Machine Learning Control by Symbolic Regression
暫譯: 符號回歸的機器學習控制
Diveev, Askhat, Shmalko, Elizaveta
- 出版商: Springer
- 出版日期: 2021-10-24
- 售價: $5,640
- 貴賓價: 9.5 折 $5,358
- 語言: 英文
- 頁數: 150
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 3030832120
- ISBN-13: 9783030832124
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相關分類:
Machine Learning
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相關主題
商品描述
This book provides comprehensive coverage on a new direction in computational mathematics research: automatic search for formulas. Formulas must be sought 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 application of numerical methods of symbolic regression to solving control problems, the authors offer new possibilities not only in the field of control automation, but also in the design of completely different optimal structures in many fields.
For specialists in the field of control, Machine Learning Control by Symbolic Regression opens up a new promising direction of research and acquaints scientists with the methods of automatic construction of control systems.For specialists in the field of machine learning, the book opens up 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 used. For mathematicians, the book opens up a new approach to the construction of numerical methods for obtaining analytical solutions to unsolvable problems; for example, numerical analytical solutions of algebraic equations, differential equations, non-trivial integrals, etc. For specialists in the field of artificial intelligence, the book offers a machine way to solve problems, framed in the form of analytical relationships.
商品描述(中文翻譯)
這本書全面探討計算數學研究的一個新方向：自動尋找公式。公式必須在科學和生活的各個領域中尋找：這些是宇宙的法則、宏觀和微觀世界、基本物理學、工程、天氣和自然災害預測；在經濟學、政治學、社會學中尋找新法則。作者累積了多年在符號回歸的數值方法開發和應用於控制問題解決的經驗，提供了在控制自動化領域以及在許多領域設計完全不同的最佳結構的新可能性。
對於控制領域的專家來說，《Machine Learning Control by Symbolic Regression》開啟了一個新的有前景的研究方向，並使科學家熟悉自動構建控制系統的方法。對於機器學習領域的專家來說，這本書開啟了一個比神經網絡更廣泛的新方向：符號回歸方法。這本書使得掌握這一機器學習的新領域變得容易，並在神經網絡使用的所有地方應用這種方法。對於數學家來說，這本書提供了一種新的方法來構建數值方法，以獲得無法解決問題的解析解；例如，代數方程、微分方程、非平凡積分的數值解析解等。對於人工智慧領域的專家來說，這本書提供了一種以解析關係形式框架的機器解決問題的方法。
作者簡介
Prof., Dr. Diveev is a renowned specialist in the field of control and a leading researcher in Russia in evolutionary computation and symbolic regression. He received the Ph.D. degree in technical science from Bauman Moscow State Technical University, in 1989, and Doctor of Sciences in 2001 in Dorodnitsyn Computing Center of the Russian Academy of Sciences, in 2009 he became a professor. Presently, he works as a Director of Robotic Center of Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences. He is also a Professor at the RUDN University, Engineering Department. He is the author of five books, more than 300 articles. Prof. Diveev is a member of the editorial board of the RUDN journal of Engineering Researches and journal of Instrument Engineering of the Bauman Moscow State Technical University, a general chair of the INTELS Symposium.
Dr. Shmalko is a former student and follower of Prof. Diveev, received the B.S. and M.S. degrees in Computer Science and Cybernetics from RUDN University, Engineering Dept. and the Ph.D. degree from Dorodnicyn Computing Center of the Russian Academy of Sciences, Moscow, Russia, in 2009. From 2007 to 2010, she was with IBM East Europe/Asia. Since 2010, she is a Senior researcher with the Computing Center of the Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences.
The authors' current research interests are computational methods in control, symbolic regression and evolutionary computation with applications to model identification, optimization and control system synthesis. The authors conduct theoretical research and implement applied tasks on the basis of the Robotics Center of the Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences.
作者簡介(中文翻譯)
德維耶夫教授是控制領域的知名專家，也是俄羅斯進化計算和符號回歸的領先研究者。他於1989年在莫斯科巴馬科技大學獲得技術科學博士學位，並於2001年在俄羅斯科學院多羅德尼辛計算中心獲得科學博士學位，2009年成為教授。目前，他擔任俄羅斯科學院聯邦研究中心「計算機科學與控制」的機器人中心主任，同時也是RUDN大學工程系的教授。他是五本書籍的作者，發表了300多篇文章。德維耶夫教授是RUDN工程研究期刊和莫斯科巴馬科技大學儀器工程期刊的編輯委員會成員，也是INTELS研討會的總主席。
施馬爾科博士是德維耶夫教授的前學生和追隨者，於RUDN大學工程系獲得計算機科學和控制論的學士和碩士學位，並於2009年在俄羅斯莫斯科的多羅德尼辛計算中心獲得博士學位。她曾於2007年至2010年在IBM東歐/亞洲工作。自2010年以來，她是俄羅斯科學院聯邦研究中心「計算機科學與控制」的高級研究員。
作者目前的研究興趣包括控制中的計算方法、符號回歸和進化計算，應用於模型識別、優化和控制系統合成。作者在俄羅斯科學院聯邦研究中心「計算機科學與控制」的機器人中心進行理論研究並實施應用任務。
