comparison of neuro-fuzzy, artificial neural network and multivariate regression for prediction energy consumption in the country
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The efficiency of Artificial Neural Network, Neuro-Fuzzy and Multivariate Regression models for runoff and erosion simulation using rainfall simulator
1- INTRODUCTION According to the complexity of environmental factors related to erosion and runoff, correct simulation of these variables find importance under rain intensity domain of watershed areas. Although modeling of erosion and runoff by Artificial Neural Network and Neuro-Fuzzy based on rainfall-runoff and discharge-sediment models were widely applied by researchers, scrutinizing Arti...
متن کاملComparison of artificial neural network and multivariate regression methods in prediction of soil cation exchange capacity (Case study: Ziaran region)
Investigation of soil properties like Cation Exchange Capacity (CEC) plays important roles in study of environmental reaserches as the spatial and temporal variability of this property have been led to development of indirect methods in estimation of this soil characteristic. Pedotransfer functions (PTFs) provide an alternative by estimating soil parameters from more readily available soil data...
متن کاملa comparison of neuro-fuzzy, artificial neural network and multivariate regression for prediction of some soil properties (case study: golestan province)
realizing the difficulties involved in direct measurement of soil properties, in recent years, alternative methods have been employed. in the present research, soil texture, organic carbon, saturation percentage and lime as readily measurable parameters, wilting point, field capacity, cation exchange capacity as well as bulk density, as predicted variables were evaluated. the data set was then ...
متن کاملPrediction of Thermal performance nanofluid Al2O3 by Artificial Neural Network and Adaptive Neuro-Fuzzy Inference Systemt
In recent years, the use of modeling methods that directly utilize empirical data is increasing due to the high accuracy in predicting the results of the process, rather than statistical methods. In this paper, the ability of Artificial Neural Network (ANN) and Adaptive Fuzzy-Neural Inference System (ANFIS) models in the prediction of the thermal performance of Al2O3 nanofluid that is measured ...
متن کاملcomparison of neuro-fuzzy, genetic algorithm, artificial neural network and multivariate regression for prediction of soil salinity (case study: ardakan city)
in recent years, alternative methods have been used for estimation of soil salinity. therefore, at present research, 600 soil samples collected from ardakan in central iran. then em38 and terrain parameters such as wetness index, land index and curvature as readily measured properties and soil salinity (0-30 and 0-100) as predicted variables were measured. after that, the data set was divided i...
متن کاملAn Artificial Neural Network Model for Prediction of the Operational Parameters of Centrifugal Compressors: An Alternative Comparison Method for Regression
Nowadays, centrifugal compressors are commonly used in the oil and gas industry, particularly in the energy transmission facilities just like a gas pipeline stations. Therefore, these machines with different operational circumstances and thermodynamic characteristics are to be exploited according to the operational necessities. Generally, the most important operational parameters of a gas pipel...
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پژوهشنامه اقتصادیجلد ۱۲، شماره ۴۶، صفحات ۴۳-۶۴
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