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Book Machine Learning and Artificial Intelligence with Industrial Applications

Download or read book Machine Learning and Artificial Intelligence with Industrial Applications written by Diego Carou and published by Springer Nature. This book was released on 2022-03-11 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the tools used in machine learning (ML) and the benefits of using such tools in facilities. It focus on real life business applications, explaining the most popular algorithms easily and clearly without the use of calculus or matrix/vector algebra. Replete with case studies, this book provides a working knowledge of ML current and future capabilities and the impact it will have on every business. It demonstrates that it is also possible to carry out successful ML and AI projects in any manufacturing plant, even without fully fulfilling the five V (Volume, Velocity, Variety, Veracity and Value) usually associated with big data. This book takes a closer look at how AI and ML are also able to work for industrial area, as well as how you could adapt some of the standard tips and techniques (usually for big data) for your own needs in your SME. Organizations which first understand these tools and know how to use them will benefit at the expense of their rivals.

Book Artificial Intelligence and Industrial Applications

Download or read book Artificial Intelligence and Industrial Applications written by Tawfik Masrour and published by Springer Nature. This book was released on 2020-09-01 with total page 442 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers the refereed proceedings of the Artificial Intelligence and Industrial Applications (A2IA’2020), the first installment of an annual international conference organized by the ENSAM-Meknes at Moulay Ismail University, Morocco. The 30 papers presented here were carefully reviewed and selected from 141 submissions by an international scientific committee. They address various aspects of artificial intelligence such as smart manufacturing, smart maintenance, smart supply chain management, supervised learning, unsupervised learning, reinforcement learning, graph-based and semi-supervised learning, neural networks, deep learning, planning and optimization, and other AI applications. The book is intended for AI experts, offering them a valuable overview of the status quo and a global outlook for the future, with many new and innovative ideas and recent important developments in AI applications, both of a foundational and practical nature. It will also appeal to non-experts who are curious about this timely and important subject.

Book Artificial Intelligence in Industrial Applications

Download or read book Artificial Intelligence in Industrial Applications written by Steven Lawrence Fernandes and published by Springer Nature. This book was released on 2021-12-07 with total page 203 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book highlights the analytics and optimization issues in industry, to propose new approaches, and to present applications of innovative approaches in real facilities. In the past few decades there has been an exponential rise in the application of artificial intelligence for solving complex and intricate problems arising in industrial domain. The versatility of these techniques have made them a favorite among scientists and researchers working in diverse areas. The book is edited to serve a broad readership, including computer scientists, medical professionals, and mathematicians interested in studying computational intelligence and their applications. It will also be helpful for researchers, graduate and undergraduate students with an interest in the fields of Artificial Intelligence and Industrial problems. This book will be a useful resource for researchers, academicians as well as professionals interested in the highly interdisciplinary field of Artificial Intelligence.

Book Artificial Intelligence and Industrial Applications

Download or read book Artificial Intelligence and Industrial Applications written by Tawfik Masrour and published by Springer Nature. This book was released on 2020-07-18 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers selected papers from Artificial Intelligence and Industrial Applications (A2IA’2020), the first installment of an annual international conference organized by ENSAM-Meknes at Moulay Ismail University, Morocco. The 29 papers presented here were carefully reviewed and selected from 141 submissions by an international scientific committee. They address various aspects of artificial intelligence such as digital twin, multiagent systems, deep learning, image processing and analysis, control, prediction, modeling, optimization and design, as well as AI applications in industry, health, energy, agriculture, and education. The book is intended for AI experts, offering them a valuable overview and global outlook for the future, and highlights a wealth of innovative ideas and recent, important advances in AI applications, both of a foundational and practical nature. It will also appeal to non-experts who are curious about this timely and important subject.

Book Neural Networks  Artificial Intelligence and Industrial Applications

Download or read book Neural Networks Artificial Intelligence and Industrial Applications written by Bert Kappen and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 398 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neural networks is a field of research which has enjoyed rapid expansion in both the academic and industrial research communities. This volume contains papers presented at the Third Annual SNN Symposium on Neural Networks to be held in Nijmegen, The Netherlands, 14 - 15 September 1995. The papers are divided into two sections: the first gives an overview of new developments in neurobiology, the cognitive sciences, robotics, vision and data modelling. The second presents working neural network solutions to real industrial problems, including process control, finance and marketing. The resulting volume gives a comprehensive view of the state of the art in 1995 and will provide essential reading for postgraduate students and academic/industrial researchers.

