基于人工智能的结构框架优化设计及其在实际建筑设计中的应用
This book introduces an auto‑design‑based optimization for building frames using an artificial neural network (ANN)‑based Lagrange method and novel genetic algorithm (GA). The work of great mathematician Joseph‑Louis Lagrange and ANNs are merged to identify parameters that optimize structural frames of reinforced concrete, prestressed concrete, and steel frames subject to one or more design constraints. New features for enhancing conventional GA are also demonstrated to optimize structural frames.
New features for optimizing multiple design targets of the building frames are highlighted, while design requirements imposed by codes are automatically satisfied. Chapters provide readers with an understanding of how both ANN‑based and novel GA‑based structural optimization can be implemented in holistically optimizing designated design targets for building structural frames, guiding readers toward more rational designs that is consistent with American Institute of Steel Construction (AISC) and American Concrete Institute (ACI) standards. ANN‑based holistic designs of multi‑story frames in general and reinforced concrete, prestressed concrete, and steel frames in particular, are introduced.
This book suits structural engineers, architects, and graduate students in the field of building frame designs and is heavily illustrated with color figures and tables.
中文|2024|ISBN:978100344826|607页|True PDF，EPUB | 107.38 MB本书介绍了一种基于自动设计的建筑框架优化方法，该方法使用基于人工神经网络（ANN）的拉格朗日方法和新型遗传算法（GA）。伟大数学家Joseph Louis Lagrange和ANN的工作被合并，以确定在一个或多个设计约束下优化钢筋混凝土、预应力混凝土和钢框架结构框架的参数。还展示了增强传统遗传算法的新功能，以优化结构框架。 突出了优化建筑框架多个设计目标的新功能，同时自动满足规范规定的设计要求。各章让读者了解如何在整体优化建筑结构框架的指定设计目标时实现基于ANN和基于GA的新型结构优化，引导读者进行符合美国钢结构学会（AISC）和美国混凝土学会（ACI）标准的更合理的设计。介绍了基于人工神经网络的多层框架整体设计，特别是钢筋混凝土、预应力混凝土和钢框架。 这本书适合建筑框架设计领域的结构工程师、建筑师和研究生，并配有大量彩色插图和表格。本站不对文件进行储存，仅提供文件链接，请自行下载，本站不对文件内容负责，请自行判断文件是否安全，如发现文件有侵权行为，请联系管理员删除。
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