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⛄ 内容介绍
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 specifyingthe score of each variable, and eventually the final condition of thecandidate. 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.
⛄ 部分代码
%Plot the whole view
plotfis(pso);
%Plot each mf(input/output)
figure
[x,mf] = plotmf(pso,'input',1);
subplot(5,1,1), plot(x,mf);
xlabel('Membership Functions for Ex-uni Length');
[x,mf] = plotmf(pso,'input',2);
subplot(5,1,2), plot(x,mf);
xlabel('Membership Functions for Ex-uni Average');
[x,mf] = plotmf(pso,'input',3);
subplot(5,1,3), plot(x,mf);
xlabel('Membership Functions for Olympiad Chosen');
[x,mf] = plotmf(pso,'input',4);
subplot(5,1,4), plot(x,mf);
xlabel('Membership Functions for Ex-Uni Quality');
[x,mf] = plotmf(pso,'input',5);
subplot(5,1,5), plot(x,mf);
xlabel('Membership Functions for IELTS');
figure
[x,mf] = plotmf(pso,'input',6);
subplot(5,1,1), plot(x,mf);
xlabel('Membership Functions for Papers');
[x,mf] = plotmf(pso,'input',7);
subplot(5,1,2), plot(x,mf);
xlabel('Membership Functions for Festival Chosen');
[x,mf] = plotmf(pso,'input',8);
subplot(5,1,3), plot(x,mf);
xlabel('Membership Functions for Compilation,Translation,Invention');
[x,mf] = plotmf(pso,'input',9);
subplot(5,1,4), plot(x,mf);
xlabel('Membership Functions for Msc Thesis Quality');
[x,mf] = plotmf(pso,'input',10);
subplot(5,1,5), plot(x,mf);
xlabel('Membership Functions for Interviews Test');
figure
[x,mf] = plotmf(pso,'output',1);
subplot(2,1,1), plot(x,mf);
xlabel('Membership Functions for Qualification(output)');
⛄ 运行结果
⛄ 参考文献
Mousavi, Seyed Muhammad Hossein, et al. "A PSO fuzzy-expert system: As an assistant for specifying the acceptance by NOET measures, at PH. D level." 2017 Artificial Intelligence and Signal Processing Conference (AISP). IEEE, 2017.
