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

• 作者: Abdulwahed Aboukarima Mohamed Al-Sulaiman Mohamed Wahby Saad Al-Hamed
• 来源期刊: 土壤科学期刊(英文)
• 学科: 医学
• 关键词: Agriculture ANFIS SOIL TEXTURE Natural Radionuclides
• 年，卷（期）: 2014,（7）
• 页码范围: 215-225
• 页数: 11页
• 分类号: R73

摘要

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.