Investigation on agricultural land selection using hybrid fuzzy logic system ∗
Document Type
Article
Publication Date
1-1-2020
Abstract
For maintaining the horticultural generation, Land Selection Investigation (LSI) is essential. Though incorporates estimation of the criteria assortment from the soil, territory to financial, market, and foundation, and these components are considerably enigmatically characterized and described by their inherent ambiguity. Multi-criteria basic leadership systems like positioning, rating, and so on are utilized for reasonableness examination. Master learning and judgment by leaders at different levels is integrated into this process. In the field of farming sciences, the Fuzzy Logic (FL) strategy has been effectively used to take care of numerous issues. Fuzzy with AHP is a Hybrid Fuzzy Logic (HFL) methodology. The policies Analytic Hierarchy Process (AHP), Fuzzy Numbers, Fuzzy Degree Investigation, Alpha Cut, and Lambda capacity are associated with it. As expressed, the procedure of necessary leadership includes a scope of criteria and a considerable measure of master learning and decisions. The components result from impacts extraordinarily. The capacity of three methods to demonstrate the affectability of the necessary leadership procedure is researched. Alpha cut and lambda esteem give and encourage considerable affectability investigation. All techniques are actualized to examine the reasonableness of the crop in the Indian nation. Test results when performed on Various Datasets, demonstrate that the proposed procedure removes more highlights just as gives more exactness when contrasted with existing techniques.
Publication Title
Scalable Computing
First Page Number
569
Last Page Number
582
DOI
10.12694:/scpe.v21i4.1604
Recommended Citation
Sengan, Sudhakar; Vijayakumar, V.; Krishnamoorthy, Sujatha; Gunasekaran, S.; Kumar, C. Sathiya; Palani, Saravanan; and Subramaniyaswamy, V., "Investigation on agricultural land selection using hybrid fuzzy logic system ∗" (2020). Kean Publications. 1260.
https://digitalcommons.kean.edu/keanpublications/1260