Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/262528
Title: | Design and Development of Fuzzy Expert System for Disease Diagnosis |
Researcher: | Kasbe Tanmay |
Guide(s): | Pippal Ravi Kumar Singh |
Keywords: | Engineering and Technology,Computer Science,Automation and Control Systems |
University: | RKDF University |
Completed Date: | 2019 |
Abstract: | The advancements of computer technology are playing a important role in diagnosis of medical newlinesystems. Medical diagnosis is full of uncertainty and dynamically changed according to the newlinesituations. Now a day the use of computer technology is essential in every filed and medical newlinediagnosis area is not an exception. The diagnostic decision depends upon experience, expertise newlineand use of proper method with powerful logical reasoning ability. We know very well that newlinethese fields, in which the computers are used, have very high complexity and irregularity and newlinethe use of expert systems such as fuzzy logic, artificial network and genetic algorithm have newlinebeen developed. Expert Systems is an smart computer is based on decision making tool that newlineuses dataset and rules to solve real life problems based on knowledge obtained from one or newlinemore of a human expert in a specific areas. Medical Diagnosis system is a system which can newlinediagnose any diseases through checking out the symptoms. Diagnosis of human disease is one newlineof the complicated and difficul t processes and it requires high level of expertise. Fuzzy expert newlinesystem is one of the best systems to diagnosis medical disease because any disease diagnosis newlinehas so many uncertainties and fuzzy logic is the best tool to deal with uncertainty. Despite newlinethe fact that there are some limitations due to information, educational and other reasons these newlinesystems are widely acknowledged in medical institutions. newlineFuzzy logic is advance version of Boolean logic. Fuzzy logic first was introduced in the year of newline1930 by Polish Philosopher Jan lukasiewicz. Later in 1965, Lotfi Zadeh regenerate fuzziness newlineand explored in broad way. Fuzzy logic works on the concept of mathematical principles to newlinerepresent knowledge base and degree of membership rather than binary logic. Fuzzy logic newlinebased on multivalve whereas Boolean logic based on only two values. An expert system that newlineused fuzzy logic is known as fuzzy expert system. Fuzzy expert system is a collection of fuzzy newlinerules, membership functions and fuzzy rules that |
Pagination: | x, 90p. |
URI: | http://hdl.handle.net/10603/262528 |
Appears in Departments: | Faculty of Computer Science & Application |
Files in This Item:
File | Description | Size | Format | |
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01_title.pdf | Attached File | 180.54 kB | Adobe PDF | View/Open |
02_declaration.pdf | 78 kB | Adobe PDF | View/Open | |
03_certificate.pdf | 65.47 kB | Adobe PDF | View/Open | |
04_forwarding letter.pdf | 63.72 kB | Adobe PDF | View/Open | |
05_acknowledgement.pdf | 27.14 kB | Adobe PDF | View/Open | |
06_abstract.pdf | 24.91 kB | Adobe PDF | View/Open | |
07_contents.pdf | 257.39 kB | Adobe PDF | View/Open | |
08_list of figures.pdf | 19.09 kB | Adobe PDF | View/Open | |
09_list of tables.pdf | 10.83 kB | Adobe PDF | View/Open | |
10_chapter1.pdf | 562.66 kB | Adobe PDF | View/Open | |
11_chapter2.pdf | 431.96 kB | Adobe PDF | View/Open | |
12_chapter3.pdf | 812.49 kB | Adobe PDF | View/Open | |
13_chapter4.pdf | 762.18 kB | Adobe PDF | View/Open | |
14_chapter5.pdf | 3.37 MB | Adobe PDF | View/Open | |
15_conclusion.pdf | 27.07 kB | Adobe PDF | View/Open | |
16_summary.pdf | 204.81 kB | Adobe PDF | View/Open | |
17_references.pdf | 204.88 kB | Adobe PDF | View/Open | |
18_publications.pdf | 2.03 MB | Adobe PDF | View/Open | |
19_presentations.pdf | 5.58 MB | Adobe PDF | View/Open | |
20_saims certificate.pdf | 1.57 MB | Adobe PDF | View/Open | |
21_plagiarism report.pdf | 371.47 kB | Adobe PDF | View/Open |
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