Ai Based Optimized Design Of Structural Frames
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Ai Based Optimized Design Of Structural Frames
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Author : Won‐Kee Hong
language : en
Publisher: CRC Press
Release Date : 2024-10-16
Ai Based Optimized Design Of Structural Frames written by Won‐Kee Hong and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-16 with Technology & Engineering categories.
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.
Ai Based Optimized Design Of Structural Frames
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Author : Won-Kee Hong
language : en
Publisher: CRC Press
Release Date : 2024-10
Ai Based Optimized Design Of Structural Frames written by Won-Kee Hong and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10 with Business & Economics categories.
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.
Artificial Neural Network Based Optimized Design Of Reinforced Concrete Structures
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Author : Won‐Kee Hong
language : en
Publisher: CRC Press
Release Date : 2023-01-11
Artificial Neural Network Based Optimized Design Of Reinforced Concrete Structures written by Won‐Kee Hong and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-01-11 with Technology & Engineering categories.
Artificial Neural Network-based Optimized Design of Reinforced Concrete Structures introduces AI-based Lagrange optimization techniques that can enable more rational engineering decisions for concrete structures while conforming to codes of practice. It shows how objective functions including cost, CO2 emissions, and structural weight of concrete structures are optimized either separately or simultaneously while satisfying constraining design conditions using an ANN-based Lagrange algorithm. Any design target can be adopted as an objective function. Many optimized design examples are verified by both conventional structural calculations and big datasets. Uniquely applies the new powerful tools of AI to concrete structural design and optimization Multi-objective functions of concrete structures optimized either separately or simultaneously Design requirements imposed by codes are automatically satisfied by constraining conditions Heavily illustrated in color with practical design examples The book suits undergraduate and graduate students who have an understanding of collegelevel calculus and will be especially beneficial to engineers and contractors who seek to optimize concrete structures.
Handbook Of Ai Based Metaheuristics
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Author : Anand J. Kulkarni
language : en
Publisher: CRC Press
Release Date : 2021-09-01
Handbook Of Ai Based Metaheuristics written by Anand J. Kulkarni and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-01 with Computers categories.
At the heart of the optimization domain are mathematical modeling of the problem and the solution methodologies. The problems are becoming larger and with growing complexity. Such problems are becoming cumbersome when handled by traditional optimization methods. This has motivated researchers to resort to artificial intelligence (AI)-based, nature-inspired solution methodologies or algorithms. The Handbook of AI-based Metaheuristics provides a wide-ranging reference to the theoretical and mathematical formulations of metaheuristics, including bio-inspired, swarm-based, socio-cultural, and physics-based methods or algorithms; their testing and validation, along with detailed illustrative solutions and applications; and newly devised metaheuristic algorithms. This will be a valuable reference for researchers in industry and academia, as well as for all Master’s and PhD students working in the metaheuristics and applications domains.
New Advances In Soft Computing In Civil Engineering
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Author : Gebrail Bekdaş
language : en
Publisher: Springer Nature
Release Date : 2024-08-07
New Advances In Soft Computing In Civil Engineering written by Gebrail Bekdaş and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-07 with Technology & Engineering categories.
Soft computing applications plays a crucial role in civil engineering applications, with engineers striving to create outstanding designs that prioritize safety, aesthetics, cost-efficiency, and environmental considerations. Advanced optimization techniques are especially valuable for complex systems including multi-constraint problems, multi-objective problems and control problems needing iterative processes in solving differential equations. Throughout history, people have used their creativity to enhance designs in everyday tasks, and this is where metaheuristics come into play, drawing inspiration from nature to develop novel algorithms. These artificial intelligence-based algorithms possess distinctive attributes, and leveraging various features from different algorithms can enhance the effectiveness of optimization, improving precision, computational efficiency, and convergence. This book serves as a timely resource, summarizing the latest advancements in civil engineering optimization, encompassing both metaheuristic approaches and emerging trends that integrates artificial intelligence and machine learning techniques to predict optimal solutions, streamlining lengthy optimization processes. The book's chapters cover a wide range of civil engineering applications, with the primary goal being to introduce fundamental concepts and advanced adaptations. This comprehensive resource is designed to provide undergraduates and graduate engineering students with a solid understanding of materials and content, making it a valuable reference for university courses in various civil engineering disciplines. The book will be edited, and the editors will contribute to most of the chapters. Depending on the availability of high-quality papers, the editors may increase their contributions by sharing recent research projects and postgraduate students' theses.
