چکیده مقاله
To achieve the high performance system without any failure, we should provide the high reliability level of software Soft computing models for software reliability prediction sufferfrom low accuracy during predicting the number of faults Moreover, the models have some problems like no solid mathematical foundation for analysis, being trapped in local minima,and convergence problem This paper introduces Imperialist Competitive Algorithm ICA to overcome the weaknesses of previous models and improve the efficiency of training process of Multi Layer Perceptron MLP neural network Therefore, the network canpredict the number of faults precisely The results show that the proposed predicting model is more efficient than the existing techniques in prediction performance
کلیدواژهها
نویسندگان
Shirin Noekhah
Soft Computing Research Group SCRG , University Technology Malaysia,Johor, Malaysia
Ali Akbar Hozhabri
Department of Management, Faculty of Management and Human Resource Development, FPPSM
Hamideh Salimian Rizi
University of Isfahan, Iran
شیوه ارجاع
Noekhah, Shirin and Hozhabri, Ali Akbar and Salimian Rizi, Hamideh,1392,Software Reliability Prediction Model Based On Ica Algorithm and Mlp Neural Network,7th International Conference on e- Commerce whit focus on e-Security,Kish Island
ارائهشده در
مجموعه مقالات هفتمین کنفرانس بین المللی تجارت الکترونیک در کشورهای در حال توسعه با رویکرد بر امنیت ECDC201328 فروردین 1392 · جزیره کیش