انجمن کامپیوتر ایران

In this paper, a novel inference engine named fuzzyevidential hybrid engine has been proposed using Dempster-Shafer theory of evidence and fuzzy sets theory. This hybrid engine operates in two phases. In the first phase, it models the input information’s vagueness through fuzzy sets. In following, extracting the fuzzy rule set for the problem, it applies the fuzzy inference rules on the acquired fuzzy sets to produce the first phase results. At second phase, the acquired results of previous stage are assumed as basic beliefs for the problem propositions and in this way, the belief and plausibility functions (or the belief interval) are set. Gathering information from different sources, they provide us with diverse basic beliefs which should be fused to produce an integrative result. For this purpose, evidential combination rules are used to perform the information fusion. Having applied the proposed engine on the coronary heart disease (CHD) risk assessment, it has yielded 86 percent accuracy rate in the CHD risk prediction.

This paper, proposes the use of a reinforcement learning approach for a target tracking sensor network application. Harsh and unpredictable situations of sensor nodes in such an application requires a selftuning mechanism for the nodes to adapt their behavior over time. The method is examined under high dynamic network conditions and compared with a similar method called SORA over different performance measures. The results show a significant improvement over the compared method in the environments with high level of dynamism.

Due to the changing and dynamic environment of web services, Quality of Service (QoS) becomes a key factor to differentiate service providers. Since current web service standards and technologies suffer from the lack of QoS Management, having architectures capable of supporting QoS verification, selection, negotiation and monitoring is inevitable. Software agents have been recognized as a promising technology for managing web services. Using FIPA compliant Multi Agents we were able to propose a Multi Agents based web service QoS Management Architecture. We also introduced a QoS based web service clustering method which helps us to select the best service that suits user quality preferences.