Semi-Empirical Neural Network Modeling
暫譯: 半經驗神經網絡建模
Tarkhov, Dmitriy, Lazovskaya, T. V., Nikolayevich Vasilyev, Alexander
- 出版商: Academic Press
- 出版日期: 2019-11-22
- 售價: $5,470
- 貴賓價: 9.5 折 $5,197
- 語言: 英文
- 頁數: 320
- 裝訂: Quality Paper - also called trade paper
- ISBN: 0128156511
- ISBN-13: 9780128156513
海外代購書籍(需單獨結帳)
商品描述
Semi-empirical Neural Network Modeling presents a new approach on how to quickly construct an accurate, multilayered neural network solution of differential equations. Current neural network methods have significant disadvantages, including a lengthy learning process and single-layered neural networks built on the finite element method (FEM). The strength of the new method presented in this book is the automatic inclusion of task parameters in the final solution formula, which eliminates the need for repeated problem-solving. This is especially important for constructing individual models with unique features. The book illustrates key concepts through a large number of specific problems, both hypothetical models and practical interest.
- Offers a new approach to neural networks using a unified simulation model at all stages of design and operation
- Illustrates this new approach with numerous concrete examples throughout the book
- Presents the methodology in separate and clearly-defined stages
商品描述(中文翻譯)
《半經驗神經網絡建模》提出了一種快速構建準確的多層神經網絡解決微分方程的新方法。目前的神經網絡方法存在顯著的缺點,包括漫長的學習過程和基於有限元素法(FEM)構建的單層神經網絡。本書中提出的新方法的優勢在於自動將任務參數納入最終解決公式,從而消除了重複解題的需要。這對於構建具有獨特特徵的個別模型尤其重要。本書通過大量具體問題來說明關鍵概念,包括假設模型和實際應用的問題。
- 提供了一種在設計和操作的所有階段使用統一模擬模型的神經網絡新方法
- 通過書中的眾多具體例子來說明這種新方法
- 以單獨且明確定義的階段呈現方法論