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.
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Table of Contents
1. Autonomous Design of Reinforced Concrete Beams and Columns Based on Artificial Neural Networks 2. Understanding artificial neural networks (ANNs): analogy to the biological neuron model 3. Factors influencing network trainings 4. Forward and backpropagation for artificial neural networks 5. Training methods: designs based on training entire data (TED), parallel training method (PTM), chained training scheme (CTS), and chained training scheme with revised sequence (CRS) 6. Singly reinforced concrete beams based on artificial neural networks 7. Design of Doubly Reinforced Concrete Beams based on Artificial Neural Network 8. Design of reinforced columns based on artificial neural networks
APPENDIX A. Manual to use MATLAB for training artificial neural networks (ANNs) B. MATLAB code for Revise Scenario 4 of Table 8.3
