Fuzzy logic
Fuzzy logic is a form of multi-valued logic derived from fuzzy set theory to deal with reasoning that is approximate rather than precise. In contrast with "crisp logic", where binary sets have binary logic, the fuzzy logic variables may have a membership value of not only 0 or 1 â€œ that is, the degree of truth of a statement can range between 0 and 1 and is not constrained to the two truth values of classic propositional logic.
Fuzzy logic emerged as a consequence of the 1965 proposal of fuzzy set theory by Lotfi Zadeh.Though fuzzy logic has been applied to many fields, from control theory to artificial intelligence, it still remains controversial among most statisticians.
Summarizing, it has turned out that mathematical fuzzy logic can be developed to a deep and highly interesting logic analogously to the classical (Boolean) logic; the results
are important not only for their mathematical depth but also as foundations of methods of fuzzy logic in broad sense.
Fuzzy rule-based framework for management of malaria
The application of the conventional symbolic rules found in knowledge base technology to the management of a disease suffers from its inability to evaluate the degree of severity of a symptom and by extension, the degree of the illness. Fuzzy logic technology provides a simple way to arrive at a definite conclusion from vague, ambiguous, imprecise and noisy data (as found in medical data) using linguistic variables that are not necessarily precise. In order to achieve this, a study of a knowledge base system for the management of diseases was undertaken. The root sum square of drawing inference was employed to infer the data from the rules developed. This resulted in the establishment of some degrees of influence on the diseases. Using malaria as a case study, a system that uses Visual Basic .Net development environment was developed and the results of the computations are presented in this research.
Detailed seminars report download:
http://inderscience.metapress.com/media/...568m75.pdf