کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
11031678 | 1645939 | 2019 | 7 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Using a posterior probability support vector machine model to assess soil quality in Taiyuan, China
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی انرژی
انرژی های تجدید پذیر، توسعه پایدار و محیط زیست
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Using a posterior probability support vector machine model to assess soil quality in Taiyuan, China Using a posterior probability support vector machine model to assess soil quality in Taiyuan, China](/preview/png/11031678.png)
چکیده انگلیسی
Soil quality is a significant but complicated issue. To more reliably and objectively assess this issue, we used a posterior probability support vector machine model (SVM), a method with fuzzy characteristics and robustness, to assign soil a quality grade based on concentrations of potentially toxic elements (PTEs) and fertilizers. To demonstrate this comprehensive assessment method, we analyzed soil quality in Taiyuan, Shanxi, China. The results indicated that 52.6% of the soil samples were grade I (good quality) and 70.3% of the soil samples were grade II (medium quality). We also used principal component analysis (PCA) to indirectly infer causes of the spatial distribution of differing soil qualities based on previous studies and to validate this model. The spatial distribution of soil quality in Taiyuan was mainly influenced by industrial and vehicular emissions, sewage irrigation, and application of phosphorus and potassium fertilizers. Comparing assessment results based on the posterior probability SVM and an SVM, we found the results calculated by the former model fit more closely with the soil quality expected based on artificial and natural factors in the study area. Our study indicates that soil quality assessment model, with a clear structure and ease in operation, can be used to study other ecosystems once properly calibrated.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Soil and Tillage Research - Volume 185, January 2019, Pages 146-152
Journal: Soil and Tillage Research - Volume 185, January 2019, Pages 146-152
نویسندگان
Huifeng Wang, Hong Zhang, Yong Liu,