کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6408510 1629456 2015 15 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
On the application of Bayesian Networks in Digital Soil Mapping
ترجمه فارسی عنوان
در مورد استفاده از شبکه های بیزی در نقشه برداری دیجیتال
موضوعات مرتبط
مهندسی و علوم پایه علوم زمین و سیارات فرآیندهای سطح زمین
چکیده انگلیسی


- Digital Soil Mapping codes complex soil landscape relationships.
- Bayesian Belief Networks (BN) is a novel approach to this.
- Expert knowledge can be effectively incorporated into BN.

Two corresponding issues concerning Digital Soil Mapping are the demand for up-to-date, fine resolution soil data and the need to determine soil-landscape relationships. In this study, we propose a Bayesian Network framework as a suitable modelling approach to fulfil these requirements. Bayesian Networks are graphical probabilistic models in which predictions are obtained using prior probabilities derived from either measured data or expert opinion. They represent cause and effect relationships through connections in a network system. The advantage of the Bayesian Networks approach is that the models are easy to interpret and the uncertainty inherent in the relationships between variables can be expressed in terms of probability. In this study we will define the fundamentals of a Bayesian Network and the probability theory that underpins predictions. Then, using case studies, we demonstrate how they can be applied to predict soil properties (bulk density) and soil taxonomic class (associations).

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Geoderma - Volumes 259–260, December 2015, Pages 134-148
نویسندگان
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