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This book is a collection of chapters on the state of art in the area of intelligent machines. This research provides a sound basis to make autonomous systems human-like. The contributions include an introduction to intelligent machines; supervisory control of multiple UAVs; and intelligent autonomous UAV task allocation. Also included is material on UAV path planning; dynamic path planning ; state estimation of micro air vehicles and architecture for soccer playing robots, as well as robot perception.
Book Synopsis Innovations in Intelligent Machines - 1 by : Javaan Singh Chahl
Download or read book Innovations in Intelligent Machines - 1 written by Javaan Singh Chahl and published by Springer. This book was released on 2007-07-07 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a collection of chapters on the state of art in the area of intelligent machines. This research provides a sound basis to make autonomous systems human-like. The contributions include an introduction to intelligent machines; supervisory control of multiple UAVs; and intelligent autonomous UAV task allocation. Also included is material on UAV path planning; dynamic path planning ; state estimation of micro air vehicles and architecture for soccer playing robots, as well as robot perception.
This book aims to promote a sample of current theoretical and application oriented intelligent systems research specifically in the field of neural networks computing. It presents examples of experimental and real-world investigations that demonstrate contemporary achievements and advances in the area of intelligent systems. This book will prove as a valuable source of up-to-date theoretical and application oriented research in intelligent systems for researchers and postgraduate students.
Book Synopsis Innovations in Intelligent Machines -3 by : Ivan Jordanov
Download or read book Innovations in Intelligent Machines -3 written by Ivan Jordanov and published by Springer. This book was released on 2012-09-05 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aims to promote a sample of current theoretical and application oriented intelligent systems research specifically in the field of neural networks computing. It presents examples of experimental and real-world investigations that demonstrate contemporary achievements and advances in the area of intelligent systems. This book will prove as a valuable source of up-to-date theoretical and application oriented research in intelligent systems for researchers and postgraduate students.
This research volume is a continuation of our previous volume on intelligent machines. We have laid the foundation of intelligent machines in Springer SCI Series Volume 70 by including the possible and successful applications of computational intelligence paradigms in machines for mimicking the human behaviour. The present volume includes the recent advances in intelligent paradigms and innovative applications such as document processing, language translation, English academic writing, crawling system for web pages, web-page retrieval technique, aggregate k-Nearest Neighbour for answering queries, context-aware guide, recommendation system for museum, meta-learning environment, case-based reasoning approach for adaptive modelling in exploratory learning, discussion support system for understanding research papers, system for recommending e-Learning courses, community site for supporting multiple motor-skill development, community size estimation of internet forum, lightweight reprogramming for wireless sensor networks, adaptive traffic signal controller and virtual disaster simulation system. This book is directed to engineers, scientists, researchers, professor and the undergraduate/postgraduate students who wish to explore the applications of intelligent paradigms further.
Book Synopsis Innovations in Intelligent Machines -2 by : Toyohide Watanabe
Download or read book Innovations in Intelligent Machines -2 written by Toyohide Watanabe and published by Springer Science & Business Media. This book was released on 2011-10-19 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: This research volume is a continuation of our previous volume on intelligent machines. We have laid the foundation of intelligent machines in Springer SCI Series Volume 70 by including the possible and successful applications of computational intelligence paradigms in machines for mimicking the human behaviour. The present volume includes the recent advances in intelligent paradigms and innovative applications such as document processing, language translation, English academic writing, crawling system for web pages, web-page retrieval technique, aggregate k-Nearest Neighbour for answering queries, context-aware guide, recommendation system for museum, meta-learning environment, case-based reasoning approach for adaptive modelling in exploratory learning, discussion support system for understanding research papers, system for recommending e-Learning courses, community site for supporting multiple motor-skill development, community size estimation of internet forum, lightweight reprogramming for wireless sensor networks, adaptive traffic signal controller and virtual disaster simulation system. This book is directed to engineers, scientists, researchers, professor and the undergraduate/postgraduate students who wish to explore the applications of intelligent paradigms further.
This research volume is a continuation of our previous volumes on intelligent machine. It is divided into three parts. Part I deals with big data and ontologies. It includes examples related to the text mining, rule mining and ontology. Part II is on knowledge-based systems. It includes context-centered systems, knowledge discovery, interoperability, consistency and systems of systems. The final part is on applications. The applications involve prediction, decision optimization and assessment. This book is directed to the researchers who wish to explore the field of knowledge engineering further.
Book Synopsis Innovations in Intelligent Machines-4 by : Colette Faucher
Download or read book Innovations in Intelligent Machines-4 written by Colette Faucher and published by Springer. This book was released on 2013-11-18 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: This research volume is a continuation of our previous volumes on intelligent machine. It is divided into three parts. Part I deals with big data and ontologies. It includes examples related to the text mining, rule mining and ontology. Part II is on knowledge-based systems. It includes context-centered systems, knowledge discovery, interoperability, consistency and systems of systems. The final part is on applications. The applications involve prediction, decision optimization and assessment. This book is directed to the researchers who wish to explore the field of knowledge engineering further.
