Machine Learning Applications In Industrial Solid Ash

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Machine Learning Applications in Industrial Solid Ash

Author : Chongchong Qi,Qiusong Chen,Erol Yilmaz
Publisher : Elsevier
Page : 315 pages
File Size : 48,8 Mb
Release : 2023-12-01
Category : Technology & Engineering
ISBN : 9780443155253

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Machine Learning Applications in Industrial Solid Ash by Chongchong Qi,Qiusong Chen,Erol Yilmaz Pdf

Offering the ability to process large or complex datasets, machine learning (ML) holds huge potential to reshape the whole status for solid ash management and recycling. Machine Learning for Solid Ash Management and Recycling is, as far as the author knows, the first published book about ML in solid ash management and recycling. This book highlights fundamental knowledge and recent advances in this topic, offering readers new insight into how these tools can be utilized to enhance their own work. The reference begins with fundamentals in solid ash, covering the status of solid ash generation and management. The book moves on to foundational knowledge on ML in solid ash management, which provides a brief introduction of ML for solid ash applications. The reference then goes on to discuss ML approaches currently used to address problems in solid ash management and recycling, including solid ash generation, clustering analysis, origin identification, reactivity prediction, leaching potential modelling and metal recovery evaluation, etc. Finally, potential future trends and challenges in the field are discussed. Helps readers increase their existing knowledge on data mining and ML Teaches how to apply ML techniques that work best in solid ash management and recycling through providing illustrative examples and complex practice solutions Provides an accessible introduction to the current state and future possibilities for ML in solid ash management and recycling

Industrial Applications of Machine Learning

Author : Pedro Larrañaga,David Atienza,Javier Diaz-Rozo,Alberto Ogbechie,Carlos Esteban Puerto-Santana,Concha Bielza
Publisher : CRC Press
Page : 336 pages
File Size : 54,7 Mb
Release : 2018-12-12
Category : Business & Economics
ISBN : 9781351128360

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Industrial Applications of Machine Learning by Pedro Larrañaga,David Atienza,Javier Diaz-Rozo,Alberto Ogbechie,Carlos Esteban Puerto-Santana,Concha Bielza Pdf

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

Machine Learning and Artificial Intelligence with Industrial Applications

Author : Diego Carou,Antonio Sartal,J. Paulo Davim
Publisher : Springer Nature
Page : 216 pages
File Size : 48,8 Mb
Release : 2022-03-11
Category : Technology & Engineering
ISBN : 9783030910068

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Machine Learning and Artificial Intelligence with Industrial Applications by Diego Carou,Antonio Sartal,J. Paulo Davim Pdf

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.

Machine Learning in Industry

Author : Shubhabrata Datta,J. Paulo Davim
Publisher : Springer Nature
Page : 202 pages
File Size : 52,8 Mb
Release : 2021-07-24
Category : Technology & Engineering
ISBN : 9783030758479

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Machine Learning in Industry by Shubhabrata Datta,J. Paulo Davim Pdf

This book covers different machine learning techniques such as artificial neural network, support vector machine, rough set theory and deep learning. It points out the difference between the techniques and their suitability for specific applications. This book also describes different applications of machine learning techniques for industrial problems. The book includes several case studies, helping researchers in academia and industries aspiring to use machine learning for solving practical industrial problems.

Machine Learning Algorithms for Industrial Applications

Author : Santosh Kumar Das,Shom Prasad Das,Nilanjan Dey,Aboul-Ella Hassanien
Publisher : Springer Nature
Page : 321 pages
File Size : 50,7 Mb
Release : 2020-07-18
Category : Technology & Engineering
ISBN : 9783030506414

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Machine Learning Algorithms for Industrial Applications by Santosh Kumar Das,Shom Prasad Das,Nilanjan Dey,Aboul-Ella Hassanien Pdf

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.

Intelligent Systems and Machine Learning for Industry

Author : P. R Anisha,C. Kishor Kumar Reddy,Nhu Gia Nguyen,Megha Bhushan,Ashok Kumar,Marlia Mohd Hanafiah
Publisher : CRC Press
Page : 362 pages
File Size : 44,5 Mb
Release : 2022-12-21
Category : Computers
ISBN : 9781000828832

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Intelligent Systems and Machine Learning for Industry by P. R Anisha,C. Kishor Kumar Reddy,Nhu Gia Nguyen,Megha Bhushan,Ashok Kumar,Marlia Mohd Hanafiah Pdf

The book explores the concepts and challenges in developing novel approaches using the Internet of Things, intelligent systems, machine intelligence systems, and data analytics in various industrial sectors such as manufacturing, smart agriculture, smart cities, food processing, environment, defense, stock market and healthcare. Further, it discusses the latest improvements in the industrial sectors using machine intelligence learning and intelligent systems techniques, especially robotics. Features: • Highlights case studies and solutions to industrial problems using machine learning and intelligent systems. • Covers applications in smart agriculture, smart healthcare, intelligent machines for disaster management, and smart manufacturing. • Provides the latest methodologies using machine intelligence systems in the early forecasting of weather. • Examines the research challenges and identifies the gaps in data collection and data analysis, especially imagery, signal, and speech. • Provides applications of digitization and smart processing using the Internet of Things and effective intelligent agent systems in manufacturing. • Discusses a systematic and exhaustive analysis of intelligent software effort estimation models. It will serve as an ideal reference text for graduate students, post-graduate students, IT Professionals, and academic researchers in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology.

