E3S Web Conf.
Volume 176, 2020International Scientific and Practical Conference “From Inertia to Develop: Research and Innovation Support to Agriculture” (IDSISA 2020)
|Number of page(s)||4|
|Section||Resource-Saving Technologies, Technical Means and the Digital Platform of the Agro-Industrial Complex|
|Published online||22 June 2020|
The use of machine learning methods in the diagnosis of diseases of crops
1 Financial University under the Government of the Russian Federation, Department of Data Analysis, Decision Making and Financial Technology, 105187, st. Shcherbakovskaya, 38, Moscow, Russia
2 State University of Management, Department of Innovation Management, 109542, Ryazan Avenue, 99, Moscow, Russia,
3 Yuri Gagarin State Technical University of Saratov, Department of Information Security of Automated Systems, 410054, Polytechnic St., 77, Saratov, Russia
4 Saratov State University of Saratov, Department of Nano and Biomedical Technologies, 410012, st. Astrakhanskaya, 83, Saratov, Russia
5 Institute of Precision Mechanics and Control of the Russian Academy of Sciences, 410028, st. Working, 24, Saratov, Russia
* Corresponding author: SAKorchagin@fa.ru
The approach to solving the problems of diagnosis and prognosis of diseases of agricultural crops using machine learning methods is described. To solve the problem of forecasting diseases of agricultural crops, it is proposed to use a genetic algorithm in the work. The analysis of the effectiveness of the proposed method is carried out depending on the convergence rate of such parameters as the mutation coefficient and population size. To solve the problem of diagnostics of agricultural crops, it is proposed to use a recurrent type of neural network. A software modelling complex has been developed that allows solving the problems of plant diseases diagnostics and making forecasts. The results obtained can reduce the costs of agricultural enterprises by reducing the cost of diagnosing agricultural diseases.
© The Authors, published by EDP Sciences, 2020
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