Neural Networks In The Analysis And Design Of Structures

Neural Networks are a new, interdisciplinary tool for information processing. Neurocomputing being successfully introduced to structural problems which are difficult or even impossible to be analysed by standard computers (hard computing). The book is devoted to foundations and applications of NNs in the structural mechanics and design of structures.

For convenience, many of the proofs of the key theorems have been rewritten so that the entire book uses a relatively uniform notion.

Neural network-based algorithms find numerous applications in different scientific fields and, in particular, in the various areas of engineering. In Civil Engineering, however, there are still few applications of such methods. The purpose of this thesis is to apply the resolution capabilities of artificial neural networks to structural design.

Describing the application of artificial neural networks to structural mechanics, this book will be of interest to engineers, computer scientists and mathematicians working on the application of neural computing to structural mechanics and in particular finite element problems. It is accompanied by a voucher for a free software disk.

Artificial Intelligence-Based Design of Reinforced Concrete Structures: Artificial Neural Networks for Engineering Applications is an essential reference resource for readers who want to learn how to perform artificial intelligence-based structural design. The book describes, in detail, the main concepts of ANNs and their application and use in civil and architectural engineering. It shows how neural networks can be established and implemented depending on the nature of a broad range of diverse engineering problems. The design examples include both civil and architectural engineering solutions, for both structural engineering and concrete structures. Those who have not had the opportunity to study or implement neural networks before will find this book very easy to follow. It covers the basic network theory and how to formulate and apply neural networks to real-world problems. Plenty of examples based on real engineering problems and solutions are included to help readers better understand important concepts. Helps civil engineers understand the fundamentals of AI and ANNs and how to apply them in simple reinforced concrete design cases Contains practical case study examples on the application of AI technology in structural engineer Teaches readers how to apply ANNs as solutions for a broad range of engineering problems Includes AI-based software [MATLAB], which will enable readers to verify AI-based examples

Discover the new, unconventional alternatives for conquering RF and microwave design and modeling problems using neural networks -- information processing systems that can learn, generalize, and even allow model development when component formulas are missing -- with this book and software package. It shows you the ease of creating models with neural networks, and how quick model evaluation can be done, plus other opportunities presented by neural networks for conquering the toughest RF and microwave CAD problems.