Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6901404 | Procedia Computer Science | 2017 | 8 Pages |
Abstract
In this paper, the grain loss assessment was studied based on logistic regression, and 5400 samples of 31 provinces in our country in the year 2012-2014 were selected, and the 7 typical provinces among them were respectively tested. Using the logistic regression model to predict the loss rate of grain harvesting step, the prediction result is 86.25%. The stochastic gradient descent algorithm is used to optimize the parameters of the model, when the learning_rate is 0.1, the prediction results of grain harvest losses of up to 92.53%, which further improves the prediction accuracy of grain harvest step loss.
Keywords
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Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
Tingkai Huang, Bingchan Li, Dongqin Shen, Jie Cao, Bo Mao,