the inference system provides the membership class of this object with a certain symbolic degree of belief. Methods to evaluate the degree of belief are numerous but they are often tarnished with uncertainty. To appreciate the performances of our symbolic approach, tests are made on the Iris data basis.

MODELING FUZZY REASONING USING HIGH LEVEL FUZZY PETRI NETS

1996 ◽  
Vol 04 (01) ◽  
pp. 61-85 ◽  
Author(s):  
HELOISA SCARPELLI ◽  
FERNANDO GOMIDE ◽  
WITOLD PEDRYCZ
Keyword(s):  
Time Complexity ◽  
Fuzzy Reasoning ◽  
Approximate Reasoning ◽  
Data Driven ◽  
Production Rules ◽  
Formal Tool ◽  
Fuzzy Petri Net ◽  
Fuzzy Production Rules ◽  
Fuzzy Petri Nets ◽  
High Level

A formal tool, the High Level Fuzzy Petri Net, is proposed for representing and processing fuzzy production rules in a knowledge base. The basic net structures to model inference patterns in approximate reasoning are introduced. The chaining mechanism used and the modeling of rules with fuzzy quantifiers and certainty factors are discussed. We have also investigated the representation of parallel and conflicting rules. Two types of fuzzy reasoning algorithms, to answer data driven and goal driven queries are described. The issue of time complexity of the algorithms is also addressed.

Acute Rheumatic Fever: A population-based study in Wallis, a South Pacific Island

2015 ◽  
Vol 181 ◽  
pp. 30-31 ◽  
Author(s):  
Thomas Fauchier ◽  
Muriel Tafflet ◽  
Graziella Filitoga ◽  
Laurent Morisse ◽  
Eloi Marijon ◽  
...  
Keyword(s):  
Rheumatic Fever ◽  
Acute Rheumatic Fever ◽  
South Pacific ◽  
Population Based ◽  
Pacific Island ◽  
Population Based Study ◽  
South Pacific Island

Mean platelet volume in acute rheumatic fever

Platelets ◽  
2012 ◽  
Vol 24 (5) ◽  
pp. 378-382 ◽  
Author(s):  
Ahmet Sert ◽  
Ebru Aypar ◽  
Dursun Odabas
Keyword(s):  
Rheumatic Fever ◽  
Mean Platelet Volume ◽  
Acute Rheumatic Fever ◽  
Platelet Volume
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