Abstract
The model of the yield forecast, realized as fuzzy knowledge bases, has been described. An algorithm for constructing a prediction model of this type has been given. In the basic procedures of this algorithm, operations of fuzzy inference have been used. A lot of inference rules describing the forecast model appear in a fuzzy knowledge base in the form of an expert knowledge matrix. The organization of a computational experiment on the evaluation of the effectiveness of the proposed model for predicting cotton yields is outlined. The input parameters of the model under study are: weather (climatic) conditions during sowing, vegetation and harvesting, degree of water supply, types of crops, types of soils, and types and amount of fertilizer application. The problems of constructing a forecasting model for yields under indistinctly specified information on the climatic and agro-technical conditions of growing agricultural crops were considered.
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Mukhamediyeva, D., Solieva, B. (2020). Construction of the Model of Crop Production Forecasting with Fuzzy Information. In: Pawar, P., Ronge, B., Balasubramaniam, R., Vibhute, A., Apte, S. (eds) Techno-Societal 2018 . Springer, Cham. https://doi.org/10.1007/978-3-030-16848-3_18
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DOI: https://doi.org/10.1007/978-3-030-16848-3_18
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