Civil And Environmental Engineering For Resilient Smart And Sustainable Solutions
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Author : Tahar Ayadat
language : en
Publisher: Materials Research Forum LLC
Release Date : 2025-03-25
Civil And Environmental Engineering For Resilient Smart And Sustainable Solutions written by Tahar Ayadat and has been published by Materials Research Forum LLC this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-25 with Technology & Engineering categories.
The book focusses on recent developments in the area of infrastructures that are resilient, smart, and sustainable. It presents an important guideline for policy makers, engineers and researchers interested in various infrastructure issues faced by societies. Keywords: Earthquakes, Damage Localization, Global Warming, Machine Learning, Seismic Assessment, Reinforced Concrete, Fire Behavior, Shape Memory Alloys, Green Sustainable Concrete, Geotechnical Parameters, Cement Paste, Plasticity Index, Urban Environment, Underground Pipeline, Soil Stabilization, Groundwater Monitoring, Solar Photovoltaic Systems, Climate Change, Pollution Monitoring, Cost Estimation Model.
Criteria And Methods Of Structural Optimization
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Author : Andrzej M Brandt
language : en
Publisher: Springer Science & Business Media
Release Date : 1987-06-30
Criteria And Methods Of Structural Optimization written by Andrzej M Brandt and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 1987-06-30 with Science categories.
This book is intended to serve all those who are interested in structural opti mization, whether they work in this field or study it for other purposes. Rapid growth of interest in the cognitive aspects of optimization and the increas ing demands that the present day engineer has to meet in modern design have created the need of a monographic treatment of the subject. The vast number and wide range of structural optimization problems formulated and investigated in the last twenty years call for an attempt to sum up the pres ent state of knowledge in this domain and to outline the directions of its further development. The present authors undertook this task, hoping that the result would stimulate further work towards finding new methods and solutions and increasing the range of applications of the optimization methods to structural design. The immediate aim of the book is to present the basic criteria and methods of optimization and to provide a reference guide to the most important publications in the field. 'The book consists of fourteen chapters. Chapter 1 introduces the basic concepts, definitions and assumptions relating to structural optimization. Chapter 2 gives the foundations of optimization for minimum elastic strain potential or maximum rigidity, and sets a basis for optimization of bar, plate and lattice structures. Chapter 3 presents criteria of strength design and their applications to plane structures.
Modern Computing Technologies For Ev Efficiency And Sustainable Energy Integration
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Author : Fotis, George
language : en
Publisher: IGI Global
Release Date : 2025-05-30
Modern Computing Technologies For Ev Efficiency And Sustainable Energy Integration written by Fotis, George and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-30 with Technology & Engineering categories.
The market for electric vehicles (EVs) and sustainable energy solutions is experiencing exponential growth, driven by increasing environmental concerns and the need for sustainable alternatives to traditional transportation and energy sources. From intelligent energy management systems to autonomous driving algorithms, modern computing technology is shaping the future of transportation and energy. Therefore, modern computing can drive industrial growth and foster sustainable infrastructure that supports both economic development and environmental sustainability. The efficient use of computing technologies to minimize energy waste, optimize EV charging, and promote renewable energy integration offers a clear path to mitigating climate change. Modern Computing Technologies for EV Efficiency and Sustainable Energy Integration explores the intersection of cutting-edge computing technology and the rapidly evolving fields of EVs and renewable energy. It delves into how advancements in computing are driving innovation in these sectors, shaping the future of transportation and energy sustainability. Covering topics such as interoperability, control strategies, and hybrid energy management, this book is an excellent resource for engineers, technologists, environmentalists, sustainability experts, policymakers, professionals, researchers, scholars, academicians, and more.
