in this paper, a recurrent fuzzy-neural network (rfnn) controller with neural network identifier in direct control model is designed to control the speed and exhaust temperature of the gas turbine in a combined cycle power plant. since the turbine operation in combined cycle unit is considered, speed and exhaust temperature of the gas turbine should be simultaneously controlled by fuel command ...

due to its critical impact and significant destructive nature during and after seismic events, soil liquefaction and liquefactioninduced lateral ground spreading have been increasingly important topics in the geotechnical earthquake engineering field during the past four decades. the aim of this research is to develop an empirical model for the assessment of liquefaction-induced lateral ground ...

background : in medical studies, when the joint prediction about occurrence of two events should be anticipated, a statistical bivariate model is used. due to the limitations of usual statistical models, other methods such as artificial neural network (ann) and hybrid models could be used. in this paper, we propose a hybrid artificial neural network-genetic algorithm (ann-ga) model to predictio...

no unique method has been so far specified for determining the number of neurons in hidden layers of multi-layer perceptron (mlp) neural networks used for prediction. the present research is intended to optimize the number of neurons using two meta-heuristic procedures namely genetic and hill climbing algorithms. the data used in the present research for prediction are consumption data of water...

Isotactic poly (1-butene), ipbu-1, was synthesized by using a metallocene catalyst. The thermodynamic phase behavior of polymer–organic solvents systems is very important in every polymer application.  In this paper, the solid–liquid equilibrium of ipbu-1 with different organic solvents (1-heptyne, cyclo octane) was studied by a mathematical model. By considering the experiments temperature...

In this paper, the theory and construction methods of four models are presented for predicting the vegetable market price, which are BP neural network model, the neural network model based on genetic algorithm, RBF neural network model and an integrated prediction model based on the three models above. The four models are used to predict the Lentinus edodes price for Beijing Xinfadi wholesale m...

Developing artificial neural network (ANN), a model to make a correct prediction of required force and torque in ring rolling process is developed for the first time. Moreover, an optimal state of process for specific range of input parameters is obtained using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) methods. Radii of main roll and mandrel, rotational speed of main roll, pr...

in this paper, a novel hybrid model based on neural network and game theory is proposed to support the analyzers in oil market. in this model, first the neural network is utilized to learn the oil prices associated with opec production level and usa imports level. then the learned neural network is applied by a game model. finally the nash equilibrium points of the game present the optimum deci...

injection molding is one of the most important and common plastic formation methods. combination of modeling tools and optimization algorithms can be used in order to determine optimum process conditions for the injection molding of a special part. because of the complication of the injection molding process and multiplicity of parameters and their interactive effects on one another, analytical...