Book Deep Neural Network Applications

Download or read book Deep Neural Network Applications written by Hasmik Osipyan and published by CRC Press. This book was released on 2022-04-28 with total page 158 pages. Available in PDF, EPUB and Kindle. Book excerpt: The world is on the verge of fully ushering in the fourth industrial revolution, of which artificial intelligence (AI) is the most important new general-purpose technology. Like the steam engine that led to the widespread commercial use of driving machineries in the industries during the first industrial revolution; the internal combustion engine that gave rise to cars, trucks, and airplanes; electricity that caused the second industrial revolution through the discovery of direct and alternating current; and the Internet, which led to the emergence of the information age, AI is a transformational technology. It will cause a paradigm shift in the way’s problems are solved in every aspect of our lives, and, from it, innovative technologies will emerge. AI is the theory and development of machines that can imitate human intelligence in tasks such as visual perception, speech recognition, decision-making, and human language translation. This book provides a complete overview on the deep learning applications and deep neural network architectures. It also gives an overview on most advanced future-looking fundamental research in deep learning application in artificial intelligence. Research overview includes reasoning approaches, problem solving, knowledge representation, planning, learning, natural language processing, perception, motion and manipulation, social intelligence and creativity. It will allow the reader to gain a deep and broad knowledge of the latest engineering technologies of AI and Deep Learning and is an excellent resource for academic research and industry applications.

Book Artificial Intelligence and Industrial Applications

Download or read book Artificial Intelligence and Industrial Applications written by Tawfik Masrour and published by Springer Nature. This book was released on 2023-10-16 with total page 493 pages. Available in PDF, EPUB and Kindle. Book excerpt: Amid the dynamic growth of artificial intelligence, this book presents a collection of findings and advancements from the second edition of the A2IA-Artificial Intelligence and Industrial Applications conference. The conference, hosted by ENSAM-Meknès at Moulay Ismail University, Morocco, fosters knowledge exchange in AI, focusing primarily on its industrial applications. Covering a wide range of topics, the book highlights the adaptable nature of AI and its increasing impact on industrial sectors. It brings together contributions from an international cohort of researchers, discussing themes such as intelligent manufacturing and maintenance, intelligent supply chain management, various modes of learning including supervised, unsupervised, reinforcement, semi-supervised, and graph-based, as well as neural networks, deep learning, planning, and optimization. A defining feature of this edition is its extensive scope and emphasis on the practical applications of AI, along with its foundational elements. It facilitates an understanding of AI's current state and potential future direction, showcasing recent developments that bridge the gap between theory and practice. Designed for a diverse readership, this book is of interest to AI practitioners, academics, and enthusiasts, as well as to those new to the field. It provides an opportunity to explore AI's critical role in industrial applications, and the practical insights it offers are likely to be beneficial for decision-making within industrial settings.

Book Industrial Applications of Machine Learning

Download or read book Industrial Applications of Machine Learning written by Pedro Larrañaga and published by CRC Press. This book was released on 2018-12-12 with total page 309 pages. Available in PDF, EPUB and Kindle. Book excerpt: Industrial Applications of Machine Learning shows how machine learning can be applied to address real-world problems in the fourth industrial revolution, and provides the required knowledge and tools to empower readers to build their own solutions based on theory and practice. The book introduces the fourth industrial revolution and its current impact on organizations and society. It explores machine learning fundamentals, and includes four case studies that address a real-world problem in the manufacturing or logistics domains, and approaches machine learning solutions from an application-oriented point of view. The book should be of special interest to researchers interested in real-world industrial problems. Features Describes the opportunities, challenges, issues, and trends offered by the fourth industrial revolution Provides a user-friendly introduction to machine learning with examples of cutting-edge applications in different industrial sectors Includes four case studies addressing real-world industrial problems solved with machine learning techniques A dedicated website for the book contains the datasets of the case studies for the reader's reproduction, enabling the groundwork for future problem-solving Uses of three of the most widespread software and programming languages within the engineering and data science communities, namely R, Python, and Weka

Book Industrial Applications of Neural Networks

Download or read book Industrial Applications of Neural Networks written by Ian F. Croall and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: Neural network technology encompasses a class of methods which attempt to mimic the basic structures used in the brain for information processing. Thetechnology is aimed at problems such as pattern recognition which are difficult for traditional computational methods. Neural networks have potential applications in many industrial areas such as advanced robotics, operations research, and process engineering. This book is concerned with the application of neural network technology to real industrial problems. It summarizes a three-year collaborative international project called ANNIE (Applications of Neural Networks for Industry in Europe) which was jointly funded by industry and the European Commission within the ESPRIT programme. As a record of a working project, the book gives an insight into the real problems faced in taking a new technology from the workbench into a live industrial application, and shows just how it can be achieved. It stresses the comparison between neural networks and conventional approaches. Even the non-specialist reader will benefit from understanding the limitations as well as the advantages of the new technology.

