Stochastic Processes And Their Applications In Artificial Intelligence

Author : Ananth, Christo,Anbazhagan, N.,Goh, Mark
Publisher : IGI Global
Page : 238 pages
File Size : 43,9 Mb
Release : 2023-07-10
Category : Mathematics
ISBN : 9781668476819

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Stochastic Processes and Their Applications in Artificial Intelligence by Ananth, Christo,Anbazhagan, N.,Goh, Mark Pdf

Stochastic processes have a wide range of applications ranging from image processing, neuroscience, bioinformatics, financial management, and statistics. Mathematical, physical, and engineering systems use stochastic processes for modeling and reasoning phenomena. While comparing AI-stochastic systems with other counterpart systems, we are able to understand their significance, thereby applying new techniques to obtain new real-time results and solutions. Stochastic Processes and Their Applications in Artificial Intelligence opens doors for artificial intelligence experts to use stochastic processes as an effective tool in real-world problems in computational biology, speech recognition, natural language processing, and reinforcement learning. Covering key topics such as social media, big data, and artificial intelligence models, this reference work is ideal for mathematicians, industry professionals, researchers, scholars, academicians, practitioners, instructors, and students.

Author : M.J. Beckmann
Publisher : Springer Science & Business Media
Page : 996 pages
File Size : 49,7 Mb
Release : 1991-12-11
Category : Business & Economics
ISBN : 3540546359

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Stochastic Processes and their Applications by M.J. Beckmann Pdf

This volume deals with Stochastic tools with special reference to applications in the areas of Physics, Biology and Operations Research. Quitea few of the papers deal with the applications of the rich theory of point processes in Physics and Operations Research. A few of the papers deal with the problems of Inference and Stochastic theory. In addition papers of some leading specialists are included. These papers reflect the latest trends in these areas and will, therefore, be of value and interest to researchers in these fields.

Author : Claudio Turchetti
Publisher : IOS Press
Page : 202 pages
File Size : 44,6 Mb
Release : 2004
Category : Neural networks (Computer science)
ISBN : 4274906264

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Stochastic Models of Neural Networks by Claudio Turchetti Pdf

Author : Michael M. Richter,Sheuli Paul,Veton Këpuska,Marius Silaghi
Publisher : Springer
Page : 0 pages
File Size : 54,9 Mb
Release : 2022-10-01
Category : Computers
ISBN : 3319453718

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Signal Processing and Machine Learning with Applications by Michael M. Richter,Sheuli Paul,Veton Këpuska,Marius Silaghi Pdf

Signal processing captures, interprets, describes and manipulates physical phenomena. Mathematics, statistics, probability, and stochastic processes are among the signal processing languages we use to interpret real-world phenomena, model them, and extract useful information. This book presents different kinds of signals humans use and applies them for human machine interaction to communicate. Signal Processing and Machine Learning with Applications presents methods that are used to perform various Machine Learning and Artificial Intelligence tasks in conjunction with their applications. It is organized in three parts: Realms of Signal Processing; Machine Learning and Recognition; and Advanced Applications and Artificial Intelligence. The comprehensive coverage is accompanied by numerous examples, questions with solutions, with historical notes. The book is intended for advanced undergraduate and postgraduate students, researchers and practitioners who are engaged with signal processing, machine learning and the applications.

Author : Holger H. Hoos,Thomas Stützle
Publisher : Elsevier
Page : 677 pages
File Size : 46,5 Mb
Release : 2004-09-28
Category : Computers
ISBN : 9780080498249

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Stochastic Local Search by Holger H. Hoos,Thomas Stützle Pdf

Stochastic local search (SLS) algorithms are among the most prominent and successful techniques for solving computationally difficult problems in many areas of computer science and operations research, including propositional satisfiability, constraint satisfaction, routing, and scheduling. SLS algorithms have also become increasingly popular for solving challenging combinatorial problems in many application areas, such as e-commerce and bioinformatics. Hoos and Stützle offer the first systematic and unified treatment of SLS algorithms. In this groundbreaking new book, they examine the general concepts and specific instances of SLS algorithms and carefully consider their development, analysis and application. The discussion focuses on the most successful SLS methods and explores their underlying principles, properties, and features. This book gives hands-on experience with some of the most widely used search techniques, and provides readers with the necessary understanding and skills to use this powerful tool. Provides the first unified view of the field Offers an extensive review of state-of-the-art stochastic local search algorithms and their applications Presents and applies an advanced empirical methodology for analyzing the behavior of SLS algorithms A companion website offers lecture slides as well as source code and Java applets for exploring and demonstrating SLS algorithms

