شماره ركورد كنفرانس :
3297
عنوان مقاله :
A PSO Fuzzy-Expert System: As an Assistant for Specifying the Acceptance by NOET Measures, at PH.D Level
پديدآورندگان :
Mousavi Muhammad Hossein Department of Computer Engineering - Bu Ali Sina University Hamedan - Iran , MiriNezhad S.Younes Department of Computer Engineering - Bu Ali Sina University Hamedan - Iran , Shafeii Mosleh Mehrdad Department of Computer Engineering - Bu Ali Sina University Hamedan - Iran , Dezfoulian Mir Hossein Department of Computer Engineering - Bu Ali Sina University Hamedan - Iran
كليدواژه :
(Particle Swarm Optimization (PSO , Evolutionary Algorithms , Fuzzy- Expert System , Classification , NOET Measures , PH.D Level
عنوان كنفرانس :
نوزدهمين سمپوزيوم بين المللي هوش مصنوعي و پردازش سيگنال
چكيده لاتين :
The intelligent decision making systems are useful tools
for the assistance of human expert, and or as a perfect alternative
for expert in a variety of auto-decision making fields. The use of
such systems in education, agriculture, industry, fishery, animal
husbandry etc., can decrease manpower errors or need of it; In the
other hand, it can increase the quality and the pace of service
giving. The interview at the PH.D level or even Master's degree,
due to the high sensitivity in scoring to the candidates, is of high
importance. Therefore, creating a system for storing these scores,
and inferring the results can be beneficial when there is a large
number of candidates. In this paper, the expert system has an
educational use, and classifies the probability of acceptance or
unacceptance of PH.D candidates in the exam and interview, based
on the (National Organization of Educational Testing) NOET
measures, also estimates scientific level of candidates. The
proposed fuzzy-expert system takes advantage of the particle
swarm optimization (PSO) evolutionary algorithm to specifying
the score of each variable, and eventually the final condition of the
candidate. The acquired results of evaluating the fuzzy-expert
system proves its functionality. This system is also able to function
well in scoring similar educational cases to specify acceptance.