gas hydrate formation in production and transmission pipelines and consequent plugging of these lines have been a major flow-assurance concern of the oil and gas industry for the last 75 years. gas hydrate formation rate is one of the most important topics related to the kinetics of the process of gas hydrate crystallization. the main purpose of this study is investigating phenomenon of gas hyd...

this paper investigates the forecasting gold coin futures contract price in iran mercantile exchange. this research has presented a hybrid model based on genetic fuzzy systems (gfs) and artificial neural network (ann) to forecast the gold futures contract, at first, we use stepwise regression analysis (sra) to determine factors which have most influence on stock prices. at the next stage we div...

improving time series forecastingaccuracy is an important yet often difficult task.both theoretical and empirical findings haveindicated that integration of several models is an effectiveway to improve predictive performance, especiallywhen the models in combination are quite different. in this paper,a model of the hybrid artificial neural networks andfuzzy model is proposed for time series for...

In this contribution a new supervised classification model is proposed, namely the Fuzzy Evolutionary Probabilistic Neural Network (FEPNN). The proposed model incorporates a fuzzy class membership function into the recently proposed Evolutionary Probabilistic Neural Network (EPNN). EPNN employs an evolutionary algorithm, namely the Particle Swarm Optimization (PSO), for the selection of the spr...

The jamor purpose of the present research is to predict the total stock market index of Tehran Stock Exchange, using a combined method of Wavelet transforms, Fuzzy genetics, and neural network in order to predict the active participations of finance market as well as macro decision makers.To do so, first the prediction was made by neural network, then a series of price index was decomposed by w...

the proposed iafc neural networks have both stability and plasticity because theyuse a control structure similar to that of the art-1(adaptive resonance theory) neural network.the unsupervised iafc neural network is the unsupervised neural network which uses the fuzzyleaky learning rule. this fuzzy leaky learning rule controls the updating amounts by fuzzymembership values. the supervised iafc ...

In this work, an artificial neural network (ANN) model along with a combination of adaptive neuro-fuzzy inference system (ANFIS) and particle swarm optimization (PSO) i.e. (PSO-ANFIS) are proposed for modeling and prediction of the propylene/propane adsorption under various conditions. Using these computational intelligence (CI) approaches, the input parameters such as adsorbent shape (S<su...

Modeling of stream flow–suspended sediment relationship is one of the most studied topics in hydrology due to itsessential application to water resources management. Recently, artificial intelligence has gained much popularity owing toits application in calibrating the nonlinear relationships inherent in the stream flow–suspended sediment relationship. Thisstudy made us of adaptive neuro-fuzzy ...

water quality assessment provides a scientific basis for water resources development and management. this case study proposes a factor analysis- hopfield neural network model (fhnn) based on factor analysis method and hopfield neural network method. the results showed that the factor analysis (fa) technique was introduced to identify important water quality parameters. results revealed that bio...