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Intelligent Decision Technologies: Proceedings of the 13th KES-IDT 2021 Conference (Smart Innovation, Systems and Technologies #238)
by Lakhmi C. Jain Robert J. Howlett Ireneusz CzarnowskiThis book contains selected papers from the KES-IDT-2021 conference, being held as a virtual conference in June 14–16, 2021. The KES-IDT is an interdisciplinary conference with opportunities for the presentation of new research results and discussion about them under the common title "Intelligent Decision Technologies". The conference has been creating for years a platform for knowledge transfer and the generation of new ideas in the field of intelligent decision making.The range of topics discussed during the conference covered methods of classification, prediction, data analysis, big data, decision support, knowledge engineering, modeling, social networks and many more in areas such as finance, economy, management and transportation. The discussed topics covered also decision making for problems regarding the electric vehicle industry.The book contains also several sections devoted to specific topics, such asAdvances in intelligent data processing and its applicationsMulti-criteria decision analysis methodsKnowledge engineering in large-scale systemsHigh-dimensional data analysisSpatial data analysis and sparse estimationInnovative technologies and applications in computer intelligenceIntelligent diagnosis and monitoring of systemsDecision making theory for economics.
Intelligent Decision Technologies: Proceedings of the 14th KES-IDT 2022 Conference (Smart Innovation, Systems and Technologies #309)
by Lakhmi C. Jain Robert J. Howlett Ireneusz CzarnowskiThis book gathers selected papers from the KES-IDT 2022 Conference, held in Rhodes, Greece on June 20–22, 2022. The book presents and discusses the latest research results and generates new ideas in the field of intelligent decision-making. The range of topics discussed are classification, prediction, data analysis, big data, data science, decision support, knowledge engineering, and modeling in diverse areas such as finance, cybersecurity, economics, health, management, and transportation. The problems in Industry 4.0 and IoT are also addressed. The book contains several sections devoted to specific topics, such as intelligent data processing and its applications, high-dimensional data analysis and its applications, multi-criteria decision analysis—theory and applications, large-scale systems for intelligent decision-making and knowledge engineering, decision technologies and related topics in big data analysis of social and financial issues, and decision-making theory for economics.
Intelligent Decision Technologies: Proceedings of the 15th KES-IDT 2023 Conference (Smart Innovation, Systems and Technologies #352)
by Lakhmi C. Jain Ireneusz Czarnowski R. J. HowlettThis book gathers selected papers from the KES-IDT 2023 Conference, held in Rome, Italy, on June 14–16, 2023. The book presents and discusses the latest research results and generates new ideas in the field of intelligent decision-making. The range of topics discussed is classification, prediction, data analysis, big data, data science, decision support, knowledge engineering and modeling in diverse areas such as finance, cybersecurity, economics, health, management and transportation. The problems in industry 4.0 and IoT are also addressed. The book contains several sections devoted to specific topics, such as intelligent data processing and its applications, high-dimensional data analysis and its applications, multi-criteria decision analysis—theory and applications, large-scale systems for intelligent decision-making and knowledge engineering, decision technologies and related topics in big data analysis of social and financial issues and decision-making theory for economics.
Intelligent Decision Technologies: Proceedings of the 16th KES-IDT 2024 Conference (Smart Innovation, Systems and Technologies #411)
by Lakhmi C. Jain Robert J. Howlett Ireneusz CzarnowskiThis book gathers selected papers from the KES-IDT 2024 conference, held in Madeira, Portugal, on June 19–21, 2024. The book presents and discusses the latest research results and generates new ideas in the field of intelligent decision-making. The range of topics discussed is classification, prediction, data analysis, big data, data science, decision support, knowledge engineering, and modeling in diverse areas such as finance, cybersecurity, economics, health, management, and transportation. The problems in Industry 4.0 and IoT are also addressed. The book contains several sections devoted to specific topics, such as intelligent data processing and its applications, high-dimensional data analysis and its applications, multi-criteria decision analysis—theory and applications, large-scale systems for intelligent decision-making and knowledge engineering, decision technologies, and related topics in big data analysis of social and financial issues and decision-making theory for economics.
