Rule Descriptions for Soil Quality and Soil Fertility Assessment using Fuzzy Control System
Himanshu Pant1, Manoj Chandra Lohani2, Ashutosh Bhatt3, Janmejay Pant4, Manoj Kumar Singh5
1Himanshu Pant*, Department of Computer Science, Graphic Era Hill University, Bhimtal, India.
2Manoj Chandra Lohani, Department of Computer Science, Graphic Era Hill University, Bhimtal, India.
3Janmejay Pant, Department of Computer Science, Graphic Era Hill University, Bhimtal, India.
4Ashutosh Bhatt, Department of Computer Science, BIAS, Bhimtal, India.
5Manoj Kumar Singh, Department of Computer Science, Graphic Era Hill University, Bhimtal, India.
Manuscript received on February 10, 2020. | Revised Manuscript received on February 20, 2020. | Manuscript published on March 30, 2020. | PP: 1341-1346 | Volume-8 Issue-6, March 2020. | Retrieval Number: F7663038620/2020©BEIESP | DOI: 10.35940/ijrte.F7663.038620
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The three major elements or fertilizers of the soil are Nitrogen (N), Phosphorus (P) and Potassium (K). These three elements are necessary for the plants development and increase the productiveness of the soil. The trend for categorizing soil quality for the diversity of usages is by calculating the Soil Fertility Indexes (SFI). In this paper, we have created a fuzzy control system using scikit-learn-fuzzy or skfuzzy (Fuzzy Logic Toolbox for Python) for Soil quality and fertility assessment, based on fuzzy rules to suggest suitable nutrients for the crops and relate to linguistic classification of soil excellence with degree of confidence in Nainital district of Uttarakhand, India.
Keywords: Fuzzy control system, Fuzzy logic, Fuzzy rule-based system, Linguistic term, Soil fertility, Soil quality.
Scope of the Article: Fuzzy logics.