ABSTRACT Expert systems have been intensively developed in various applications to solve problems. The advantage of expert systems depend highly on the accuracy of setting up the knowledge base and its rules. Therefore, model of inference engine to manage of uncertainties is needed. There are several popular model of the inference engine to manage uncertainties, such as probability theory, Demster-Shafer theory, and possibility theory. Model of inference engine for reasoning with uncertainties in expert systems using fuzzy logic was discussed. Rules were given along with membership functions. The Model of inference engine was used to conduct analysis by combining several interpretations of implications, inference methods, and several operat...
Reasoning with uncertain information has received a great deal of attention recently, as this issue ...
Purpose Expert systems are computer-based systems that mimic the logical processes of human experts ...
In this work we present a model for handling uncertain information. The concept of fuzzy knowledge-b...
Abstract — The aim of artificial intelligence is to develop tools for representing piece of knowledg...
AbstractThe management of uncertainty and imprecision is becoming more and more important in knowled...
Expert systems, being human-oriented systems in their essence, suffer from a lack of an appropriate ...
AbstractThis paper compares four measures that have been advocated as models for uncertainty in expe...
AbstractThis paper addresses the problem of modeling of expert knowledge as a starting point for inf...
Expert systems are well known area of artificial intelligence and have a huge impact in various fiel...
AbstractThe use of support pairs associated with the facts and rules of a knowledge base of an exper...
The management of uncertainty and imprecision is becoming more and more important in knowledge-base...
The aim of the research is to study the models, rules, and fuzzy inference engines, which occupy the...
Inference under uncertainty plays a crucial role in expert system and receives growing attention fro...
This thesis examines the issue of uncertainty reasoning and representation in expert systems. Uncert...
This book generalizes fuzzy logic systems for different types of uncertainty, including - semantic a...
Reasoning with uncertain information has received a great deal of attention recently, as this issue ...
Purpose Expert systems are computer-based systems that mimic the logical processes of human experts ...
In this work we present a model for handling uncertain information. The concept of fuzzy knowledge-b...
Abstract — The aim of artificial intelligence is to develop tools for representing piece of knowledg...
AbstractThe management of uncertainty and imprecision is becoming more and more important in knowled...
Expert systems, being human-oriented systems in their essence, suffer from a lack of an appropriate ...
AbstractThis paper compares four measures that have been advocated as models for uncertainty in expe...
AbstractThis paper addresses the problem of modeling of expert knowledge as a starting point for inf...
Expert systems are well known area of artificial intelligence and have a huge impact in various fiel...
AbstractThe use of support pairs associated with the facts and rules of a knowledge base of an exper...
The management of uncertainty and imprecision is becoming more and more important in knowledge-base...
The aim of the research is to study the models, rules, and fuzzy inference engines, which occupy the...
Inference under uncertainty plays a crucial role in expert system and receives growing attention fro...
This thesis examines the issue of uncertainty reasoning and representation in expert systems. Uncert...
This book generalizes fuzzy logic systems for different types of uncertainty, including - semantic a...
Reasoning with uncertain information has received a great deal of attention recently, as this issue ...
Purpose Expert systems are computer-based systems that mimic the logical processes of human experts ...
In this work we present a model for handling uncertain information. The concept of fuzzy knowledge-b...