Intelligent Decision Technology Support in Practice
by Junzo Watada Lakhmi C. Jain Robert J. Howlett Gloria Phillips-Wren Jeffrey W. Tweedale Rui Neves-SilvaThis book contains a collection of innovative chapters emanating from topics raised during the 5th KES International Conference on Intelligent Decision Technologies (IDT), held during 2013 at Sesimbra, Portugal. The authors were invited to expand their original papers into a plethora of innovative chapters espousing IDT methodologies and applications. This book documents leading-edge contributions, representing advances in Knowledge-Based and Intelligent Information and Engineering System. It acknowledges that researchers recognize that society is familiar with modern Advanced Information Processing and increasingly expect richer IDT systems. Each chapter concentrates on the theory, design, development, implementation, testing or evaluation of IDT techniques or applications. Anyone that wants to work with IDT or simply process knowledge should consider reading one or more chapters and focus on their technique of choice. Most readers will benefit from reading additional chapters to access alternative technique that often represent alternative approaches. This book is suitable for anyone interested in or already working with IDT or Intelligent Decision Support Systems. It is also suitable for students and researchers seeking to learn more about modern Artificial Intelligence and Computational Intelligence techniques that support decision-making in modern computer systems.
Intelligent Decision-making Models for Production and Retail Operations
by Zhaoxia GuoThis book provides an overview of intelligent decision-making techniques and discusses their application in production and retail operations. Manufacturing and retail enterprises have stringent standards for using advanced and reliable techniques to improve decision-making processes, since these processes have significant effects on the performance of relevant operations and the entire supply chain. In recent years, researchers have been increasingly focusing attention on using intelligent techniques to solve various decision-making problems. The opening chapters provide an introduction to several commonly used intelligent techniques, such as genetic algorithm, harmony search, neural network and extreme learning machine. The book then explores the use of these techniques for handling various production and retail decision-making problems, such as production planning and scheduling, assembly line balancing, and sales forecasting.
Intelligent Designs, Innovations and Sustainability in Agriculture 4.0
by Vania V. Estrela Anand B. Deshpande Asiya KhanFeeding an expanding population in light of environmental preservation and keeping production lean is a considerable challenge. Sustainable and Precise Agriculture relying on Industry 4.0 (Agri4) points toward creating strategic collaborations, innovations, and alternative approaches to old concerns, and incorporating solutions from other expertise domains. It requires intensive efforts from governments, investors, investigators, and developers. These initiatives address many problems while connecting more agrarians and their communities. Agri4 entails key agribusiness developments, viz. precision agriculture, biotech, IoT, and Big Data, to augment efficiency in dealing with growing population and climate change. Agri4 is likely to yield improvements such as sustainable practices education, environmental residue reduction, seed improvement, and traditional agricultural knowledge usage, among others. It promotes sustainable food production, community development, and scientific literacy by fostering effective natural resource administration.This book explores the transformative impact of Agriculture 4.0, guiding readers through the integration of digital technologies and sustainable practices into modern farming. It discusses how innovations like AI and the IoT are revolutionizing agriculture, enhancing connectivity, precision, and ecological awareness. The intended readers of the book include agricultural professionals, researchers, tech innovators, policymakers, and students. It caters to those interested in the convergence of modern technology and farming, particularly in advancing sustainable practices and understanding the future of agriculture in the digital age.
Intelligent Diagnosis and Prognosis of Industrial Networked Systems (Automation and Control Engineering #44)
by Tong Heng Lee Frank L. Lewis Chee Khiang Pang Zhao Yang DongIn an era of intense competition where plant operating efficiencies must be maximized, downtime due to machinery failure has become more costly. To cut operating costs and increase revenues, industries have an urgent need to predict fault progression and remaining lifespan of industrial machines, processes, and systems. An engineer who mounts an acoustic sensor onto a spindle motor wants to know when the ball bearings will wear out without having to halt the ongoing milling processes. A scientist working on sensor networks wants to know which sensors are redundant and can be pruned off to save operational and computational overheads. These scenarios illustrate a need for new and unified perspectives in system analysis and design for engineering applications. Intelligent Diagnosis and Prognosis of Industrial Networked Systems proposes linear mathematical tool sets that can be applied to realistic engineering systems. The book offers an overview of the fundamentals of vectors, matrices, and linear systems theory required for intelligent diagnosis and prognosis of industrial networked systems. Building on this theory, it then develops automated mathematical machineries and formal decision software tools for real-world applications. The book includes portable tool sets for many industrial applications, including: Forecasting machine tool wear in industrial cutting machines Reduction of sensors and features for industrial fault detection and isolation (FDI) Identification of critical resonant modes in mechatronic systems for system design of R&D Probabilistic small-signal stability in large-scale interconnected power systems Discrete event command and control for military applications The book also proposes future directions for intelligent diagnosis and prognosis in energy-efficient manufacturing, life cycle assessment, and systems of systems architecture. Written in a concise and accessible style, it presents tools that are mathematically rigorous but not involved. Bridging academia, research, and industry, this reference supplies the know-how for engineers and managers making decisions about equipment maintenance, as well as researchers and students in the field.
