Computational Statistical Methodologies And Modeling For Artificial Intelligence
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Computational Statistical Methodologies And Modeling For Artificial Intelligence
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Author : Priyanka Harjule
language : en
Publisher: CRC Press
Release Date : 2023-03-31
Computational Statistical Methodologies And Modeling For Artificial Intelligence written by Priyanka Harjule and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-31 with Computers categories.
This book covers computational statistics-based approaches for Artificial Intelligence. The aim of this book is to provide comprehensive coverage of the fundamentals through the applications of the different kinds of mathematical modelling and statistical techniques and describing their applications in different Artificial Intelligence systems. The primary users of this book will include researchers, academicians, postgraduate students, and specialists in the areas of data science, mathematical modelling, and Artificial Intelligence. It will also serve as a valuable resource for many others in the fields of electrical, computer, and optical engineering. The key features of this book are: Presents development of several real-world problem applications and experimental research in the field of computational statistics and mathematical modelling for Artificial Intelligence Examines the evolution of fundamental research into industrialized research and the transformation of applied investigation into real-time applications Examines the applications involving analytical and statistical solutions, and provides foundational and advanced concepts for beginners and industry professionals Provides a dynamic perspective to the concept of computational statistics for analysis of data and applications in intelligent systems with an objective of ensuring sustainability issues for ease of different stakeholders in various fields Integrates recent methodologies and challenges by employing mathematical modeling and statistical techniques for Artificial Intelligence
Handbook Of Computational Social Science Volume 2
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Author : Uwe Engel
language : en
Publisher: Taylor & Francis
Release Date : 2021-11-10
Handbook Of Computational Social Science Volume 2 written by Uwe Engel and has been published by Taylor & Francis this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-10 with Computers categories.
The Handbook of Computational Social Science is a comprehensive reference source for scholars across multiple disciplines. It outlines key debates in the field, showcasing novel statistical modeling and machine learning methods, and draws from specific case studies to demonstrate the opportunities and challenges in CSS approaches. The Handbook is divided into two volumes written by outstanding, internationally renowned scholars in the field. This second volume focuses on foundations and advances in data science, statistical modeling, and machine learning. It covers a range of key issues, including the management of big data in terms of record linkage, streaming, and missing data. Machine learning, agent-based and statistical modeling, as well as data quality in relation to digital trace and textual data, as well as probability, non-probability, and crowdsourced samples represent further foci. The volume not only makes major contributions to the consolidation of this growing research field, but also encourages growth into new directions. With its broad coverage of perspectives (theoretical, methodological, computational), international scope, and interdisciplinary approach, this important resource is integral reading for advanced undergraduates, postgraduates, and researchers engaging with computational methods across the social sciences, as well as those within the scientific and engineering sectors.
Artificial Intelligence Based System Models In Healthcare
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Author : A. Jose Anand
language : en
Publisher: John Wiley & Sons
Release Date : 2024-10-29
Artificial Intelligence Based System Models In Healthcare written by A. Jose Anand and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-29 with Computers categories.
Artificial Intelligence-Based System Models in Healthcare provides a comprehensive and insightful guide to the transformative applications of AI in the healthcare system. This book is a groundbreaking exploration of the synergies between artificial intelligence and healthcare innovation. In an era where technological advancements are reshaping the landscape of medical practices, this book provides a comprehensive and insightful guide to the transformative applications of AI in healthcare systems. From conceptual foundations to practical implementations, the book serves as a roadmap for understanding the intricate relationships between AI-based system models and the evolution of healthcare delivery. The first section delves into the fundamental role of technology in reshaping the healthcare landscape. With a focus on daily life activities, decision support systems, vision-based management, and semantic frameworks, this section lays the groundwork for understanding the pivotal role of AI in revolutionizing traditional healthcare approaches. Each chapter offers a unique perspective, emphasizing the intricate integration of technology into healthcare ecosystems. The second section takes a deep dive into specific applications of AI, ranging from predictive analysis and machine learning to deep learning, image analysis, and biomedical text processing. With a focus on decision-making support systems, this section aims to demystify the complex world of AI algorithms in healthcare, offering valuable insights into their practical implications and potential impact on patient outcomes. The final section addresses the modernization of healthcare practices and envisions the future landscape of AI applications. From medical imaging and diagnostics to predicting ventilation needs in intensive care units, modernizing health record maintenance, natural language processing, chatbots for medical inquiries, secured health insurance management, and glimpses into the future, the book concludes by exploring the frontiers of AI-driven healthcare innovations. Audience This book is intended for researchers and postgraduate students in artificial intelligence and the biomedical and healthcare sectors. Medical administrators, policymakers and regulatory specialists will also have an interest.
