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With the rapid development of industrialization and urbanization, crime prevention issues become serious in China each day. Many cities have established a number of crime prevention systems in order to maintain social stability. However, crime prevention system is a complex system, which is controlled by a number of interrelated factors and is difficult to estimate. To overcome the obstacles of conventional effectiveness evaluation for crime prevention system, this paper proposed an effectiveness evaluation method for crime prevention system which combined the advantages of the analytic hierarchy process (AHP) and a grey clustering method to guarantee the accuracy and objectivity of weight coefficients. After constructing an index system of crime prevention system effectiveness evaluation based on correlated factors, we calculated the weight of every index with AHP and gave an evaluation result by means of a grey clustering method. A case study was given to validate the design of the underlying grey analytic hierarchy process model. Results show the feasibility and reliability of the model, which will be helpful to realize the quantitative analysis in crime prevention system effectiveness evaluation and provide a decision support tool for decision makers.

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Abstract. As a very efficient tool, π calculus could do modeling and make evaluations effectively particularly by targeting the features of concurrency and mobility which quite commonly exist in the software system nowadays. After a brief introduction of π comparison, this paper mainly discusses a comparison algorithm based on π comparison which is frequently used in the software modeling. As the ways of data storage mainly concern about random storage of elements and linked list storage of elements, this paper analyzes the algorithm of comparing any two elements in both ways. Particularly, the efficiency analysis is carried on to the element comparing algorithm in the linked list storage, which is relatively complicated, finding that the designed algorithm in this paper is greatly improved not only in algorithm simplification but also in working efficiency.

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