Intelligent Distributed Computing IX
by Amal El Fallah Seghrouchni Costin Badica Paulo Novais David Camacho Cesar AnalideThis book represents the combined peer-reviewed proceedings of the ninth International Symposium on Intelligent Distributed Computing - IDC'2015, of the Workshop on Cyber Security and Resilience of Large-Scale Systems - WSRL'2015, and of the International Workshop on Future Internet and Smart Networks - FI&SN'2015. All the events were held in Guimarães, Portugal during October 7th-9th, 2015. The 46 contributions published in this book address many topics related to theory and applications of intelligent distributed computing, including: Intelligent Distributed Agent-Based Systems, Ambient Intelligence and Social Networks, Computational Sustainability, Intelligent Distributed Knowledge Representation and Processing, Smart Networks, Networked Intelligence and Intelligent Distributed Applications, amongst others.
Intelligent Distributed Computing XIII (Studies in Computational Intelligence #868)
by Costin Badica Igor Kotenko Mirjana Ivanovic Vasily Desnitsky Didier El BazThis book gathers research contributions on recent advances in intelligent and distributedcomputing. A major focus is placed on new techniques and applications for several highlydemanded research directions: Internet of Things, Cloud Computing and Big Data, Data Mining and Machine Learning, Multi-agent and Service-Based Distributed Systems, Distributed Algorithms and Optimization, Modeling Operational Processes, Social Network Analysis and Inappropriate Content Counteraction, Cyber-Physical Security and Safety, Intelligent Distributed Decision Support Systems, Intelligent Human-Machine Interfaces, VisualAnalytics and others. The book represents the peer-reviewed proceedings of the 13thInternational Symposium on Intelligent Distributed Computing (IDC 2019), which was held in St. Petersburg, Russia, from October 7 to 9, 2019.
Intelligent Distributed Computing XIV (Studies in Computational Intelligence #1026)
by David Camacho Mario Versaci Domenico Rosaci Giuseppe M. L. SarnéThis book collects 43 regular papers received from 18 countries that present innovative advances in intelligent and distributed computing, encompassing both architectural and algorithmic results related to these fields. Significant attention is given to new models, techniques, and applications for distributed intelligent architectures and high-performance architectures, machine learning techniques, Internet of Things, blockchain, intelligent transport systems, data analytics, trust and reputation systems, and many others. The book includes the peer-reviewed proceedings of the 14th International Symposium on Intelligent Distributed Computing (IDC 2021), which was held in online mode due to the COVSARS2 pandemic situation, during September 16–18, 2021. The IDC 2021 event included sessions on Internet of Things, data analytics, machine learning, multi-agent systems, algorithms, future intelligent transport solutions, blockchain, intelligent distributed computing for cyber-physical security, and security and trust and reputation in intelligent environments.
Intelligent Distributed Computing XV (Studies in Computational Intelligence #1089)
by Costin Bădică Lars Braubach Kai JanderThis book includes the latest research in the diverse field of intelligent distributed computing, covering a multitude of aspects in both distributed computing and intelligent systems. It includes contributions in machine learning, distributed systems & agents, text- and research-centric applications, social systems, and smart cities. It was written by leading experts in the field, who presented their work as part of the 15th International Symposium on Intelligent Distributed Computing (IDC 2022).
Intelligent Distributed Computing XVI: 16th International Symposium on Intelligent Distributed Computing, IDC 2023 (Studies in Computational Intelligence #1138)
by Michael Köhler-Bußmeier Wolfgang Renz Jan SudeikatThis book presents selected contributions to the 16th Symposium on Intelligent Distributed Computing (IDC’23) held from September 13 to 15, 2023, at the HAW Hamburg, Germany. This unique collection of papers presents the latest findings, research achievements and ideas in the area of Intelligent Distributed Computing provided by researchers and practitioners from both distributed computing and intelligent computing communities. Distributed computing covers methods and technology to build complex computational systems composed of collaborating software components scattered across diverse computational elements. Intelligent computing offers a hybrid palette of methods, techniques and their applications ranging from classical artificial intelligence, information and data sciences, multi-agent technologies or computational intelligence to more recent trends such as swarm intelligence, bio-inspired computation, cloud computing, machine learning or social/cyber-physical trust and security.
Intelligent Document Capture with Ephesoft
by Michael Muller Ike KavasWritten in easy to follow manner, this book is a complete guide to Document capture with Ephesoft,This book is intended for information technology professionals interested in installing and configuring Ephesoft for their organization, but it is a valuable resource for anyone interested in learning about document capture in general.
