Xiaoping Qiu

A new fuzzy clustering method based on distance and density

Fuzzy clustering is capable of finding vague boundaries, but its time complexity is usually high, and the need to specify complicated parameters hinders its use. Here, a new fuzzy clustering method based on distance and density (FCDD) is proposed, which automatically identifies the cluster number. It calculates the density and density set of each data point and selects any data point at the beginning of the FCDD algorithm. Next it judges whether every element in the chosen data points density set is in the same cluster with itself. This process is repeated until all data points has been chosen. The method does not require finding the cluster center and density values are calculated only once. It requires two parameters that are easy to specify and is able to find the natural clusters in the data. In order to find the optimum values of the parameters with respect to the specified number of the cluster, we construct a target function using entropy. Cluster analysis of the two methods has been performed on several data sets and the experimental results show that a high recognition rate can be achieved.

The identification of fuzzy weighted classification system incorporated with Fuzzy Naive Bayes from data

We present an effective approach for identifying the rule base, the weight of each proposition and the certainty factor of each rule in the fuzzy weighted classification system. Here we use the idea of Fuzzy Naive Bayes, and assume variables in antecedents are conditional independent given corresponding consequents. So the weight of each proposition in the antecedent can be computed out via the conditional probability of the corresponding consequent given this proposition in the antecedent, and the certainty factor of each rule can also be computed out via the conditional probability of the consequent in this rule given the corresponding antecedent. The final rule base consists of all fuzzy rules whose certainty factors are large enough. Using this approach we can get a concise and consistent fuzzy system. Before computing all kinds of weights according to the proposed method, an optimal fuzzy partition is achieved by using fuzzy clustering, for instance, fuzzy c-means or similar cluster method. Finally we evaluate our identification method using Fisher iris data and Diabetes data, the tests show that a high recognition rate can be achieved.

Executive validation analysis of workflow process

In the workflow management system, the process definition is finished by the process definition tools and explained and enacted by the workflow enactment service. The method in which the application logic and the process logic are separated improves the reuse rate of the software and the efficiency of the system by modifying the process model rather than the material functions. We adopt the practicable automated reasoning method to analyze the executive validation after the workflow process defined in this paper. The method includes two steps. In the first step, the basic relations between the activities in the workflow process is discussed, and then the transformation rules from the workflow process to a clause set is given. The automated reasoning based on path searching is proposed for judging the satisfiability of the clause set and finding out the executive validation of the workflow process in the second step. Experimental results show that this method is effective for WfMS.

Multilayered fuzzy clustering method based on distance and density

In this paper, a multilayered fuzzy clustering method based on distance and density (MFCDD) is proposed. The first layers algorithm deals with the original data points, the upper with the cluster centers of the contiguous lower layer. In each layer it identifies the cluster number automatically. It calculates the density and density set of each data point based on distance matrix; then chooses one data point randomly and judges whether every element in the selected data points density set is in the same cluster with itself, this process is repeated till all data points have been selected. In order to find the optimum value of the parameters, we adopt an objective function using entropy on the upmost layer. Clustering analysis of MFCDD has been performed and the experimental results show that a high recognition rate can be achieved.

An automated reasoning method used in workflow management system

In the workflow management system, the process definition is finished by the process definition tools and explained and enacted by the workflow enactment service. The method that the application logic and the process logic are separated improves the reuse rate of the software and the efficiency of the system by modifying the process model rather than the material functions. We propose an automated reasoning method to validate the process definition in this paper. The method includes two steps. In the first step, the typical relationship between the activities is discussed, and then the transformation rules from the relevant activities to a clause set is given; the automated reasoning based on path searching is proposed for judging the satisfiability of the clause set and finding out the validation of the process definition in the second step. Experimental results show that this method is effective for WfMS.

Adding forecast support to workflow management system by classical logic formula computing

Workflow technology is a new hotspot in the area of computer application after the 1990s. In order to improve the performance of workflow management system (WfMS), a dynamic neural network based on classical formula computing is proposed to add forecast support to it. On the basis of the requirement of WfMS, neural unit, generation algorithm and computing algorithm for classical logic formula computing are discussed in detail and the experiment results show that this method is effective and universal.

The hierarchical fuzzy evaluation system and its application

The hierarchical fuzzy evaluation system (HFES) and its application in intelligent workflow management system (IWfMS) are discussed in this paper. First, the definition of HFES is discussed, including the definitions of the evaluation items and the relationships among them, based on the five common operations. Second, the running algorithms of the HFES are introduced to compute the values of those evaluation items and the result of the HFES. Subsequently, the application of the HFES in the IWfMS is presented in detail including the cooperating model. The experiments are carried out and the results show that the HFES is effective.

Resolution principle based on six lattice-valued proposition logic LP/sub 6/(X)

Resolution-based automated reasoning theory is an important and active research field in artificial intelligence. It is used to judge the satisfiability of any logic formula. With the development of classical and non-classical logic, the resolution theory and method based on different logic system has been discussed widely and deeply. In the present paper, a new resolution principle by using ultrafilter in LP/sub 6/(X) is put forward. Different from existed method of resolution, this resolution in this paper is based on ultrafilter of lattice implication algebra. Because of LP/sub 6/(X) is a non-chain, non-boolean and non-well-ordered algebra structure, resolution based on LP/sub 6/(X) can be the theoretical foundation of resolution on lattice-valued truth-field. Accordingly, the research in this paper is helpful supported for the application of intelligent reasoning system based on lattice-valued logic.

Workflow model of intelligent office information system

The intelligent office information system (abbr. IOIS) becomes very necessary with the development of the information society for the peoples progressive requirements such as more convenience and high performance. In this paper, the main frame of IOIS is constructed fully based on the existing workflow technology. Firstly, several main models, which are corresponding to the different aspects of IOIS, are analyzed separately, including the function model, the process model, the source model, the organization model and the information model. Then the workflow model of IOIS is formed based on those models and establishes the indispensable foundation in theory for the further development of IOIS.

A new special-domain and stepwise intelligent development method in software engineering

Based on the many achievements and experiences in artificial intelligence and software engineering about program design automation, a new special-domain and stepwise intelligent development method is proposed in this paper. Referencing to the lifecycle method and the prototype method, the intelligent developments of detail design, outline design, and requirement analysis are discussed in detail successively. Then, the relations among those three intelligent development steps are explained clearly. Finally, the characteristics and the advantages of this method are analyzed in depth, which shows that it is a feasible way for developing intelligent information system.