Artificial Intelligence and Machine Learning Applications in Civil, Mechanical, and Industrial Engineering

Author : Gebrail Bekdas,Sinan Melih Nigdeli,Melda Yucel
Publisher : Unknown
Page : 327 pages
File Size : 49,5 Mb
Release : 2020
Category : Artificial intelligence
ISBN : 1523128933

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Artificial Intelligence and Machine Learning Applications in Civil, Mechanical, and Industrial Engineering by Gebrail Bekdas,Sinan Melih Nigdeli,Melda Yucel Pdf

Artificial Intelligence and Machine Learning Applications in Civil, Mechanical, and Industrial Engineering

Author : Gebrail Bekdas,Sinan Melih Nigdeli,Melda Yucel
Publisher : Engineering Science Reference
Page : 312 pages
File Size : 41,7 Mb
Release : 2019
Category : Artificial intelligence
ISBN : 1799803023

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Artificial Intelligence and Machine Learning Applications in Civil, Mechanical, and Industrial Engineering by Gebrail Bekdas,Sinan Melih Nigdeli,Melda Yucel Pdf

"This book examines the application of artificial intelligence and machine learning civil, mechanical, and industrial engineering"--

Recent Advances in Material, Manufacturing, and Machine Learning

Author : Bjorn Schuller,Rajeev Gupta,Rakesh Mote,Abhishek Sharma,J.P. Giri,R.B. Chadge
Publisher : CRC Press
Page : 1016 pages
File Size : 51,6 Mb
Release : 2024-06-17
Category : Computers
ISBN : 9781040002438

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Recent Advances in Material, Manufacturing, and Machine Learning by Bjorn Schuller,Rajeev Gupta,Rakesh Mote,Abhishek Sharma,J.P. Giri,R.B. Chadge Pdf

The main aim of the 2nd international conference on recent advances in materials manufacturing and machine learning processes-2023 (RAMMML-23) is to bring together all interested academic researchers, scientists, engineers, and technocrats and provide a platform for continuous improvement of manufactur□ing, machine learning, design and materials engineering research. RAMMML 2023 received an overwhelm□ing response with more than 530 full paper submissions. After due and careful scrutiny, about 120 of them have been selected for presentation. The papers submitted have been reviewed by experts from renowned institutions, and subsequently, the authors have revised the papers, duly incorporating the suggestions of the reviewers. This has led to significant improvement in the quality of the contributions, Taylor & Francis publications, CRC Press have agreed to publish the selected proceedings of the conference in their book series of Advances in Mechanical Engineering and Interdisciplinary Sciences. This enables fast dissemina□tion of the papers worldwide and increases the scope of visibility for the research contributions of the authors.

Deep Learning Applications with Practical Measured Results in Electronics Industries

Author : Mong-Fong Horng,Hsu-Yang Kung,Chi-Hua Chen,Feng-Jang Hwang
Publisher : MDPI
Page : 272 pages
File Size : 54,9 Mb
Release : 2020-05-22
Category : Technology & Engineering
ISBN : 9783039288632

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Deep Learning Applications with Practical Measured Results in Electronics Industries by Mong-Fong Horng,Hsu-Yang Kung,Chi-Hua Chen,Feng-Jang Hwang Pdf

This book collects 14 articles from the Special Issue entitled “Deep Learning Applications with Practical Measured Results in Electronics Industries” of Electronics. Topics covered in this Issue include four main parts: (1) environmental information analyses and predictions, (2) unmanned aerial vehicle (UAV) and object tracking applications, (3) measurement and denoising techniques, and (4) recommendation systems and education systems. These authors used and improved deep learning techniques (e.g., ResNet (deep residual network), Faster-RCNN (faster regions with convolutional neural network), LSTM (long short term memory), ConvLSTM (convolutional LSTM), GAN (generative adversarial network), etc.) to analyze and denoise measured data in a variety of applications and services (e.g., wind speed prediction, air quality prediction, underground mine applications, neural audio caption, etc.). Several practical experiments were conducted, and the results indicate that the performance of the presented deep learning methods is improved compared with the performance of conventional machine learning methods.

