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Diagnostic Analytics on Agriculture with Fuzzy Classification

Diagnostic Analytics on Agriculture with Fuzzy Classification
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Author(s): R. Umarani (Sri Sarada College for Women (Autonomous), India)and R. Suguna (Sri Sarada College for Women (Autonomous), India)
Copyright: 2020
Pages: 11
Source title: Fuzzy Expert Systems and Applications in Agricultural Diagnosis
Source Author(s)/Editor(s): A.V. Senthil Kumar (Hindusthan College of Arts and Science, India)and M. Kalpana (Tamil Nadu Agricultural University, India)
DOI: 10.4018/978-1-5225-9175-7.ch005

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Abstract

Agriculture is the main domain and need of India. The country is second place in the world in agriculture. Cropping is the main part of agriculture. Various crops like millets, fruits, vegetables, oil seeds are produced and exported to other countries every year. So, various innovative technologies are used to improve the productivity of crops in agriculture. Rainfall is most important for growing crops. The water level for the crops based on rainfall has some uncertainty. Fuzzy regression analysis is one of the methods based on regression analysis that is used to handle fuzzy parameters and crisp data and vice versa. Linear fuzzy regression is one of the methods of fuzzy regression analysis to handle fuzzy parameters. This chapter explores fuzzy classification, which is based on fuzzy regression analysis, and it is compared with other classification algorithms on the agriculture data.

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