Book Industrial Applications of Neural Networks

Download or read book Industrial Applications of Neural Networks written by Lakhmi C. Jain and published by CRC Press. This book was released on 1998-10-28 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: Industrial Applications of Neural Networks explores the success of neural networks in different areas of engineering endeavors. Each chapter shows how the power of neural networks can be exploited in modern engineering applications. The first seven chapters focus on image processing as well as industrial or manufacturing perspectives. Topics discussed include: shape recognition shape from shading aircraft detection in SAR images visualization of high-dimensional data bases of industrial systems 3-D object learning and recognition from multiple 2-D views fingerprint classification performance optimization in flexible manufacturing systems The remaining chapters address issues and applications in the expansive area of multimedia communications as well as mobile and cellular communications.

Book AI and Learning Systems

Download or read book AI and Learning Systems written by Konstantinos Kyprianidis and published by BoD – Books on Demand. This book was released on 2021-02-17 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over the last few years, interest in the industrial applications of AI and learning systems has surged. This book covers the recent developments and provides a broad perspective of the key challenges that characterize the field of Industry 4.0 with a focus on applications of AI. The target audience for this book includes engineers involved in automation system design, operational planning, and decision support. Computer science practitioners and industrial automation platform developers will also benefit from the timely and accurate information provided in this work. The book is organized into two main sections comprising 12 chapters overall: •Digital Platforms and Learning Systems •Industrial Applications of AI

Book Machine Learning Algorithms for Industrial Applications

Download or read book Machine Learning Algorithms for Industrial Applications written by Santosh Kumar Das and published by Springer Nature. This book was released on 2020-07-18 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book explores several problems and their solutions regarding data analysis and prediction for industrial applications. Machine learning is a prominent topic in modern industries: its influence can be felt in many aspects of everyday life, as the world rapidly embraces big data and data analytics. Accordingly, there is a pressing need for novel and innovative algorithms to help us find effective solutions in industrial application areas such as media, healthcare, travel, finance, and retail. In all of these areas, data is the crucial parameter, and the main key to unlocking the value of industry. The book presents a range of intelligent algorithms that can be used to filter useful information in the above-mentioned application areas and efficiently solve particular problems. Its main objective is to raise awareness for this important field among students, researchers, and industrial practitioners.

Book Intelligent Systems in Industrial Applications

Download or read book Intelligent Systems in Industrial Applications written by Martin Stettinger and published by Springer Nature. This book was released on 2021-02-03 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a selection of papers from the industrial track of ISMIS 2020. The selection emphasizes broad applicability of artificial intelligence (AI) technologies in various industrial fields. The aim of the book is to fertilize preliminary ideas of readers on the application of AI by means of already successfully implemented application examples. Furthermore, the development of new ideas and concepts shall be motivated by the variety of different application examples. The spectrum of the presented contributions ranges from education and training, industrial applications in production and logistics to the development of new approaches in basic research, which will further expand the possibilities of future applications of AI in industrial settings. This broad spectrum gives readers working in the industrial as well as the academic field a good overview of the state of the art in the field of methodologies for intelligent systems.