Advances In Structural Engineering Optimization
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Author : Sinan Melih Nigdeli
language : en
Publisher: Springer Nature
Release Date : 2020-12-04
Advances In Structural Engineering Optimization written by Sinan Melih Nigdeli and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-04 with Technology & Engineering categories.
This book is an up-to-date source for computation applications of optimization, prediction via artificial intelligence methods, and evaluation of metaheuristic algorithm with different structural applications. As the current interest of researcher, metaheuristic algorithms are a high interest topic area since advance and non-optimized problems via mathematical methods are challenged by the development of advance and modified algorithms. The artificial intelligence (AI) area is also important in predicting optimum results by skipping long iterative optimization processes. The machine learning used in generation of AI models also needs optimum results of metaheuristic-based approaches. This book is a great source to researcher, graduate students, and bachelor students who gain project about structural optimization. Differently from the academic use, the chapter that emphasizes different scopes and methods can take the interest and help engineer working in design and production of structural engineering projects.
Genetic Ai Algorithms Evolutionary Approaches For Solving Complex Computational Problems
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Author : Rajesh Ojha Prof (Dr) Ajay Shriram Kushwaha
language : en
Publisher: DeepMisti Publication
Release Date : 2025-01-14
Genetic Ai Algorithms Evolutionary Approaches For Solving Complex Computational Problems written by Rajesh Ojha Prof (Dr) Ajay Shriram Kushwaha and has been published by DeepMisti Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-14 with Computers categories.
In an era where technology evolves at an unprecedented pace, the demand for efficient, adaptable, and innovative solutions to complex computational problems has never been greater. Traditional algorithms often struggle to tackle the complexity, non-linearity, and scale of challenges faced in various fields, ranging from artificial intelligence (AI) to data science, bioinformatics, and beyond. This is where the power of genetic algorithms (GAs) and other evolutionary computation techniques comes into play, offering a new paradigm for problem-solving inspired by the process of natural selection. Genetic AI Algorithms: Evolutionary Approaches for Solving Complex Computational Problems explores the fascinating intersection of evolutionary biology and computational intelligence. It delves into the principles, techniques, and applications of genetic algorithms (GAs), genetic programming (GP), and other evolutionary strategies to provide readers with a comprehensive understanding of how these methods can be used to address some of the most challenging problems in modern computing. Evolutionary algorithms draw inspiration from the mechanisms of natural evolution, such as selection, mutation, crossover, and inheritance. These methods excel at finding optimal or near-optimal solutions in vast, poorly understood, or highly complex problem spaces. By mimicking the evolutionary process, they can explore potential solutions in ways that are often more robust and flexible than traditional approaches. Whether it’s solving optimization problems, designing neural networks, evolving game strategies, or simulating biological systems, evolutionary algorithms provide a powerful framework for innovation. This book serves as both an introduction and a practical guide for those seeking to harness the power of genetic AI algorithms. It begins with foundational concepts and gradually builds up to more advanced topics, ensuring accessibility for newcomers while providing in-depth insights for experienced practitioners. Through a combination of theory, examples, and case studies, readers will learn how to apply evolutionary algorithms to real-world problems, gain insights into the latest research, and discover new frontiers in computational intelligence. By the end of this journey, readers will be equipped with the knowledge and tools necessary to implement genetic AI algorithms for solving a wide array of complex computational challenges. As you embark on this exploration, I encourage you to think creatively and embrace the potential of evolutionary approaches to drive progress in your work, whether in academia, industry, or any other domain where computational problems abound. In closing, it is my hope that this book inspires further inquiry and discovery in the exciting field of genetic AI algorithms, and that it provides a solid foundation for those seeking to unlock the full potential of evolutionary computation. Authors