Crop Recommender System for the Farmers using Mamdani Fuzzy Inference Model

  • Authors

    • Madhusree Kuanr
    • Bikram Kesari Rath
    • Sachi Nandan Mohanty
    2018-10-07
    https://doi.org/10.14419/ijet.v7i4.15.23006
  • Collaborative Recommender system, cosine similarity, fuzzy logic, Mamdani Fuzzy Inference model

  • Abstract

    Recommender systems provide suggestions to the users for choosing particular items from a large pool of items. The purpose of this study is to design a collaborative recommender system for the farmers for recommending giving prior idea regarding a crop which is suitable according to the location of the farmer based on weather condition of the previous months. The proposed system also recommends other seeds, pesticides and instruments according to the preferences in farming and location of the farmers while purchasing the seeds through online. It uses cosine similarity measure to find the similar user according the location of the farmer and fuzzy logic for predicting the yield of rice crop for Kharif season in state Odisha, India. The proposed system is implemented in Mamdani Fuzzy Inference model. The results reveal that it provides prior idea regarding a crop before sowing of seeds.

     

     

  • References

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  • How to Cite

    Kuanr, M., Kesari Rath, B., & Nandan Mohanty, S. (2018). Crop Recommender System for the Farmers using Mamdani Fuzzy Inference Model. International Journal of Engineering & Technology, 7(4.15), 277-280. https://doi.org/10.14419/ijet.v7i4.15.23006

    Received date: 2018-12-03

    Accepted date: 2018-12-03

    Published date: 2018-10-07