scholarly journals Application of Fuzzy Expert System in Determination of MMPI-2 Protocol Code Type

2018 ◽  
Vol 7 (2) ◽  
pp. 4-9
Author(s):  
Pavel Škobrtal ◽  
Iveta Bebčáková ◽  
Jana Talašová
Keyword(s):  
Expert System ◽  
Fuzzy Expert System ◽  
Code Type

On Sharp Boundary Problem in Rule Based Expert Systems in the Medical Domain

2010 ◽  
Vol 5 (3) ◽  
pp. 14-26
Author(s):  
Oladipupo O. Olufunke ◽  
Uwadia O. Charles ◽  
Ayo K. Charles
Keyword(s):  
Coronary Heart Disease ◽  
Heart Disease ◽  
Expert System ◽  
Boundary Problem ◽  
System Approach ◽  
Disease Risk ◽  
Fuzzy Expert System ◽  
Sharp Boundary ◽  
Rule Based

Recently, the application of the conventional rule based expert system for disease risk determination in medical domains has increased. However, a major limitation to the effectiveness of the rule based expert system approach is the sharp boundary problem that leads to underestimation or overestimation of boundary cases, which ultimately affects the accuracy of their recommendation. In this paper, an expert driven approach is used to investigate the viability of a fuzzy expert system in the determination of risk associated with coronary heart disease with regards to the sharp boundary problem in rule based expert system.

Fuzzy expert system to determine stream water quality classification from ecological information

1997 ◽  
Vol 36 (12) ◽  
pp. 199-206 ◽  
Author(s):  
H. K. Lee ◽  
K. D. Oh ◽  
D. H. Park ◽  
J. H. Jung ◽  
S. J. Yoon
Keyword(s):  
Water Quality ◽  
Expert System ◽  
Stream Water ◽  
Water Quality Management ◽  
Fuzzy Expert System ◽  
Stream Water Quality ◽  
Ecological Information ◽  
Quality Classification ◽  
Water Quality Classification

Water quality classification for stream has been major tool for water quality management in Korea. This paper examines the application of the fuzzy inference mechanism to develop a fuzzy expert system for proper determination of WQCS from uncertain and imprecise ecological information. This study proposes a rule matrix composed of seven water quality grades, toxicity of water and rarity of cases. From this rule matrix, 30 rules for WQCS determination are generated. From the comparison of performance of the fuzzy expert system and the conventional expert system for the determination of class, toxicity, and rarity, it seems that the smoothly varying curves of WQCS determination from the fuzzy expert system represent our real-world experience more realistically than stepwise curves from the conventional expert system.

scholarly journals Fuzzy Expert System for Earthquake Prediction in Western Himalayan Range

2020 ◽  
Vol 26 (3) ◽  
pp. 4-12
Author(s):  
Rabia Tehseen ◽  
Muhammad Shoaib Farooq ◽  
Adnan Abid
Keyword(s):  
Expert System ◽  
Expert Systems ◽  
Quantitative Determination ◽  
Earthquake Prediction ◽  
Rule Base ◽  
Fuzzy Expert System ◽  
Human Expert ◽  
Magnitude Scales ◽  
Earthquake Data

Fuzzy Expert System (FES) with application to earthquake prediction has been presented to reproduce the performance of a human expert in earthquake prediction using expert systems. This research aims to predict future earthquakes having a magnitude 5.5 or greater. Previous earthquake data from 2000 to 2019 have been collected for this purpose. Since the earthquake data for the specified region have been reported on different magnitude scales, suitable relationships were determined to obtain uniform data. The uniform data have been used to calculate seismicity indicators according to the guidelines provided by Gutenberg-Richter’s scale for quantitative determination of earthquake features. The relationships among these seismic indicators have been used by the human expert to set the rule base of Fuzzy expert system. These rules have been mathematically validated and tested on instrumentally recorded earthquake data. The results obtained from the proposed FES presented 47 % accuracy in predicting future earthquakes that may occur in the 100 km radial area from 34.708 ° N, 72.5478 ° E.

On Sharp Boundary Problem in Rule Based Expert Systems in the Medical Domain

2012 ◽  
pp. 112-124
Author(s):  
Oladipupo O. Olufunke ◽  
Uwadia O. Charles ◽  
Ayo K. Charles
Keyword(s):  
Coronary Heart Disease ◽  
Heart Disease ◽  
Expert System ◽  
Boundary Problem ◽  
System Approach ◽  
Disease Risk ◽  
Fuzzy Expert System ◽  
Sharp Boundary ◽  
Rule Based

Recently, the application of the conventional rule based expert system for disease risk determination in medical domains has increased. However, a major limitation to the effectiveness of the rule based expert system approach is the sharp boundary problem that leads to underestimation or overestimation of boundary cases, which ultimately affects the accuracy of their recommendation. In this paper, an expert driven approach is used to investigate the viability of a fuzzy expert system in the determination of risk associated with coronary heart disease with regards to the sharp boundary problem in rule based expert system.