Computational Intelligence Algorithms For The Diagnosis Of Neurological Disorders
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Author : S. N. Kumar
language : en
Publisher: CRC Press
Release Date : 2025-08-06
Computational Intelligence Algorithms For The Diagnosis Of Neurological Disorders written by S. N. Kumar and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-06 with Computers categories.
This book delves into the transformative potential of artificial intelligence (AI) and machine learning (ML) as game-changers in diagnosing and managing neurodisorder conditions. It covers a wide array of methodologies, algorithms, and applications in depth. Computational Intelligence Algorithms for the Diagnosis of Neurological Disorders equips readers with a comprehensive understanding of how computational intelligence empowers healthcare professionals in the fight against neurodisorders. Through practical examples and clear explanations, it explores the diverse applications of these technologies, showcasing their ability to analyze complex medical data, identify subtle patterns, and contribute to the development of more accurate and efficient diagnostic tools. The authors delve into the exciting possibilities of AI-powered algorithms, exploring their ability to analyze various data sources like neuroimaging scans, genetic information, and cognitive assessments. They also examine the realm of ML for pattern recognition, enabling the identification of early disease markers and facilitating timely intervention. Finally, the authors also address the critical challenges of data privacy and security, emphasizing the need for robust ethical frameworks to safeguard sensitive patient information. This book aims to spark a conversation and foster collaboration among researchers, clinicians, and technologists, and will assist radiologists and neurologists in making precise diagnoses with enhanced accuracy.
Artificial Intelligence For Intelligent Systems
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Author : Inam Ullah Khan
language : en
Publisher: CRC Press
Release Date : 2024-07-31
Artificial Intelligence For Intelligent Systems written by Inam Ullah Khan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-31 with Computers categories.
The aim of this book is to highlight the most promising lines of research, using new enabling technologies and methods based on AI/ML techniques to solve issues and challenges related to intelligent and computing systems. Intelligent computing easily collects data using smart technological applications like IoT-based wireless networks, digital healthcare, transportation, blockchain, 5.0 industry and deep learning for better decision making. AI enabled networks will be integrated in smart cities' concept for interconnectivity. Wireless networks will play an important role. The digital era of computational intelligence will change the dynamics and lifestyle of human beings. Future networks will be introduced with the help of AI technology to implement cognition in real-world applications. Cyber threats are dangerous to encode information from network. Therefore, AI-Intrusion detection systems need to be designed for identification of unwanted data traffic. This book: Provides a better understanding of artificial intelligence-based applications for future smart cities Presents a detailed understanding of artificial intelligence tools for intelligent technologies Showcases intelligent computing technologies in obtaining optimal solutions using artificial intelligence Discusses energy-efficient routing protocols using artificial intelligence for Flying ad-hoc networks (FANETs) Covers machine learning-based Intrusion detection system (IDS) for smart grid It is primarily written for senior undergraduate, graduate students, and academic researchers in the fields of electrical engineering, electronics and communication engineering, and computer engineering.
Reliability And Statistical Computing
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Author : Hoang Pham
language : en
Publisher: Springer Nature
Release Date : 2020-03-28
Reliability And Statistical Computing written by Hoang Pham and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-28 with Technology & Engineering categories.
This book presents the latest developments in both qualitative and quantitative computational methods for reliability and statistics, as well as their applications. Consisting of contributions from active researchers and experienced practitioners in the field, it fills the gap between theory and practice and explores new research challenges in reliability and statistical computing. The book consists of 18 chapters. It covers (1) modeling in and methods for reliability computing, with chapters dedicated to predicted reliability modeling, optimal maintenance models, and mechanical reliability and safety analysis; (2) statistical computing methods, including machine learning techniques and deep learning approaches for sentiment analysis and recommendation systems; and (3) applications and case studies, such as modeling innovation paths of European firms, aircraft components, bus safety analysis, performance prediction in textile finishing processes, and movie recommendation systems. Given its scope, the book will appeal to postgraduates, researchers, professors, scientists, and practitioners in a range of fields, including reliability engineering and management, maintenance engineering, quality management, statistics, computer science and engineering, mechanical engineering, business analytics, and data science.
