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Optimization models extraction from data
V. I. Donskoy V. I. Vernadsky Crimean Federal University, 4 Vernadsky Av., Simferopol 295007, Russian Federation
Abstract:
The basic principles, methods and algorithms representing a new information technology for building optimization mathematical models from data (BOMD) are presented. This technology allows one to automatically build mathematical models of planning and control on the basis of use of precedents (observations) over objects that gives the chance to solve the problems of intellectual control and to define expedient behavior of economic and other objects in difficult environments. The BOMD technology allows one to obtain objective control models that reflect real-life relationships, goals, constraints, and processes. This is its main advantage over the traditional, subjective approach to control. Linear and nonlinear algorithms for synthesis of models based on precedent information are developed.
Keywords:
machine learning, model extraction from data, optimization, neural networks, gradient methods.
Received: 20.05.2019
Citation:
V. I. Donskoy, “Optimization models extraction from data”, Inform. Primen., 14:3 (2020), 109–118
Linking options:
https://www.mathnet.ru/eng/ia687 https://www.mathnet.ru/eng/ia/v14/i3/p109
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Abstract page: | 121 | Full-text PDF : | 49 | References: | 9 |
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