Titlebook: Machine Learning Control by Symbolic Regression; Askhat Diveev,Elizaveta Shmalko Book 2021 The Editor(s) (if applicable) and The Author(s)

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Rheumatologist

潛移默化

https://doi.org/10.1007/978-3-030-83213-1optimal control; Symbolic regression; control synthesis; genetic algorithm; analytic programming; Optimal

locus-ceruleus

Introduction,ocess of control, about artificial intelligence and machine learning, and, of course, about symbolic regression methods, which open up new possibilities not only in the field of control automation, but also in the design of completely different optimal structures, including building structures, technical systems, and even musical works.

增長(zhǎng)

艦旗

Mathematical Statements of MLC Problems,wn function. The function can be set up to parameters, and then machine learning techniques are used only to adjust the parameters. In general case, both the structure of the function and its parameters should be found.

向外

Obsequious

誤傳

Book 2021ught in all areas of science and life: these are the laws of the universe, the macro and micro world, fundamental physics, engineering, weather and natural disasters forecasting; the search for new laws in economics, politics, sociology. Accumulating many years of experience in the development and a

延期

a new, much broader direction than neural networks: methods of symbolic regression. This book makes it easy to master this new area in machine learning and apply this approach everywhere neural networks are use978-3-030-83215-5978-3-030-83213-1