Artificial Intelligence Assisted Structural Optimization
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Artificial Intelligence Assisted Structural Optimization
Artificial Intelligence Assisted Structural Optimization explores the use of machine learning and correlation analysis within the forward design and inverse design frameworks to design and optimize lightweight load-bearing structures as well as mechanical metamaterials. Discussing both machine learning and design analysis in detail, this book enables readers to optimize their designs using a data-driven approach. This book discusses the basics of the materials utilized, for example, shape memory polymers, and the manufacturing approach employed, such as 3D or 4D printing. Additionally, the book discusses the use of forward design and inverse design frameworks to discover novel lattice unit cells and thin-walled cellular unit cells with enhanced mechanical and functional properties such as increased mechanical strength, heightened natural frequency, strengthened impact tolerance, and improved recovery stress. Inverse design methodologies using generative adversarial networks are proposed to further investigate and improve these structures. Detailed discussions on fingerprinting approaches, machine learning models, structure screening techniques, and typical Python codes are provided in the book. The book provides detailed guidance for both students and industry engineers to optimize their structural designs using machine learning.
AI-Assisted Library Reconstruction
In an era marked by rapid technological progress, libraries find themselves at a crossroads grappling with the challenges posed by an information-rich yet digitally fragmented landscape. The conventional role of libraries, once the steadfast guardians of knowledge, faces disruption as we navigate through a sea of information abundance. This conundrum gives rise to a critical issue - how can libraries adapt and thrive in an environment dominated by the rapid evolution of artificial intelligence (AI)? AI-Assisted Library Reconstruction is a compelling solution that promises to breathe new life into these institutions, making them more dynamic, accessible, and efficient in the face of unprecedented challenges. This book addresses the pressing issues faced by libraries in the age of information technology. It doesn't merely scratch the surface; it delves deep into the heart of the matter, providing an exploration of the integration of artificial intelligence in the reconstruction and revitalization of libraries. Through an in-depth examination of technologies, methodologies, and applications, it offers a guide for libraries to not only survive but thrive in this technologically charged landscape.
Computational Intelligence Assisted Design
Computational Intelligence Assisted Design framework mobilises computational resources, makes use of multiple Computational Intelligence (CI) algorithms and reduces computational costs. This book provides examples of real-world applications of technology. Case studies have been used to show the integration of services, cloud, big data technology and space missions. It focuses on computational modelling of biological and natural intelligent systems, encompassing swarm intelligence, fuzzy systems, artificial neutral networks, artificial immune systems and evolutionary computation. This book provides readers with wide-scale information on CI paradigms and algorithms, inviting readers to implement and problem solve real-world, complex problems within the CI development framework. This implementation framework will enable readers to tackle new problems without difficulty through a few tested MATLAB source codes