Author : Alexey Piunovskiy,Yi Zhang
Publisher : Springer Nature
Page : 356 pages
File Size : 54,7 Mb
Release : 2021-06-04
Category : Technology & Engineering
ISBN : 9783030769284

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Modern Trends in Controlled Stochastic Processes: by Alexey Piunovskiy,Yi Zhang Pdf

This book presents state-of-the-art solution methods and applications of stochastic optimal control. It is a collection of extended papers discussed at the traditional Liverpool workshop on controlled stochastic processes with participants from both the east and the west. New problems are formulated, and progresses of ongoing research are reported. Topics covered in this book include theoretical results and numerical methods for Markov and semi-Markov decision processes, optimal stopping of Markov processes, stochastic games, problems with partial information, optimal filtering, robust control, Q-learning, and self-organizing algorithms. Real-life case studies and applications, e.g., queueing systems, forest management, control of water resources, marketing science, and healthcare, are presented. Scientific researchers and postgraduate students interested in stochastic optimal control,- as well as practitioners will find this book appealing and a valuable reference. ​

Author : Jingzheng Ren,Weifeng Shen,Yi Man,Lichun Dong
Publisher : Elsevier
Page : 542 pages
File Size : 49,8 Mb
Release : 2021-06-05
Category : Technology & Engineering
ISBN : 9780128217436

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Applications of Artificial Intelligence in Process Systems Engineering by Jingzheng Ren,Weifeng Shen,Yi Man,Lichun Dong Pdf

Applications of Artificial Intelligence in Process Systems Engineering offers a broad perspective on the issues related to artificial intelligence technologies and their applications in chemical and process engineering. The book comprehensively introduces the methodology and applications of AI technologies in process systems engineering, making it an indispensable reference for researchers and students. As chemical processes and systems are usually non-linear and complex, thus making it challenging to apply AI methods and technologies, this book is an ideal resource on emerging areas such as cloud computing, big data, the industrial Internet of Things and deep learning. With process systems engineering's potential to become one of the driving forces for the development of AI technologies, this book covers all the right bases. Explains the concept of machine learning, deep learning and state-of-the-art intelligent algorithms Discusses AI-based applications in process modeling and simulation, process integration and optimization, process control, and fault detection and diagnosis Gives direction to future development trends of AI technologies in chemical and process engineering

Author : Khang, Alex,Shah, Vrushank,Rani, Sita
Publisher : IGI Global
Page : 554 pages
File Size : 50,6 Mb
Release : 2023-07-03
Category : Computers
ISBN : 9781668488539

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Handbook of Research on AI-Based Technologies and Applications in the Era of the Metaverse by Khang, Alex,Shah, Vrushank,Rani, Sita Pdf

The recent advancements in the field of the internet of things (IoT), AI, big data, blockchain, augmented reality (AR)/virtual reality (VR), cloud platforms, quantum computing, cybersecurity, and telecommunication technology enabled the promotion of conventional computer-aided industry to the metaverse ecosystem that is powered by AR/VR-driven technologies. In this paradigm shift, the integrated technologies of IoT and AI play a vital role to connect the cyberspace of computing systems and virtual environments. AR/VR supports a huge range of industrial applications such as logistics, the food industry, and manufacturing utilities. AI-Based Technologies and Applications in the Era of the Metaverse discusses essential components of the metaverse ecosystem such as concepts, methodologies, technologies, modeling, designs, statistics, implementation, and maintenance. Covering key topics such as machine learning, deep learning, quantum computing, and blockchain, this premier reference source is ideal for computer scientists, industry professionals, researchers, academicians, scholars, practitioners, instructors, and students.

