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Prediction of Soil Fractions (Sand, Silt and Clay) in Surface Layer Based on Natural Radionuclides Concentration in the Soil Using Adaptive Neuro Fuzzy Inference System
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作者 Saad Al-Hamed Mohamed Wahby +1 位作者 Mohamed Al-Sulaiman abdulwahed aboukarima 《Open Journal of Soil Science》 2014年第7期215-225,共11页
In this research, a gamma ray sensor (The Mole) was used to get the natural radionuclides concentration in situ in the surface layer of cultivated soils. For sand, silt and clay predictions, an adaptive neuro fuzzy in... In this research, a gamma ray sensor (The Mole) was used to get the natural radionuclides concentration in situ in the surface layer of cultivated soils. For sand, silt and clay predictions, an adaptive neuro fuzzy inference system (ANFIS) was performed to predict such fractions (Sugeno model). The inputs to the system were Potassium (40K), Uranium (238U), Thorium (232Th) and Cesium (137Cs) concentrations. It is concluded that ANFIS structure is acceptable in the prediction of sand, silt and clay considering the studied inputs. Test results and predicted outcomes were compared and acceptable correlations were obtained. 展开更多
关键词 AGRICULTURE ANFIS SOIL Texture Natural Radionuclides
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