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 English | 2022 | ISBN: 0367765276 | 363 pages | True PDF | 46.53 MB This bookdescribes the application of artificial intelligence (AI)/machine learning (ML) concepts to develop predictive models that can be used to design alloy materials, including hard and soft magnetic alloys, nickel-base superalloys, titanium-base alloys, and aluminum-base alloys. Readers new to AI/ML algorithms can use this book as a starting point and use the MATLAB® and Python implementation of AI/ML algorithms through included case studies. Experienced AI/ML researchers who want to try new algorithms can use this book and study the case studies for reference.  English | 2022 | ISBN: 0367720914 | 194 pages | True EPUB | 12.17 MB Artificial Intelligence (AI) and Machine Learning are now mainstream business tools. They are being applied across many industries to increase profits, reduce costs, save lives and improve customer experiences. Consequently, organizations which understand these tools and know how to use them are benefiting at the expense of their rivals.  English | 2021 | ISBN: 0128206012 | 270 pages | True epub | 6.59 MB Artificial Intelligence in Data Mining: Theories and Applications offers a comprehensive introduction to data mining theories, relevant AI techniques, and their many real-world applications. This book is written by experienced engineers for engineers, biomedical engineers, and researchers in neural networks, as well as computer scientists with an interest in the area.
 English | 2021 | ISBN: 3030741877 | 270 pages | True PDF EPUB | 10.93 MB This volume provides an interdisciplinary collection of essays from leaders in various fields addressing the current and future challenges arising from the implementation of AI in brain and mental health. Artificial Intelligence (AI) has the potential to transform health care and improve biomedical research. While the potential of AI in brain and mental health is tremendous, its ethical, regulatory and social impacts have not been assessed in a comprehensive and systemic way.
 English | 2022 | ISBN: 1119761697 | 256 pages | True EPUB , PDF | 19.95 MB ARTIFICIAL INTELLIGENCE FOR RENEWABLE ENERGY SYSTEMS  English | 2022 | ISBN: 303088614X | 283 pages | pdf, epub | 6.95 MB On what basis can we challenge Artificial Intelligence (AI) - its infusion, investment,
![Artificial Intelligence and Computing Logic Cognitive Technology for AI Business Analytics [True EPUB]](https://i116.fastpic.org/big/2022/0309/f9/5eeb7ea49ac27aa67819846c65a360f9.jpeg) English | 2022 | ISBN: 1774630117 | 266 pages | True EPUB | 7.62 MB Focusing on the cutting-edge applications of AI cognitive computing from neuromorphic to quantum cognition as applied to AI business analytics, this new volume explores AIs importance in managing cognitive processes along with ontological modeling concepts for venturing into new business frontiers. The volume presents a selection of significant new accomplishments in the areas of AI cognitive computing ranging from neurocognition perception and decision-making in the human braincombining neurocognitive techniques and effective computingto basic facial recognition computing models. Topics include: Agent neurocomputing techniques for facial expression recognition Computing haptic motion and ontology epistemic Characterizations of morph schemas for visual analytics Learning and perceptive computing Functional and structural neuroimaging modeling Observed links between facial recognition and affective emotional processes Interaction of cognitive and emotional processes during social decision-making Neurocognitive processing of emotional facial expressions in individuals Neurocognitive affective system for emotive robot androids Virtual reality-based affect adaptive neuromorphic computing Executive surveys indicate that cognitive adoption is very important in business strategy for success and to remain competitive. Employing cognitive-based processes provides the way to get the right information in the right hands at the right time, which is the key to winning in the digital era and to driving business value that emphasizes competitive differentiation. Several chapters of the volume address the goal of using cognitive technology to improve search capabilities, to provide personalized customer service in business and in health and wellness, and to create better workflow management. Key features: Looks at the newest frontiers on very popular AI and analytics topics Discusses new techniques for visual analytics and data filtering Shows how AI and cognitive science merges with quantum neurocognitive computing Presents ontology models with ontology preservation data filtering techniques Provides a cross-transposition on AI and digitizations for business model innovations Artificial Intelligence and Computing Logic: Cognitive Technology for AI Business Analytics is a valuable resource that informs businesses and other enterprises the value of artificial intelligence and computing logic applications. Focusing on the cutting-edge applications of AI cognitive computing from neuromorphic to quantum cognition as applied to AI business analytics, this volume explores AIs importance in managing cognitive processes along with ontological modeling concepts for venturing into new business frontiers.  English | 2022 | ISBN: 0367859408 , 978-0367859404 | 395 pages | True PDF | 22.31 MB Artificial Intelligence and Causal Inferenceaddress the recent development of relationships between artificial intelligence(AI)and causal inference. Despite significant progress in AI, a great challenge in AI development we are still facing is to understand mechanism underlying intelligence, including reasoning, planning and imagination. Understanding, transfer and generalization are major principles that give rise intelligence. One of a key component for understanding is causal inference. Causal inference includes intervention, domain shift learning, temporal structure and counterfactual thinking as major concepts to understand causation and reasoning. Unfortunately, these essential components of the causality are often overlooked by machine learning, which leads to some failure of the deep learning. AI and causal inference involve (1) using AI techniques as major tools for causal analysis and (2) applying the causal concepts and causal analysis methods to solving AI problems. The purpose of this book is to fill the gap between the AI and modern causal analysis for further facilitating the AI revolution. This book is ideal for graduate students and researchers in AI, data science, causal inference, statistics, genomics, bioinformatics and precision medicine.  English | 2021 | ISBN: 9811239916 | 457 pages | True PDF EPUB | 31.54 MB Software is an integral part of our lives today. Modern software systems are highly complex and often pose new challenges in different aspects of Software Engineering (SE).Artificial Intelligence (AI) is a growing field in computer science that has been proven effective in applying and developing AI techniques to address various SE challenges.This unique compendium covers applications of state-of-the-art AI techniques to the key areas of SE (design, development, debugging, testing, etc).All the materials presented are up-to-date. This reference text will benefit researchers, academics, professionals, and postgraduate students in AI, machine learning and software engineering.  English | 2021 | ISBN: 9811223718 | 577 pages | True PDF EPUB | 22.5 MB This English edition monograph is developed and updated from China's best-selling, and award-winning, book on Artificial Intelligence (AI). It covers the foundations as well as the latest developments of AI in a comprehensive and systematic manner. It is a valuable guide for students and researchers on artificial intelligence.A wide range of topics in AI are covered in this book with four distinct features. First of all, the book comprises a comprehensive system, covering the core technology of AI, including the basic theories and techniques of 'traditional' artificial intelligence, and the basic principles and methods of computational intelligence. Secondly, the book focuses on innovation, covering advanced learning methods for machine learning and deep learning techniques and other artificial intelligence that have been widely used in recent years. Thirdly, the theory and practice of the book are highly integrated. There are theories, techniques and methods, as well as many application examples, which will help readers to understand the artificial intelligence theory and its application development. Fourthly, the content structure of the book is quite characteristic, consisting of three parts: (i) knowledge-based artificial intelligence, (ii) data-based artificial intelligence, and (iii) artificial intelligence applications.It is closely related to the core elements of artificial intelligence, namely knowledge, data, algorithms, and computing powers. This reflects the authors' deep understanding of the artificial intelligence discipline. |
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