Developing a fuzzy expert system for determining the levels of students' eHealth literacy (Preprint)

2019 ◽  
Author(s):  
Roghayeh Eskrootchi ◽  
Masoud Zavari ◽  
Chetan Kumar ◽  
Mohammadreza Alibeyk ◽  
Amir Ramezani
Keyword(s):  
Health Literacy ◽  
Expert System ◽  
Expert Systems ◽  
Rough Set Theory ◽  
Fuzzy Expert System ◽  
Ehealth Literacy ◽  
Significant Difference ◽  
Literacy Level ◽  
Electronic Health

BACKGROUND The concept of eHealth literacy refers to the ability of a person to access electronic health information, evaluate the information and apply the resulting knowledge in order to address or solve a health problem. In a society with higher levels of e-health literacy, health and aid in health care can be promoted by using electronic health tools. The first step of promoting eHealth literacy is to assess the current situation of society and determine its health literacy level. Although there are different methods for determination of the level of eHealth literacy in the existing studies, there is no way to measure the level of e-health literacy more precisely and realistically due to its subjective concept. OBJECTIVE This research aims to develop and implement a fuzzy expert system to determine the level of eHealth literacy. The system must be able to identify the weakness of students' e-health literacy in order to tailor services and information to the needs of the target group. In addition, the system could be a help for responsible organizations such as the Ministry of Health or the university to suggest intervention programs for improving the students' eHealth literacy based on the results. METHODS In this paper, different ways of measuring the individual’s literacy level were extracted. Due to the experts’ opinion, the Digital Health Literacy Instrument was selected and used to develop a rule-based fuzzy expert system to determine the levels of eHealth literacy. The reliability and validity of the expert system were evaluated based on the experts’ judgment and by asking for the participation of 50 students of Mashhad University of Medical Sciences. In order to decrease the calculation time and make the system easier to use, the fuzzy expert system was modified based on rough set theory, which caused a reduction in the number of rules from 300 to 159. RESULTS The comparison between the two fuzzy expert systems indicated that no significant difference was detected and both systems were succeeded in around 90% of the cases. CONCLUSIONS Determination of the levels of students’ electronic health literacy is a complex problem that includes uncertainty and inaccuracy. Due to the accuracy and agility of expert systems, it is recommended to use the fuzzy-rough expert system in order to overcome this problem.

Determination of the drug dose by fuzzy expert system in treatment of chronic intestine inflammation

2009 ◽  
Vol 20 (2) ◽  
pp. 169-176 ◽  
Author(s):  
Ismail Saritas ◽  
Ilker A. Ozkan ◽  
Novruz Allahverdi ◽  
Mustafa Argindogan
Keyword(s):  
Expert System ◽  
Drug Dose ◽  
Fuzzy Expert System

Fuzzy Expert System Approach for Determination of α-Linolenic Acid Content of Eggs Obtained from Hens by Dietary Flaxseed

2007 ◽  
Vol 13 (3) ◽  
pp. 217-223 ◽  
Author(s):  
H. Yalçin ◽  
S. Taşdemir
Keyword(s):  
Fuzzy Logic ◽  
Expert System ◽  
Linolenic Acid ◽  
Acid Content ◽  
System Approach ◽  
Fuzzy Expert System ◽  
Linolenic Acid Content ◽  
Experimental Values ◽  
Windows Xp

This paper presents the development of a fuzzy expert system (FES) for determination of α-linolenic acid content of eggs, obtained from hens fed dietary flaxseed. Based on experimental values FES models were designed using MATLAB 6.5 fuzzy logic toolbox in Windows XP running on Intel 1.9 Gh environment. It was used time and flaxseed ratio as input parameters and linolenic acid content as output. There was a good correlation ( R2 = 0.9983) between experimental values and FES (P < 0.05, t-test).

A FUZZY EXPERT SYSTEM FOR SOLVING REAL-OPTION DECISION PROCESSES

2001 ◽  
Vol 06 (02) ◽  
Author(s):  
C.A Magni ◽  
G. Mastroleo ◽  
G. Facchinetti
Keyword(s):  
Expert System ◽  
Real Option ◽  
Decision Processes ◽  
Fuzzy Expert System
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