Innovations in Intelligent Systems is a rare collection of the latest developments in intelligent paradigms such as knowledge-based systems, computational intelligence and hybrid combinations as well as practical applications in engineering, science, business and commerce. The book covers central topics such as intelligent multi-agent systems, data mining, case-based reasoning, and rough sets. Essential techniques to the development of intelligent machines are investigated such as pattern recognition and classification, machine learning, natural language processing, grammar, evolutionary schemes, fuzzy-neural procedures, and intelligent vision. The book also includes useful applications ranging from medical diagnosis and technical/medical language translation, to power demand forecasting and manufacturing plants. Due to its depth and breadth of the coverage and the usefulness of the techniques and applications, this book is a valuable reference for experts and students alike.
Book Synopsis Innovations in Intelligent Systems by : Ajith Abraham
Download or read book Innovations in Intelligent Systems written by Ajith Abraham and published by Springer. This book was released on 2014-03-12 with total page 468 pages. Available in PDF, EPUB and Kindle. Book excerpt: Innovations in Intelligent Systems is a rare collection of the latest developments in intelligent paradigms such as knowledge-based systems, computational intelligence and hybrid combinations as well as practical applications in engineering, science, business and commerce. The book covers central topics such as intelligent multi-agent systems, data mining, case-based reasoning, and rough sets. Essential techniques to the development of intelligent machines are investigated such as pattern recognition and classification, machine learning, natural language processing, grammar, evolutionary schemes, fuzzy-neural procedures, and intelligent vision. The book also includes useful applications ranging from medical diagnosis and technical/medical language translation, to power demand forecasting and manufacturing plants. Due to its depth and breadth of the coverage and the usefulness of the techniques and applications, this book is a valuable reference for experts and students alike.
Learn how to develop and employ an ontology, the secret weapon for successfully using artificial intelligence to create a powerful competitive advantage in your business. The AI-Powered Enterprise examines two fundamental questions: First, how will the future be different as a result of artificial intelligence? And second, what must companies do to stake their claim on that future? When the Web came along in the mid-90s, it transformed the behavior of customers and remade whole industries. Now, as part of its promise to bring revolutionary change in untold ways to human activity, artificial intelligence—AI—is about to create another complete transformation in how companies create and deliver value to customers. But despite the billions spent so far on bots and other tools, AI continues to stumble. Why can't it magically use all the data organizations generate to make them run faster and better? Because something is missing. AI works only when it understands the soul of the business. An ontology is a holistic digital model of every piece of information that matters to the business, from processes to products to people, and it's what makes the difference between the promise of AI and delivering on that promise. Business leaders who want to catch the AI wave—rather than be crushed by it—need to read The AI-Powered Enterprise. The book is the first to combine a sophisticated explanation of how AI works with a practical approach to applying AI to the problems of business, from customer experience to business operations to product development.
Book Synopsis The AI-Powered Enterprise by : Seth Earley
Download or read book The AI-Powered Enterprise written by Seth Earley and published by LifeTree Media. This book was released on 2020-04-28 with total page 203 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to develop and employ an ontology, the secret weapon for successfully using artificial intelligence to create a powerful competitive advantage in your business. The AI-Powered Enterprise examines two fundamental questions: First, how will the future be different as a result of artificial intelligence? And second, what must companies do to stake their claim on that future? When the Web came along in the mid-90s, it transformed the behavior of customers and remade whole industries. Now, as part of its promise to bring revolutionary change in untold ways to human activity, artificial intelligence—AI—is about to create another complete transformation in how companies create and deliver value to customers. But despite the billions spent so far on bots and other tools, AI continues to stumble. Why can't it magically use all the data organizations generate to make them run faster and better? Because something is missing. AI works only when it understands the soul of the business. An ontology is a holistic digital model of every piece of information that matters to the business, from processes to products to people, and it's what makes the difference between the promise of AI and delivering on that promise. Business leaders who want to catch the AI wave—rather than be crushed by it—need to read The AI-Powered Enterprise. The book is the first to combine a sophisticated explanation of how AI works with a practical approach to applying AI to the problems of business, from customer experience to business operations to product development.
This research monograph presents selected areas of applications in the field of control systems engineering using computational intelligence methodologies. A number of applications and case studies are introduced. These methodologies are increasing used in many applications of our daily lives. Approaches include, fuzzy-neural multi model for decentralized identification, model predictive control based on time dependent recurrent neural network development of cognitive systems, developments in the field of Intelligent Multiple Models based Adaptive Switching Control, designing military training simulators using modelling, simulation, and analysis for operational analyses and training, methods for modelling of systems based on the application of Gaussian processes, computational intelligence techniques for process control and image segmentation technique based on modified particle swarm optimized-fuzzy entropy.
