estimation (forecasting) of industrial production costs is one of the most important factor affecting decisions in the highly competitive markets. thus, accuracy of the estimation is highly desirable. hibrid regression neural network is an approach proposed in this paper to obtain better fitness in comparison with regression analysis and the neural network methods. comparing the estimated resul...

the purpose of this study is to investigate the accuracy of predictions of aniline removal efficiency in a moving bed biofilm reactor (mbbr) by various methods, namely by rbf, anfis, and fuzzy regression analysis. the reactor was operated in an aerobic batch and was filled by light expanded clay aggregate (leca) as a carrier for the treatment of aniline synthetic wastewater. exploratory data an...

gully erosion is one of the most severe types of water erosion that inclusive and global model to represent its development under different environmental circumstances is difficult. moreover, having knowledge about history behaviors of a gully and its advancement requires direct annual monitoring that is not possible in iran conditions because of cost and time. gis and remote sensing with provi...

the purpose of research was analysis of innovation management in processing and complementary industriesof livestock products. the method of research was correlative descriptive. the statistical population of this study was all managers in processing and complementary industriesof livestock products of khouzestan province (n=486). the sampling method was stratified random sampling. the sample s...

in this study, several artificial neural networks (anns) were developed to estimate seed and grain corn yields in parsabad moghan, iran. the data was collected by a face-to-face interview method from 144 corn farms during 2011. the energy ratios for seed and grain corns were calculated as 0.89 and 2.65, respectively. several multilayer perceptron anns with six neurons in the input layer and one...

NCSU, Princeton University, and UC-Davis Abstract: Functional linear regression analysis aims to model regression relations which include a functional predictor. The analogue to the regression parameter vector or matrix in conventional multivariate or multiple-response linear regression models is a regression parameter function in one or two arguments. If in addition one has scalar predictors, ...