Due to improvement of Internet, employing web services is developed. By utilizing web services, distributed applications can exchange information. Trust is a main criterion to choose the proper web service as web services selection is a main issue which is still absorbing researchers to conduct research works on this field and analyze it. Due to the significant of this problem, neuro-fuzzy system is used to optimize the trust of single web services. Eight factors such as QoS, user preferences, subjective perspectives, objective perspectives, credibility of raters, bootstrapping, dynamic computing of trust and independency are considered in the considered neuro-fuzzy system. To achieve a trust optimization, 8 membership function various neuro-fuzzy systems are considered in this paper. Ultimately, the obtained results illustrates that the root mean square error, the precision amount, the recall amount and the F score amount of the neuro-fuzzy system is: 0.0873 %, 0.986, 0.988 and 0.987. تفاصيل المقالة

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. تفاصيل المقالة

Abstract: Due to improvement of Internet, employing web services is developed. By utilizing web services, distributed applications can exchange information. Trust is a main criterion to choose the proper web service as web services selection is a main issue which is still absorbing researchers to conduct research works on this field and analyze it. Due to the significant of this problem, neuro-fuzzy system is used to optimize the trust of single web services. Eight factors such as QoS, user preferences, subjective perspectives, objective perspectives, credibility of raters, bootstrapping, dynamic computing of trust and independency are considered in the considered neuro-fuzzy system. To achieve a trust optimization, 8 membership function various neuro-fuzzy systems are considered in this paper. Ultimately, the obtained results illustrates that the root mean square error, the precision amount, the recall amount and the F score amount of the neuro-fuzzy system is: 0.0873 %, 0.986, 0.988 and 0.987 تفاصيل المقالة