An Optimal Configuration of Neural Networks by Multi-Objective Genetic Algorithm and Ensemble-Classifier Approach for Evaluation Trust in the Single Web Service

Journal of Advances in Computer Research

دوره 11، شماره 2 - شماره پیاپی 40، مرداد 2020، صفحه 105-119   

نوع مقاله: Original Manuscript

نویسندگان

baharak shakeri aski¹؛ Abolfazl Toroghi Haghighat^{* 2}؛ mehran mohsenzadeh¹

¹Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran

²Department of Computer, and IT Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran

چکیده

Abstract. Web Services provides a solution to web application integration. Due to the significant of trust to choose the proper web service, a novel optimal configuration of neural networks by multi-objective genetic algorithm and ensemble-classifier approach is used to evaluate the trust of single web services. For evaluating trust in single web services, first, a set of neural networks were trained by the settings their parameters through the multi-objective genetic algorithm. Next, the best combination of neural networks was selected to make an ensemble classifier. This method was evaluated with single WS dataset considered eight criteria. Three measurements such as accuracy, time and ROC curve were considered to assess the efficiency. Ultimately, the obtained results show that the proposed approach can achieve a trade-off between time and accuracy by the multi-objective genetic algorithm. Also using ensemble-classifiers approach increases the reliability of the model. Consequently, the proposed method promote the detection accuracy.

کلیدواژه‌ها

web service؛ Trust؛ Artificial Neural network؛ Multi-Objective Genetic Algorithm؛ Ensemble-Classifier