Book Embedded Artificial Intelligence

Download or read book Embedded Artificial Intelligence written by Ovidiu Vermesan and published by CRC Press. This book was released on 2023-05-05 with total page 143 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent technological developments in sensors, edge computing, connectivity, and artificial intelligence (AI) technologies have accelerated the integration of data analysis based on embedded AI capabilities into resource-constrained, energy-efficient hardware devices for processing information at the network edge. Embedded AI combines embedded machine learning (ML) and deep learning (DL) based on neural networks (NN) architectures such as convolutional NN (CNN), or spiking neural network (SNN) and algorithms on edge devices and implements edge computing capabilities that enable data processing and analysis without optimised connectivity and integration, allowing users to access data from various sources. Embedded AI efficiently implements edge computing and AI processes on resource-constrained devices to mitigate downtime and service latency, and it successfully merges AI processes as a pivotal component in edge computing and embedded system devices. Embedded AI also enables users to reduce costs, communication, and processing time by assembling data and by supporting user requirements without the need for continuous interaction with physical locations. This book provides an overview of the latest research results and activities in industrial embedded AI technologies and applications, based on close cooperation between three large-scale ECSEL JU projects, AI4DI, ANDANTE, and TEMPO. The book’s content targets researchers, designers, developers, academics, post-graduate students and practitioners seeking recent research on embedded AI. It combines the latest developments in embedded AI, addressing methodologies, tools, and techniques to offer insight into technological trends and their use across different industries.

Book Industrial Artificial Intelligence Technologies and Applications

Download or read book Industrial Artificial Intelligence Technologies and Applications written by Ovidiu Vermesan and published by CRC Press. This book was released on 2023-09-11 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: The advances in industrial edge artificial intelligence (AI) are transforming the way industrial equipment and machines interact with the real world, with other machines and humans during manufacturing processes. These advances allow Industrial Internet of Things (IIoT) and edge devices to make decisions during the manufacturing processes using sensors and actuators. Digital transformation is reshaping the manufacturing industry, and industrial edge AI aims to combine the potential advantages of edge computing (low latency times, reduced bandwidth, distributed architecture, improved trustworthiness, etc.) with the benefits of AI (intelligent processing, predictive solutions, classification, reasoning, etc.). The industrial environments allow the deployment of highly distributed intelligent industrial applications in remote sites that require reliable connectivity over wireless and cellular connections. Intelligent connectivity combines IIoT, wireless/cellular and AI technologies to support new autonomous industrial applications by enabling AI capabilities at the edge and allowing manufacturing companies to improve operational efficiency and reduce risks and costs for industrial applications. There are several critical issues to consider when introducing AI to industrial IoT applications considering training AI models at the edge, the deployment of the AI-trained inferencing models on the target edge hardware platforms, and the benchmarking of solutions compared to other implementations. Next-generation trustworthy industrial AI systems offer dependability in terms of their design, transparency, explainability, verifiability, and standardised industrial solutions can be implemented in various applications across different industrial sectors. New AI techniques such as embedded machine learning (ML) and deep learning (DL), capture edge data, employ AI models, and deploy these in hardware target edge devices, from ultra-low-power microcontrollers to embedded devices, gateways, and on-premises servers for industrial applications. These techniques reduce latency, increase scalability, reliability, and resilience; and optimise wireless connectivity, greatly expanding the capabilities of the IIoT. This book provides an overview of the latest research results and activities in industrial AI technologies and applications, based on the innovative research, developments and ideas generated by the ECSEL JU AI4DI, ANDANTE and TEMPO projects. The authors describe industrial AI's challenges, the approaches adopted, and the main industrial systems and applications to give the reader extensive insight into the technical nature of this field. The chapters provide insightful material on industrial AI technologies and applications. This book is a valuable resource for researchers, post-graduate students, practitioners, and technoloyg developers interested in gaining insight into industrial edge AI, the IIoT, embedded machine and deep learning, new technologies, and solutions to advance intelligent processing at the edge.

Book Machine Learning and Deep Learning in Real Time Applications

Download or read book Machine Learning and Deep Learning in Real Time Applications written by Mahrishi, Mehul and published by IGI Global. This book was released on 2020-04-24 with total page 344 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial intelligence and its various components are rapidly engulfing almost every professional industry. Specific features of AI that have proven to be vital solutions to numerous real-world issues are machine learning and deep learning. These intelligent agents unlock higher levels of performance and efficiency, creating a wide span of industrial applications. However, there is a lack of research on the specific uses of machine/deep learning in the professional realm. Machine Learning and Deep Learning in Real-Time Applications provides emerging research exploring the theoretical and practical aspects of machine learning and deep learning and their implementations as well as their ability to solve real-world problems within several professional disciplines including healthcare, business, and computer science. Featuring coverage on a broad range of topics such as image processing, medical improvements, and smart grids, this book is ideally designed for researchers, academicians, scientists, industry experts, scholars, IT professionals, engineers, and students seeking current research on the multifaceted uses and implementations of machine learning and deep learning across the globe.