Applications of Artificial Intelligence (AI) and Machine Learning (ML) in the Petroleum Industry

Author : Manan Shah,Ameya Kshirsagar,Jainam Panchal
Publisher : CRC Press
Page : 162 pages
File Size : 55,6 Mb
Release : 2022-09-02
Category : Technology & Engineering
ISBN : 9781000629552

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Applications of Artificial Intelligence (AI) and Machine Learning (ML) in the Petroleum Industry by Manan Shah,Ameya Kshirsagar,Jainam Panchal Pdf

Today, raw data on any industry is widely available. With the help of artificial intelligence (AI) and machine learning (ML), this data can be used to gain meaningful insights. In addition, as data is the new raw material for today’s world, AI and ML will be applied in every industrial sector. Industry 4.0 mainly focuses on the automation of things. From that perspective, the oil and gas industry is one of the largest industries in terms of economy and energy. Applications of Artificial Intelligence (AI) and Machine Learning (ML) in the Petroleum Industry analyzes the use of AI and ML in the oil and gas industry across all three sectors, namely upstream, midstream, and downstream. It covers every aspect of the petroleum industry as related to the application of AI and ML, ranging from exploration, data management, extraction, processing, real-time data analysis, monitoring, cloud-based connectivity system, and conditions analysis, to the final delivery of the product to the end customer, while taking into account the incorporation of the safety measures for a better operation and the efficient and effective execution of operations. This book explores the variety of applications that can be integrated to support the existing petroleum and adjacent sectors to solve industry problems. It will serve as a useful guide for professionals working in the petroleum industry, industrial engineers, AI and ML experts and researchers, as well as students.

Machine Learning for Sustainable Manufacturing in Industry 4.0

Author : Raman Kumar,Sita Rani,Sehijpal Singh Khangura
Publisher : CRC Press
Page : 250 pages
File Size : 43,9 Mb
Release : 2023-11-03
Category : Technology & Engineering
ISBN : 9781000986198

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Machine Learning for Sustainable Manufacturing in Industry 4.0 by Raman Kumar,Sita Rani,Sehijpal Singh Khangura Pdf

The book focuses on the recent developments in the areas of error reduction, resource optimization, and revenue growth in sustainable manufacturing using machine learning. It presents the integration of smart technologies such as machine learning in the field of Industry 4.0 for better quality products and efficient manufacturing methods. Focusses on machine learning applications in Industry 4.0 ecosystem, such as resource optimization, data analysis, and predictions. Highlights the importance of the explainable machine learning model in the manufacturing processes. Presents the integration of machine learning and big data analytics from an industry 4.0 perspective. Discusses advanced computational techniques for sustainable manufacturing. Examines environmental impacts of operations and supply chain from an industry 4.0 perspective. This book provides scientific and technological insight into sustainable manufacturing by covering a wide range of machine learning applications fault detection, cyber-attack prediction, and inventory management. It further discusses resource optimization using machine learning in industry 4.0, and explainable machine learning models for industry 4.0. It will serve as an ideal reference text for senior undergraduate, graduate students, and academic researchers in the fields including mechanical engineering, manufacturing engineering, production engineering, aerospace engineering, and computer engineering.

Artificial Intelligence in Industrial Applications

Author : Steven Lawrence Fernandes,Tarun K. Sharma
Publisher : Springer Nature
Page : 203 pages
File Size : 50,9 Mb
Release : 2021-12-07
Category : Technology & Engineering
ISBN : 9783030853839

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Artificial Intelligence in Industrial Applications by Steven Lawrence Fernandes,Tarun K. Sharma Pdf

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.

Industrial Artificial Intelligence Technologies and Applications

Author : Ovidiu Vermesan,Franz Wotawa,Mario Diaz Nava,Björn Debaillie
Publisher : CRC Press
Page : 242 pages
File Size : 46,6 Mb
Release : 2023-09-11
Category : Computers
ISBN : 9781000852035

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Industrial Artificial Intelligence Technologies and Applications by Ovidiu Vermesan,Franz Wotawa,Mario Diaz Nava,Björn Debaillie Pdf

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.

Machine Learning Adoption in Blockchain-Based Intelligent Manufacturing

Author : Om Prakash Jena,Sabyasachi Pramanik,Ahmed A. Elngar
Publisher : CRC Press
Page : 206 pages
File Size : 44,8 Mb
Release : 2022-06-22
Category : Computers
ISBN : 9781000600278

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Machine Learning Adoption in Blockchain-Based Intelligent Manufacturing by Om Prakash Jena,Sabyasachi Pramanik,Ahmed A. Elngar Pdf

This book looks at industry change patterns and innovations (such as artificial intelligence, machine learning, big data analysis, and blockchain support and efficiency technology) that are speeding up industrial transformation, industrial infrastructure, biodiversity, and productivity. This book focuses on real-world industrial applications and case studies to provide for a wider knowledge of intelligent manufacturing. It also offers insights into manufacturing, logistics, and supply chain, where systems have undergone an industrial transformation. It discusses current research of machine learning along with blockchain techniques that can fill the gap between research and industrial exposure. It goes on to cover the effects that the Fourth Industrial Revolution has on industrial infrastructures and looks at the current industry change patterns and innovations that are accelerating industrial transformation activities. Researchers, scholars, and students from different countries will appreciate this book for its real-world applications and knowledge acquisition. This book targets manufacturers, industry owners, product developers, scientists, logistics, and supply chain engineers. Focuses on real-world industrial applications and case studies to provide for a wider knowledge of intelligent manufacturing Offers insights into manufacturing, logistics, and supply chain where systems have undergone an industrial transformation Discusses current research of machine learning along with blockchain techniques that can fill the gap between research and industrial exposure Covers the effects that the 4th Industrial Revolution has on industrial infrastructures Looks at industry change patterns and innovations that are speeding up industrial transformation activities