In this paper, evolutionary fuzzy systems are discussed in which the membership function shapes and types and the fuzzy rule set including the number of rules inside it are evolved using a genetic (evolutionary) algorithm. In addition, the genetic parameters (operators) of the evolutionary algorithm are adapted via a fuzzy system. Benefits of the methodology are illustrated in the process of cl...

This paper presents a new filtering approach based on fuzzy-logic which has high performance in mixed noise environments. This filter is mainly based on the idea that each pixel is not allowed to be uniformly fired by each of the fuzzy rules. In the proposed filtering algorithm, the rule membership functions are tuned iteratively in order to preserve the image edges. Several test experiments we...

Recently Web mining has become a hot research topic, which combines two of the prominent research areas comprising of data mining and the World Wide Web (WWW) [8]. Web usage mining attempts to discover useful knowledge from the secondary data obtained from the interactions of the users with the Web. Web usage mining has become very critical for effective Web site management, business and suppor...

Soft computing is a part of an artificial intelligence, and fuzzy logic is the study of fuzziness on data. The combination of these two techniques can provide an intelligent system with more ability and flexibility. The nature of data in the stock/capital market is more complex and challenging to predict the movement of the price of the stock. The study has combined both fuzzy c-means and neura...

Recently Web mining has become a hot research topic, which combines two of the prominent research areas comprising of data mining and the World Wide Web (WWW). Web usage mining attempts to discover useful knowledge from the secondary data obtained from the interactions of the users with the Web. Web usage mining has become very critical for effective Web site management, business and support se...

Genetic fuzzy rule selection is a two-phase classification rule mining method. First a large number of candidate fuzzy rules are generated by an association rule mining technique. Then only a small number of generated rules are selected by a genetic algorithm. We have already proposed an idea of parallel distributed implementation of genetic fuzzy rule selection. In this paper, we examine its c...

Intuitionistic fuzzy sets introduced by Atanassov are generalization of fuzzy sets as they also handle the nondeterminacy which is caused by degree of hesitation of decision maker. The present study proposes a computational method of forecasting for fuzzy time series. In the proposed method the notion of intuitionistic fuzzy set is used in fuzzy time series forecasting with simplified computati...

the purpose of this research is to detect manipulation of stock prices in tehran stock exchange that it has been done through hybrid genetic algorithm-artificial neural network (ann-ga) model and the simplified quadratic discriminant function (sqdf) model. in this study, the variables of price, trading volume and free float stock to match the results of the model and the actual data of price ma...

Blind source separation technique separates mixed signals blindly without any information on the mixing system. In this paper, we have used two evolutionary algorithms, namely, genetic algorithm and particle swarm optimization for blind source separation. In these techniques a novel fitness function that is based on the mutual information and high order statistics is proposed. In order to evalu...

With the characteristics of nonlinearity and randomness, stock prices change with a strong feature of disorder, and its mathematical model is often complex which makes it difficult to accurately determine the price or contain chaos. One single forecast method can only describe the stock price information partially, but fails to reflect the overall picture. In this paper, a method of Radial Basi...