Abstract

As one of the most important factors that interfere in peoples life, the soil is characterized by quantitative and qualitative features which describe not only the soil itself, but also the environment, the weather and the vegetation around it. Different types of soil can be identified by means of these features. A good soil classification is very important to get a better use of the soil. Soil classification, when performed manually by experts, is not a simple task, as long as the experts opinions may vary considerably. Besides, different types of soil cannot be defined deterministically. With the objective of exploring an alternative approach towards solving this problem, we investigated in this paper the application of an automatic procedure to generate a soil classifier from data, using a fuzzy decision tree induction algorithm. In order to compare the results obtained by means of the fuzzy decision tree classifier, we used two well known methods for classifiers generation: the classic decision tree induction algorithm C4.5 and the fuzzy rules induction algorithm named FURIA.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.