Intelligent And Other Computational Techniques In Insurance
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Author : A. F. Shapiro
language : en
Publisher: World Scientific
Release Date : 2003
Intelligent And Other Computational Techniques In Insurance written by A. F. Shapiro and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Computers categories.
This book presents recent advances in the theory and implementation of intelligent and other computational techniques in the insurance industry. The paradigms covered encompass artificial neural networks and fuzzy systems, including clustering versions, optimization and resampling methods, algebraic and Bayesian models, decision trees and regression splines. Thus, the focus is not just on intelligent techniques, although these constitute a major component; the book also deals with other current computational paradigms that are likely to impact on the industry. The application areas include asset allocation, asset and liability management, cash-flow analysis, claim costs, classification, fraud detection, insolvency, investments, loss distributions, marketing, pricing and premiums, rate-making, retention, survival analysis, and underwriting.
Computational Intelligence And Its Applications Evolutionary Computation Fuzzy Logic Neural Network And Support Vector Machine Techniques
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Author : Hung Tan Nguyen
language : en
Publisher: World Scientific
Release Date : 2012-07-17
Computational Intelligence And Its Applications Evolutionary Computation Fuzzy Logic Neural Network And Support Vector Machine Techniques written by Hung Tan Nguyen and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-07-17 with Computers categories.
This book focuses on computational intelligence techniques and their applications — fast-growing and promising research topics that have drawn a great deal of attention from researchers over the years. It brings together many different aspects of the current research on intelligence technologies such as neural networks, support vector machines, fuzzy logic and evolutionary computation, and covers a wide range of applications from pattern recognition and system modeling, to intelligent control problems and biomedical applications. Fundamental concepts and essential analysis of various computational techniques are presented to offer a systematic and effective tool for better treatment of different applications, and simulation and experimental results are included to illustrate the design procedure and the effectiveness of the approaches./a
Artificial Intelligence And Bioinspired Computational Methods
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Author : Radek Silhavy
language : en
Publisher: Springer Nature
Release Date : 2020-08-08
Artificial Intelligence And Bioinspired Computational Methods written by Radek Silhavy and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-08 with Technology & Engineering categories.
This book gathers the refereed proceedings of the Artificial Intelligence and Bioinspired Computational Methods Section of the 9th Computer Science On-line Conference 2020 (CSOC 2020), held on-line in April 2020. Artificial intelligence and bioinspired computational methods now represent crucial areas of computer science research. The topics presented here reflect the current discussion on cutting-edge hybrid and bioinspired algorithms and their applications.
Comprehensive Guide To Statistics
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Author : Mohit Chatterjee
language : en
Publisher: Educohack Press
Release Date : 2025-02-20
Comprehensive Guide To Statistics written by Mohit Chatterjee and has been published by Educohack Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-20 with Science categories.
This comprehensive textbook offers an in-depth exploration of various topics in statistics, ranging from probability theory and statistical inference to machine learning and data analysis. It balances theoretical rigor and practical applications, catering to both undergraduate and graduate students, as well as professionals in the field of statistics and related disciplines. The book begins with foundational concepts in probability theory, covering random variables, probability distributions, and expectation. It then delves into statistical inference, discussing estimation, hypothesis testing, and regression analysis. Advanced topics like Bayesian statistics, machine learning algorithms, and resampling methods are also explored. Key strengths of this textbook include clear and concise explanations, numerous examples, and exercises to reinforce learning. The accessible yet rigorous writing style makes complex concepts understandable to readers at various levels of expertise. Modern computational tools and techniques are incorporated, emphasizing practical aspects of statistical analysis in the era of big data. Readers are encouraged to apply their knowledge using software packages like R and Python, enhancing their skills in data analysis and interpretation. This comprehensive and authoritative textbook covers a wide range of topics in statistics, making it an indispensable resource for students, researchers, and practitioners alike. It provides a solid foundation in statistical theory and its real-world applications.