using artificial neural networks to estimate saturated hydraulic conductivity from easily available soil properties

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application of artificial neural networks in prediction of saturated hydraulic conductivity using soil physical parameters

soil hydraulic properties such as saturated and unsaturated hydraulic conductivity play an important role in environmental research. since direct measurement of these soil hydraulic properties is time-consuming and costly, indirect methods such as pedotransfer functions and artificial neural networks (ann) were developed based on readily available parameters. in this study, the use of ann to pr...

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An evaluation of genetic algorithm method compared to geostatistical and neural network methods to estimate saturated soil hydraulic conductivity using soil texture

ABSTRACT-Determining hydraulic conductivity of soil is difficult, expensive, and time-consuming. In this study, Algorithm Genetic and geostatistical analysis and Neural Networks method are used to estimate soil saturated hydraulic conductivity using the properties of particle size distribution. The data were gathered from 134soil profiles from soil and lander form studies of the Ardabil Agricul...

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مقایسه روش‌های شبکه عصبی مصنوعی و رگرسیونی برای پیش‌بینی هدایت هیدرولیکی اشباع خاک‌های استان خوزستان

Direct measurement of soil hydraulic characteristics is costly and time-consuming. Also, the method is partly unreliable due to soil heterogeneity and laboratory errors. Instead, soil hydraulic characteristics can be predicted using readily available data such as soil texture and bulk density using pedotransfer functions (PTFs). Artificial neural networks (ANNs) and statistical regression are t...

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Effect of pH on Saturated Hydraulic Conductivity and Soil Dispersion

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عنوان ژورنال:
مدیریت خاک و تولید پایدار

جلد ۲، شماره ۱، صفحات ۹۵-۱۱۰

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