Book Synopsis Innovations in Intelligent Machines-5 by : Valentina Emilia Balas
Download or read book Innovations in Intelligent Machines-5 written by Valentina Emilia Balas and published by Springer. This book was released on 2014-05-22 with total page 261 pages. Available in PDF, EPUB and Kindle. Book excerpt: This research monograph presents selected areas of applications in the field of control systems engineering using computational intelligence methodologies. A number of applications and case studies are introduced. These methodologies are increasing used in many applications of our daily lives. Approaches include, fuzzy-neural multi model for decentralized identification, model predictive control based on time dependent recurrent neural network development of cognitive systems, developments in the field of Intelligent Multiple Models based Adaptive Switching Control, designing military training simulators using modelling, simulation, and analysis for operational analyses and training, methods for modelling of systems based on the application of Gaussian processes, computational intelligence techniques for process control and image segmentation technique based on modified particle swarm optimized-fuzzy entropy.
Book Synopsis Innovations in Intelligent Machines-4 by : Colette Faucher
Download or read book Innovations in Intelligent Machines-4 written by Colette Faucher and published by . This book was released on 2013-11-30 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt:
This book comprises select peer-reviewed proceedings of the 6th International Conference on Innovative Computing (IC 2023). The contents focus on communication networks, business intelligence and knowledge management, web intelligence, and fields related to the development of information technology. The chapters include contributions on various topics such as databases and data mining, networking and communications, web and Internet of Things, embedded systems, soft computing, social network analysis, security and privacy, optical communication, and ubiquitous/pervasive computing. This volume will serve as a comprehensive overview of the latest advances in information technology for those working as researchers in both academia and industry.
Book Synopsis Innovative Computing Vol 1 - Emerging Topics in Artificial Intelligence by : Jason C. Hung
Download or read book Innovative Computing Vol 1 - Emerging Topics in Artificial Intelligence written by Jason C. Hung and published by Springer Nature. This book was released on 2023-06-02 with total page 1042 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book comprises select peer-reviewed proceedings of the 6th International Conference on Innovative Computing (IC 2023). The contents focus on communication networks, business intelligence and knowledge management, web intelligence, and fields related to the development of information technology. The chapters include contributions on various topics such as databases and data mining, networking and communications, web and Internet of Things, embedded systems, soft computing, social network analysis, security and privacy, optical communication, and ubiquitous/pervasive computing. This volume will serve as a comprehensive overview of the latest advances in information technology for those working as researchers in both academia and industry.
Increasingly, business leaders and managers recognize that machine learning offers their companies immense opportunities for competitive advantage. But most discussions of machine learning are intensely technical or academic, and don't offer practical information leaders can use to identify, evaluate, plan, or manage projects. Deploying Machine Learning fills that gap, helping them clarify exactly how machine learning can help them, and collaborate with technologists to actually apply it successfully. You'll learn: What machine learning is, how it compares to "big data" and "artificial intelligence," and why it's suddenly so important What machine learning can do for you: solutions for computer vision, natural language processing, prediction, and more How to use machine learning to solve real business problems -- from reducing costs through improving decision-making and introducing new products Separating hype from reality: identifying pitfalls, limitations, and misconceptions upfront Knowing enough about the technology to work effectively with your technical team Getting the data right: sourcing, collection, governance, security, and culture Solving harder problems: exploring deep learning and other advanced techniques Understanding today's machine learning software and hardware ecosystem Evaluating potential projects, and addressing workforce concerns Staffing your project, acquiring the right tools, and building a workable project plan Interpreting results -- and building an organization that can increasingly learn from data Using machine learning responsibly and ethically Preparing for tomorrow's advances The authors conclude with five chapter-length case studies: image, text, and video analysis, chatbots, and prediction applications. For each, they don't just present results: they also illuminate the process the company undertook, and the pitfalls it overcame along the way.
Book Synopsis Deploying Machine Learning by : Robbie Allen
Download or read book Deploying Machine Learning written by Robbie Allen and published by Addison-Wesley Professional. This book was released on 2019-05 with total page 99998 pages. Available in PDF, EPUB and Kindle. Book excerpt: Increasingly, business leaders and managers recognize that machine learning offers their companies immense opportunities for competitive advantage. But most discussions of machine learning are intensely technical or academic, and don't offer practical information leaders can use to identify, evaluate, plan, or manage projects. Deploying Machine Learning fills that gap, helping them clarify exactly how machine learning can help them, and collaborate with technologists to actually apply it successfully. You'll learn: What machine learning is, how it compares to "big data" and "artificial intelligence," and why it's suddenly so important What machine learning can do for you: solutions for computer vision, natural language processing, prediction, and more How to use machine learning to solve real business problems -- from reducing costs through improving decision-making and introducing new products Separating hype from reality: identifying pitfalls, limitations, and misconceptions upfront Knowing enough about the technology to work effectively with your technical team Getting the data right: sourcing, collection, governance, security, and culture Solving harder problems: exploring deep learning and other advanced techniques Understanding today's machine learning software and hardware ecosystem Evaluating potential projects, and addressing workforce concerns Staffing your project, acquiring the right tools, and building a workable project plan Interpreting results -- and building an organization that can increasingly learn from data Using machine learning responsibly and ethically Preparing for tomorrow's advances The authors conclude with five chapter-length case studies: image, text, and video analysis, chatbots, and prediction applications. For each, they don't just present results: they also illuminate the process the company undertook, and the pitfalls it overcame along the way.