Author : Alexey B. Piunovskiy
Publisher : Luniver Press
Page : 342 pages
File Size : 51,5 Mb
Release : 2010-09
Category : Mathematics
ISBN : 9781905986309

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Modern Trends in Controlled Stochastic Processes by Alexey B. Piunovskiy Pdf

World leading experts give their accounts of the modern mathematical models in the field: Markov Decision Processes, controlled diffusions, piece-wise deterministic processes etc, with a wide range of performance functionals. One of the aims is to give a general view on the state-of-the-art. The authors use Dynamic Programming, Convex Analytic Approach, several numerical methods, index-based approach and so on. Most chapters either contain well developed examples, or are entirely devoted to the application of the mathematical control theory to real life problems from such fields as Insurance, Portfolio Optimization and Information Transmission. The book will enable researchers, academics and research students to get a sense of novel results, concepts, models, methods, and applications of controlled stochastic processes.

Author : Silas Nyabwala Onyango
Publisher : LAP Lambert Academic Publishing
Page : 316 pages
File Size : 47,5 Mb
Release : 2013
Category : Electronic
ISBN : 3659390496

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Pattern Recognition of Stochastic Processes in Market Data by Silas Nyabwala Onyango Pdf

This book introduces Stochastic Processes and its applications in Finance. It also combines Artificial Intelligence with Finance. The Hough Transformation is used to identify stochastic processes in dynamical systems. Mathematics of Wiener processes are treated in detail and their applications in different markets are shown. The Hough transform is used to locate market processes where transactions occur within the market.

Author : Eswar G. Phadia
Publisher : Springer
Page : 327 pages
File Size : 44,8 Mb
Release : 2016-07-27
Category : Mathematics
ISBN : 9783319327891

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Prior Processes and Their Applications by Eswar G. Phadia Pdf

This book presents a systematic and comprehensive treatment of various prior processes that have been developed over the past four decades for dealing with Bayesian approach to solving selected nonparametric inference problems. This revised edition has been substantially expanded to reflect the current interest in this area. After an overview of different prior processes, it examines the now pre-eminent Dirichlet process and its variants including hierarchical processes, then addresses new processes such as dependent Dirichlet, local Dirichlet, time-varying and spatial processes, all of which exploit the countable mixture representation of the Dirichlet process. It subsequently discusses various neutral to right type processes, including gamma and extended gamma, beta and beta-Stacy processes, and then describes the Chinese Restaurant, Indian Buffet and infinite gamma-Poisson processes, which prove to be very useful in areas such as machine learning, information retrieval and featural modeling. Tailfree and Polya tree and their extensions form a separate chapter, while the last two chapters present the Bayesian solutions to certain estimation problems pertaining to the distribution function and its functional based on complete data as well as right censored data. Because of the conjugacy property of some of these processes, most solutions are presented in closed form. However, the current interest in modeling and treating large-scale and complex data also poses a problem – the posterior distribution, which is essential to Bayesian analysis, is invariably not in a closed form, making it necessary to resort to simulation. Accordingly, the book also introduces several computational procedures, such as the Gibbs sampler, Blocked Gibbs sampler and slice sampling, highlighting essential steps of algorithms while discussing specific models. In addition, it features crucial steps of proofs and derivations, explains the relationships between different processes and provides further clarifications to promote a deeper understanding. Lastly, it includes a comprehensive list of references, equipping readers to explore further on their own.

Author : Rajest, S. Suman,Singh, Bhopendra,Obaid, Ahmed J.,Regin, R.,Chinnusamy, Karthikeyan
Publisher : IGI Global
Page : 433 pages
File Size : 49,6 Mb
Release : 2023-09-11
Category : Computers
ISBN : 9798369313022

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Advances in Artificial and Human Intelligence in the Modern Era by Rajest, S. Suman,Singh, Bhopendra,Obaid, Ahmed J.,Regin, R.,Chinnusamy, Karthikeyan Pdf

