Multi-agent Blind Model and Its Application to Regional Eco-environmental Quality Assessment

1 Introduction Eco-environmental quality assessment is an activity that is affected by man-made factors. As other environmental systems, regional eco-environment is also a complicated and uncertain system (Wu et al., 2005). Owing to these reasons, people may produce a style of subjective un- certainty in mind in evaluating such system (Liu et al. 1999a; Wu et al., 2004). According to unascertained mathematics (Liu et al., 1997; Liu et al., 1999b), we know that this kind of subjective uncerta…

Multi-agent blind model and its application to regional eco-environmental quality assessment

Through denoting each expert as an agent and viewing a multiple criteria decision-making as a synthesis problem of aggregating experts’ ratings, a multi-agent blind model (MABM) is developed for regional eco-environmental quality assessment. In this model, the ratings of the evaluated object under an index, given by expert group, are first utilized to construct a series of blind numbers. In general, each index will correspond to different blind numbers. On the basis of aggregating index weights, the rank score in the form of a blind number is obtained for the evaluated object. Then, by means of calculating expected value of the above blind number, its rank score is further converted into a crisp value. By way of comparing the expected value with classification standards, eco-environmental quality of the evaluated sample could be identified successfully in the end. As a case, the MABM is used to evaluate the eco-environmental quality of Chaohu Lake basin. Study result shows that the MABM is a useful model for regional eco-environmental quality assessment. Foundation item: Under the auspices of the Natural Science Foundation of Anhui Province (No. 050450303) Biography: LI Ruzhong (1970–), male, a native of Huaiyuan of Anhui Province, post-doctor, associate professor, specialized in water environmental protection and eco-environmental quality assessment.