Prediction using Sugar production data : Neural and Fuzzy time series
نویسندگان
چکیده
. This study covers inquisitive approach to develop an Artificial Neural Network (ANN) model to foresee sugarcane production. The various input data set comprises the agro-climatic and socio-economic factors influencing sugarcane production whereas the output is real sugarcane output. Different forecasting techniques have been deployed on the concept of fuzzy time series data, whereas precision has been a doubtful factor in this scenario. In this paper, On the basis of fuzzy time series (FTS) models performance analysis has been drawn. Data from Food Corporation of India have been gathered for performing the comparative study. The relativity of various FTS models have been suspiciously investigated on the production data on different agro products.
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