Fuzzy c-means text clustering based on topic concept sub-space

To improve the accuracy of text clustering, fuzzy c-means clustering based on topic concept sub-space （TCS2FCM） is introduced for classifying texts. Five evaluation functions are combined to extract key phrases. Concept phrases, as well as the descriptions of final clusters, are presented using WordNet origin from key phrases. Initial centers and membership matrix are the most important factors affecting clustering performance. Orthogonal concept topic sub-spaces are built with the topic concept phrases representing topics of the texts and the initialization of centers and the membership matrix depend on the concept vectors in sub-spaces. The results show that, different from random initialization of traditional fuzzy c-means clustering, the initialization related to text content contributions can improve clustering precision.

B-vex Fuzzy Mappings and Its Application to Fuzzy Optimization Problems

The concept of b-vex and logarithmic b-vex for fuzzy mappings are introduced by relaxing the definition of convexity of a fuzzy mapping. Most of the basic properties of b-vex fuzzy mapping are discussed and established for the nondifferentiable case. Necessary and sufficient conditions for b-vex fuzzy mapping are presented. Sevaral important results are given for nonlinear fuzzy optimization problems assuming that the objective and constraint functions are b-vex fuzzy mappings.

Comprehensive Evaluation Model of Reservoir Operation Based on Improved Set Pair Analysis

A comprehensive evaluation model based on improved set pair analysis is established. Considering the complexity in decision-making process, the model combines the certainties and uncertainties in the schemes, i.e., identical degree, different degree and opposite degree. The relations among different schemes are studied, and the traditional way of solving uncertainty problem is improved. By using the gray correlation to determine the difference degree, the problem of less evaluation indexes and inapparent linear relationship is solved. The difference between the evaluation parameters is smaller in both the fuzzy comprehensive evaluation model and fuzzy matter-element method, and the dipartite degree of the evaluation result is unobvious. However, the difference between each integrated connection degree is distinct in the improved set pair analysis. Results show that the proposed method is feasible and it obtains better effects than the fuzzy comprehensive evaluation method and fuzzy matter-element method.

Research on the Recognition Method of Electric Energy Meter Lead Title based on the Fuzzy Image Processing

This article puts forward an automatic recognition algorithm of electric energy meter lead seals： firstly, the image will be histogram equalization, smoothing, binaryzation pretreatment, then according to the image characteristics of text changes, the system can quickly and accurately segment image from complex background, finally the system extract different dimension and the feature of English and Arabia using digital projection transform coefficient method and to identify the corresponding number by BP neural network, solves the problem of automatic recognition of electric energy meter lead sealing.

An Intelligent System for a Resource Allocation Problem Based on Fuzzy Reasoning

The development of the assistive abilities regarding the decision-making process o fan Intelligent Control System （ICS） like a fuzzy expert system implies the development of its functionality and its ability of specification. Fuzzy expert systems can model fuzzy controllers, i.e., the knowledge representation and the abilities of making decisions corresponding to fuzzy expert systems are much more complicated that in the case of standard fuzzy controllers. The expert system acts also as a supervisor, creating meta-level reasoning on a set of fuzzy controllers, in order to choose the best one for the management of the process. Knowledge Management Systems （KMSs） is a new development paradigm of Intelligent Systems which has resulted from a synergy between fuzzy sets, artificial neural networks, evolutionary computation, machine learning, etc., broadening computer science, physics, economics, engineering, mathematics. This paper presents, after a synergic new paradigm of intelligent systems, as a practical case study the fuzzy and temporal properties of knowledge formalism embedded in an ICS. We are not dealing high with level reasoning methods, because we think that real-time problems can only be solved by rather low-level reasoning. Solving the match-time predictability problem would allow us to build much more powerful reasoning techniques.

Similarity measure design on overlapped and non-overlapped data

Similarity measure design on non-overlapped data was carried out and compared with the case of overlapped data.Unconsistant feature of similarity on overlapped data to non-overlapped data was provided by example.By the artificial data illustration,it was proved that the conventional similarity measure was not proper to calculate the similarity measure of the non-overlapped case.To overcome the unbalance problem,similarity measure on non-overlapped data was obtained by considering neighbor information.Hence,different approaches to design similarity measure were proposed and proved by consideration of neighbor information.With the example of artificial data,similarity measure calculation was carried out.Similarity measure extension to intuitionistic fuzzy sets(IFSs)containing uncertainty named hesitance was also followed.

Minimizing Tardy Jobs in a Single Machine Scheduling Problem with Fuzzy Processing Times and Due Dates

The optimality of a fuzzy logic alternative to the usual treatment of uncertainties in a scheduling system using fuzzy numbers is examined formally. Processing times and due dates are fuzzified and presented by fuzzy numbers. With introducing the necessity measure, we compare fuzzy completion times of jobs with fuzzy due dates to decide whether jobs are tardy. The object is to minimize the numbers of tardy jobs. The efficient solution method for this problem is proposed. And deterministic counterpart of this single machine scheduling problem is a special case of fuzzy version.

Optimization Model on Quadratic Programming Problem with Fuzzy

In this paper, the authors propose a computational procedure by using fuzzy approach to fred the optimal solution of quadratic programming problems. The authors divide the calculation of the optimal solution into two stages. In the first stage the authors determine the unconstrained minimization and check its feasibility. The second stage, the authors explore the feasible region from initial point to another point until the authors get the optimal point by using Lagrange multiplier. A numerical example is included to support as illustration of the paper.

Site selection of emergency material warehouse under fuzzy environment

The objective of this work was to determine the location of emergency material warehouses. For the site selection problem of emergency material warehouses, the triangular fuzzy numbers are respectively demand of the demand node, the distance between the warehouse and demand node and the cost of the warehouse, a bi-objective programming model was established with minimum total cost of the system and minimum distance between the selected emergency material warehouses and the demand node. Using the theories of fuzzy numbers, the fuzzy programming model was transformed into a determinate bi-objective mixed integer programming model and a heuristic algorithm for this model was designed. Then, the algorithm was proven to be feasible and effective through a numerical example. Analysis results show that the location of emergency material warehouse depends heavily on the values of degree a and weight wl. Accurate information of a certain emergency activity should be collected before making the decision.

Existence and Uniqueness Theorem for the Cauchy Problem of Fuzzy Differential Equations under Non-Lipschitz Conditions

Solutions of fuzzy differential equations provide a noteworthy example of time-dependent fuzzy sets The purpose of this paper is to introduce functions of a suitable Lyapunov-like type and to show the existence and uniqueness theorem for the Cauchy problem of fuzzy differential equations under non-Lipschitz conditions The comparison principles and the existence and uniqueness theorems of this paper generalize many well-known results up to now

Fuzzy adaptive genetic algorithm based on auto-regulating fuzzy rules

There are defects such as the low convergence rate and premature phenomenon on the performance of simple genetic algorithms （SGA） as the values of crossover probability （Pc） and mutation probability （Pro） are fixed. To solve the problems, the fuzzy control method and the genetic algorithms were systematically integrated to create a kind of improved fuzzy adaptive genetic algorithm （FAGA） based on the auto-regulating fuzzy rules （ARFR-FAGA）. By using the fuzzy control method, the values of Pc and Pm were adjusted according to the evolutional process, and the fuzzy rules were optimized by another genetic algorithm. Experimental results in solving the function optimization problems demonstrate that the convergence rate and solution quality of ARFR-FAGA exceed those of SGA, AGA and fuzzy adaptive genetic algorithm based on expertise （EFAGA） obviously in the global search.