Intelligent Document Capture with Ephesoft - Second Edition
by Ike Kavas Pat MyersAutomate the processing of scanned and digital documents by improving accuracy using web-based open and modern intelligent document capture software About This Book * Learn how to implement the benefits of intelligent document capture using Ephesoft Enterprise 4 * Leverage the power of the open platform to run it as a classic intake capture system to make your current portals or applications more intelligent * A practical guide providing examples for optimizing document capture for your business Who This Book Is For This book is intended for information technology professionals interested in installing and configuring Ephesoft Enterprise for their organization, but it is a valuable resource for anyone interested in learning about intelligent document capture. What You Will Learn * Discover the benefits of using intelligent document capture in your work place * Learn to capture, classify, and separate any type of document * Extract important information from your documents * Transfer the documents and data into your content management system * Customize Ephesoft to meet your unique business requirements * Understand the integration techniques using the Ephesoft web services API * Convert your paper archive to electronic records efficiently * Automate business processes that depend on documents in paper, fax, or email attachment format * Implement distributed capture for mailroom automation In Detail Every organization, public or private, processes documents in various formats, especially paper and fax formats. Processing documents manually is an expensive and time-consuming endeavor. Ephesoft Enterprise is a modern document capture solution that allows an organization to automate the business process. It uses powerful technology to classify and capture the vital information from the document's content. This helps to minimize the time your company spends on reviewing and processing any physical and electronic documents. This book teaches you about document capture in general and implementation of document capture using Ephesoft. Start by learning about document capture and how Ephesoft revolutionized the industry. Progress to a tour of key features, including operator and administrator interfaces and then learn to configure Ephesoft to process your business's specific document types and extract content from those documents. You will also get to know the advanced customization techniques that make Ephesoft accommodate your unique business needs. Finally, the book concludes by teaching you how to embed the classification and extraction functionality using Ephesoft's web services. By the end, you will learn to optimize the processing of your documents, saving your company time and money. Style and approach This is a step-by-step guide on how to configure and use Ephesoft using an accounts payable use case. The book will start with basic techniques and progress to more advanced features that allow you to leverage the power for a modern powerful capture system.
Intelligent Document Processing with AWS AI/ML: A comprehensive guide to building IDP pipelines with applications across industries
by Sonali SahuBuild real-world artificial intelligence applications across industries with the help of intelligent document processingKey FeaturesTackle common document processing problems to extract value from any type of documentUnlock deeper levels of insights on IDP in a more structured and accelerated way using AWS AI/MLApply your knowledge to solve real document analysis problems in various industry applicationsBook DescriptionWith the volume of data growing exponentially in this digital era, it has become paramount for professionals to process this data in an accelerated and cost-effective manner to get value out of it. Data that organizations receive is usually in raw document format, and being able to process these documents is critical to meeting growing business needs.This book is a comprehensive guide to helping you get to grips with AI/ML fundamentals and their application in document processing use cases. You'll begin by understanding the challenges faced in legacy document processing and discover how you can build end-to-end document processing pipelines with AWS AI services. As you advance, you'll get hands-on experience with popular Python libraries to process and extract insights from documents. This book starts with the basics, taking you through real industry use cases for document processing to deliver value-based care in the healthcare industry and accelerate loan application processing in the financial industry. Throughout the chapters, you'll find out how to apply your skillset to solve practical problems.By the end of this AWS book, you'll have mastered the fundamentals of document processing with machine learning through practical implementation.What you will learnUnderstand the requirements and challenges in deriving insights from a documentExplore common stages in the intelligent document processing pipelineDiscover how AWS AI/ML can successfully automate IDP pipelinesFind out how to write clean and elegant Python code by leveraging AIGet to grips with the concepts and functionalities of AWS AI servicesExplore IDP across industries such as insurance, healthcare, finance, and the public sectorDetermine how to apply business rules in IDPBuild, train, and deploy models with serverless architecture for IDPWho this book is forThis book is for technical professionals and thought leaders who want to understand and solve business problems by leveraging insights from their documents. If you want to learn about machine learning and artificial intelligence, and work with real-world use cases such as document processing with technology, this book is for you. To make the most of this book, you should have basic knowledge of AI/ML and python programming concepts. This book is also especially useful for developers looking to explore AI/ML with industry use cases.
Intelligent Electrical Systems and Industrial Automation: Proceedings of IESIA 2024 (Studies in Autonomic, Data-driven and Industrial Computing)
by Vincenzo Piuri João Manuel R. S. Tavares Sanjoy MondalThis book features high-quality research papers presented at the International Conference on Intelligent Electrical Systems & Industrial Automation (IESIA 2024), organized by Department of Electrical Engineering, Electrical and Electronics Engineering, Institute of Engineering & Management, