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

作者: hearing-aid    時間: 2025-3-21 17:25
書目名稱Machine Learning Control by Symbolic Regression影響因子(影響力)




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作者: Rheumatologist    時間: 2025-3-21 23:24

作者: 潛移默化    時間: 2025-3-22 02:53
https://doi.org/10.1007/978-3-030-83213-1optimal control; Symbolic regression; control synthesis; genetic algorithm; analytic programming; Optimal
作者: locus-ceruleus    時間: 2025-3-22 06:03
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.
作者: 增長    時間: 2025-3-22 11:05

作者: 艦旗    時間: 2025-3-22 14:31
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.
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作者: 誤傳    時間: 2025-3-23 05:22
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
作者: 延期    時間: 2025-3-23 07:21
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
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lern bei der selbstst?ndigen Regulation von Lernprozessen konfrontiert. Zudem wird die Einstellung zur Selbstregulation erfasst. Die Ergebnisse weisen darauf hin, dass sich Lehrende mit positiverer Einstellung eher an einer humanistisch gepr?gten Perspektive orientieren.978-3-658-05098-6978-3-658-05099-3
作者: 廢除    時間: 2025-3-24 05:34

作者: Insensate    時間: 2025-3-24 09:50
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, tech
作者: propose    時間: 2025-3-24 13:01
Mathematical Statements of MLC Problems,finding an unknown functional relationship. Next, we present the formulations of control theory problems that can be distinguished as machine learning control problems, namely the optimal control problem and more widely the general control synthesis problem, optimal control problem based on the synt
作者: 熄滅    時間: 2025-3-24 18:28
Numerical Solution of Machine Learning Control Problems,t popular and widespread apparatus of neural networks is considered. Theoretical substantiations are given for the general possibility of using machine learning methods for searching functions, namely the Kolmogorov–Arnold theorem. The only general approach of structural-parametric search of functio
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作者: 逃避現(xiàn)實    時間: 2025-3-24 23:19
Examples of MLC Problem Solutions, book. First, the tasks of unsupervised learning are considered based on the value of the target functional. The classical Pontryagin problem is considered and a comparison of the solution obtained by machine learning with the classical result is given. The problem of stabilization system synthesis
作者: Multiple    時間: 2025-3-25 06:23
ividualisierung von Unterricht. Entsprechend müssen Lehrende ihr t?gliches Vorgehen auch in Bezug auf geeignetes Feedback überdenken. Die erh?hte Selbstregulation der Lerner verursacht dabei ein Spannungsfeld zwischen Instruktion und Autonomie. Wie Lehrende sich hier verorten, h?ngt u. a. von ihrer
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A Novel HVS Based Gray Scale Image Watermarking Scheme Using Fast Fuzzy-ELM Hybrid Architecture,ting the Fuzzy Inference System (FIS) by taking into account luminance sensitivity, edge sensitivity and contrast sensitivity. The output of the FIS is a single output known as weighing factor (WF). A dataset is prepared using the image coefficients and the WF. A fast neural network known as extreme
作者: ABASH    時間: 2025-3-26 03:08
Blood and Bone Marrow Products in the Treatment of Radiation Injurylities, equipment, blood, and blood products for treating individuals exposed to radiation. The proper diagnosis and treatment of individuals exposed to radiation depend on methods used to detect the type and magnitude of radiation exposure, to decontaminate both the individuals and the environment
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作者: osteocytes    時間: 2025-3-26 16:08
Scope, Position and Sequence,ysis are used to provide insights into the competing forces that haunt and contradict simplistic positivist accounts of contemporary school leadership and to reveal the presence of a political struggle for the soul of the principal in this neoliberal era.
作者: dura-mater    時間: 2025-3-26 18:42
Phospholipids as Basic Ingredients deposition of minerals, lipofuscin, etc.). Another aspect in this connection is the .. Aerobic capacity declines with ageing (Robinson 1936, ?strand and Rodahl 1970, Hollman 1963, Davies 1972 etc.). Here in particular an important part is played by muscular tissue where the intensity of metabolic p
作者: 沒收    時間: 2025-3-26 23:33
Suresh Nath,Naveen Kangodecolonising the primary school history curriculum through teaching and learning may be in attempting to reframe Eurocentric mindsets; the default position from which trainee-teachers of White-British mono-ethnic background and socialisation begin to think about teaching the story of Britain’s past.
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作者: 發(fā)源    時間: 2025-3-27 08:23
Vishank Arun Shah,Romergryko G. GeocadinIt alreadyyielded a rich crop of mathematically pleasing, deep and beautiful results that quickly translated into a wealth of practical engineering applications. You are holding in your hands the ?rst guide boo978-1-4899-8245-2978-1-4419-7011-4
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