Evaluation Method of Public Transportation System Based on Fuzzy Cloud Model

Abstract

This article describes how the public traffic system evaluation is an important measure to strengthen the management of urban transportation. Many scholars have evaluated the public transportation system, but lack research on different index weights of it. In past models, although the fuzzy assessment method was integrated into an evaluation methodology, its randomness was reflected unclearly. To solve the problems, a fuzzy evaluation of a cloud model is researched. Firstly, the corresponding weights of all indexes are calculated by analytic hierarchy process (AHP) and a clustering method. Then, the principal component of the indexes is extracted by the principal component analysis. According to the distribution of a principal component and processed with the cloud model, a subordinate degree function was established. Finally, scoring cities by combining the principal component weight and membership cloud matrix and evaluating the public transportation system. Comparing the matter-element analysis and the AHP gray model method, this proposed model in this article can evaluate the performance of different urban traffic systems more practically.

Intelligent task planner for cloud robotics using level of attention empowered with fuzzy system

“…Selective attention will assist robot to get rid of this situation by limiting the workload through selective filtering on perceived input [2]. The attention mechanism in the hierarchical system will enable robots to regulate attention by gathering information from its surroundings by interacting with other robots of the same or different layers of the cloud computing [3,4].…”