comparison of k-nearest neighbor and artificial neural network methods for predicting cation exchange capacity of soil
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Comparison 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 کاملComparison of Artificial Neural Network and Multivariate Regression Methods in Prediction of Soil Cation Exchange Capacity
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 کاملIdentification of selected monogeneans using image processing, artificial neural network and K-nearest neighbor
Abstract Over the last two decades, improvements in developing computational tools made significant contributions to the classification of biological specimens` images to their correspondence species. These days, identification of biological species is much easier for taxonomist and even non-taxonomists due to the development of automated computer techniques and systems. In this study, we d...
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 کاملcomparison of artificial neural network and regressionpedotransfer functions models for prediction of soil cation exchange capacity in chaharmahal - bakhtiari province
abstract cation exchange capacity (cec) is an important characteristic of soil in terms of nutrient and water holding capacities and contamination management. measurement of cec is laborious and time-consuming. therefore, cec estimation through other easily - measured properties is desirable. in this study, ptfs for estimation of cation exchange capacity from basic soil properties such as parti...
متن کاملscour modeling piles of kambuzia industrial city bridge using hec-ras and artificial neural network
today, scouring is one of the important topics in the river and coastal engineering so that the most destruction in the bridges is occurred due to this phenomenon. whereas the bridges are assumed as the most important connecting structures in the communications roads in the country and their importance is doubled while floodwater, thus exact design and maintenance thereof is very crucial. f...
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مدیریت خاک و تولید پایدارجلد ۳، شماره ۱، صفحات ۷۷-۹۴
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