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@article{164362,
        author = {M. Hariharan and Dr.M.Balamurugan},
        title = {Optimizing Agricultural Loan Distribution Through Fuzzy Logic Based Digitalized Process},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {10},
        number = {12},
        pages = {1324-1330},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=164362},
        abstract = {The level of agricultural information is an important part of the modernization of a country. It is important to set up a fair evaluation code system for agricultural informatization and evaluation methods to promote agricultural loan information. The previous method cannot effective in analyzing the season, environment, rainfall for the loan process. It cannot show the proper results for the agriculture loan constructions.so the crop or seed loan procedure will not be proper method based upon the previous statistical report. Due to the lack of support for irrigation and harvesting techniques are ineffective. While the impact of seasonal change on Indian agriculture loan is still clear, monitoring the user data and their different impacts will be crucial. To resolve these issues, propose a Fuzzy Logic, Method. The proposed method provides a flexible and advanced process is important for the field, especially the proposed method and response in the critical environment that can monitor the agriculture loan issues. The proposed Fuzzy Logic method monitors the season, environment, and rain study for loan process. Fuzzy Logic model can not only use them for loan procedure in different areas depending on the level of informatization but can also achieve quality assessment based on agricultural information in different parts of the rating system. Finally, the built-in agricultural information evaluation system would be useful, and the evaluation method that is going to be used is simple and easy to use.},
        keywords = {Agricultural informatization, Fuzzy logic, Construction Index, quality assessment, cultivation.},
        month = {},
        }