In the realm of psychological and brain sciences, there is a growing urgency to refine individual performance using personalized interventions that account for unique cognitive and biological attributes. Yet, the quest for such tailored approaches has proven challenging, as conventional methods often fall short. The limited integration of domain expertise and human judgment curtails the potential of artificial intelligence (AI) in effectively optimizing human performance, particularly in areas like customized training, health monitoring, and cognitive enhancement. Bridging the gap between AI capabilities and the specific requirements of individuals becomes crucial in meeting this rising demand. Advances in Artificial and Human Intelligence in the Modern Era present a transformative solution to tackle the prevailing challenges at the intersection of AI and human performance enhancement. This book delves deeply into the latest empirical research, literature reviews, and methodological advancements to introduce precision AI techniques for personalized interventions. By examining how the amalgamation of domain expertise and human insights can enhance AI performance, the book establishes a comprehensive framework for modeling individual distinctions and devising effective, tailored AI approaches. Tailored for academic scholars and researchers in psychological and brain sciences, computer science, and related fields, this book provides a comprehensive exploration of pioneering advancements in the convergence of artificial and human intelligence. Its diverse chapters encompass a wide array of topics, including the identification of mental health concerns, integration of human intelligence into AI tools, enhancement of reliability, and exploration of data standards. As it fuses expertise from these two disciplines, the book paves the way for a new era of personalized interventions with the potential to revolutionize human cognitive enhancement, training, and overall well-being.

Author : Thomas, J. Joshua,Harini, S.,Pattabiraman, V.
Publisher : IGI Global
Page : 315 pages
File Size : 41,5 Mb
Release : 2023-08-25
Category : Computers
ISBN : 9781668498057

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Scalable and Distributed Machine Learning and Deep Learning Patterns by Thomas, J. Joshua,Harini, S.,Pattabiraman, V. Pdf

Scalable and Distributed Machine Learning and Deep Learning Patterns is a practical guide that provides insights into how distributed machine learning can speed up the training and serving of machine learning models, reduce time and costs, and address bottlenecks in the system during concurrent model training and inference. The book covers various topics related to distributed machine learning such as data parallelism, model parallelism, and hybrid parallelism. Readers will learn about cutting-edge parallel techniques for serving and training models such as parameter server and all-reduce, pipeline input, intra-layer model parallelism, and a hybrid of data and model parallelism. The book is suitable for machine learning professionals, researchers, and students who want to learn about distributed machine learning techniques and apply them to their work. This book is an essential resource for advancing knowledge and skills in artificial intelligence, deep learning, and high-performance computing. The book is suitable for computer, electronics, and electrical engineering courses focusing on artificial intelligence, parallel computing, high-performance computing, machine learning, and its applications. Whether you're a professional, researcher, or student working on machine and deep learning applications, this book provides a comprehensive guide for creating distributed machine learning, including multi-node machine learning systems, using Python development experience. By the end of the book, readers will have the knowledge and abilities necessary to construct and implement a distributed data processing pipeline for machine learning model inference and training, all while saving time and costs.

Author : Harold Kushner,G. George Yin
Publisher : Springer Science & Business Media
Page : 478 pages
File Size : 40,8 Mb
Release : 2006-05-04
Category : Mathematics
ISBN : 9780387217697

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Stochastic Approximation and Recursive Algorithms and Applications by Harold Kushner,G. George Yin Pdf

This book presents a thorough development of the modern theory of stochastic approximation or recursive stochastic algorithms for both constrained and unconstrained problems. This second edition is a thorough revision, although the main features and structure remain unchanged. It contains many additional applications and results as well as more detailed discussion.

Author : Jacek Fabian
Publisher : Unknown
Page : 316 pages
File Size : 49,9 Mb
Release : 2016-10-01
Category : Electronic
ISBN : 1681176483

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Stochastic Processes and Applications by Jacek Fabian Pdf

The field of stochastic processes is essentially a branch of probability theory, treating probabilistic models that evolve in time. It is best viewed as a branch of mathematics, starting with the axioms of probability and containing a rich and fascinating set of results following from those axioms. Although the results are applicable to many areas, they are best understood initially in terms of their mathematical structure and interrelationships. Applying axiomatic probability results to a real-world area requires creating a probability model for the given area. Stochastic processes were first studied rigorously in the late 19th century to aid in understanding financial markets and Brownian motion. These subjects originally had an application emphasis, the first on queueing and congestion in data networks and the second on modulation and detection of signals in the presence of noise. It has become increasingly clear that the mathematical development is applicable to a much broader set of applications in engineering, operations research, physics, biology, economics, finance, statistics, etc. Stochastic Processes and their Applications emphasizes on the theory and applications of stochastic processes. It is concerned with concepts and techniques, and is oriented towards a broad spectrum of mathematical, scientific and engineering interests. Characterization, structural properties, inference and control of stochastic processes are covered.