accurate prediction of municipal solid waste’s quality and quantity is crucial for designing and programming municipal solid waste management system. but predicting the amount of generated waste is difficult task because various parameters affect it and its fluctuation is high. in this research with application of feed forward artificial neural network, an appropriate model for predicting the...

Background and Objectives: Rheological characteristics of dough are important for achieving useful information about raw-material quality, dough behavior during mechanical handling, and textural characteristics of products. Our purpose in the present research is to apply soft computation tools for predicting the rheological properties of dough out of simple measurable factors. Materials and Me...

the method of artificial neural network is used as a suitable tool for intelligent interpretation of gravity data in this paper. we have designed a hopfield neural network to estimate the gravity source depth. the designed network was tested by both synthetic and real data. as real data, this artificial neural network was used to estimate the depth of a qanat (an underground channel) located at...

The creation process of Artificial Neural Networks (ANNs) used to be quite slow and the human expert had to test several architectures until finding the one that achieves the best results for the solution of a certain problem. This work presents a new technique that uses Genetic Programming (GP) for automatically creating ANNs. This technique also allows the obtaining of simplified networks wit...

background: the complexity of the fermentation processes is mainly due to the complex nature of the biological systems which follow the life in a non-linear manner. joined performance of artificial neural network (ann) and genetic algorithm (ga) in finding optimal solutions in experimentation has found to be superior compared to the statistical methods. range of applications of β-cyclodextrin (...

natural fire inflicting irreparable damage to rangelands and forest areas is cause changes in landscape ecology. the purpose of this research is comparison of artificial neural network (ann) and line regression (lr) models to predict of forest and rangelands fires to this end, the data consist fire burned area and fire were used weather data over a period of 7 years (2006-2012(.the result indic...

the moe and mor are controlled by production variables of particleboard process. now, the basic question is which of the particleboard variables is effective on bending strength property? 13 variables of internal scientific resources were measured with 100 repeats. the study steps include the following; liner regression or stepwise, genetic algorithm, and artificial neural network. the number o...

drought is random and nonlinear phenomenon and using linear stochastic models, nonlinear artificial neural network and hybrid models is advantaged for drought forecasting. this paper presents the performances of autoregressive integrated moving average (arima), direct multi-step neural network (dmsnn), recursive multi-step neural network (rmsnn), hybrid stochastic neural network of directive ap...