By S. H. Nasseri, Z. Alizadeh, B. Khabiri (auth.), Bing-Yuan Cao, Xiang-Jun Xie (eds.)

ISBN-10: 3642285910

ISBN-13: 9783642285912

ISBN-10: 3642285929

ISBN-13: 9783642285929

“Fuzzy Engineering and Operations examine” is the edited final result of the fifth foreign convention on Fuzzy details and Engineering (ICFIE2011) held in the course of Oct. 15-17, 2011 in Chengdu, China and through the first educational convention in institution of Guangdong Province Operations learn Society (GDORSC) hung on Oct. 20, 2011 in Guangzhou, China. The fifth ICFIE2011, equipped at the luck of prior meetings, and the GDORC, first held, are significant Symposiums, respectively, for scientists, engineers practitioners and Operation study (OR) researchers featuring their up-to-date effects, advancements and functions in all parts of fuzzy info and engineering and OR. It goals to reinforce kinfolk among study laboratories and universities, and to create a major symposium for international scientists in Fuzziology and OR fields. The ebook comprises sixty two papers and is split into 5 major components: “Fuzzy Optimization, good judgment and Information”, “The mathematical idea of Fuzzy Systems”, “Fuzzy Engineering purposes and delicate Computing Methods”, “OR and Fuzziology” and “Guess and Review”.

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**Example text**

Because of the traditional competitive learning algorithm which can deal with ordinary against crime data sets, against crime space spatial clustering sample characteristic data is often take interval-valued situation, we first establish crime interval-valued fuzzy neural network and its competition network structure as shown in Figure 1: input layer fuzzification layer output layer Fig. 1. Fuzzy competitive neural network structure The network consists of three layers, which the first layer for input layer,the input data for the pretreatment of the training sample of after a crime, input variables for X i , among (i = 1, , n) .

1. Corresponding to given a real number t, there is a trapezoidal fuzzy number t˜ such that Y2 (t˜) = t. Proof. To obtain a trapezoidal fuzzy number t˜, it is need to choose two arbitrary real number α and β such that α = β and then let aL = t − α2 and aU = t + α2 in (8). Thus, we have α α 1 α α−α α Y2 (t˜) = Y2 (t − , t + , α, α) = ) =t t− +t+ +( 2 2 2 2 2 2 Hence, for every real number t there is a trapezoidal fuzzy number as (t − α 2 , α, α). 1. Depending upon to need, one can also use a small α and β in the above theorem.

Liu property crime and economic crimes will still maintain high-risk situation. In the economic crisis conditions, not only the unemployment rise, but the crime rate. In human society, crime is very sensitive and complex social phenomenon. For many years the researchers studied from the angle of criminology, the formation mechanism and social crime control method, but the theoretical study always with real situation exists some bias,so it can not reflect social crime real situations, investigate its reason is the number of criminal dark existence.

### Fuzzy Engineering and Operations Research by S. H. Nasseri, Z. Alizadeh, B. Khabiri (auth.), Bing-Yuan Cao, Xiang-Jun Xie (eds.)

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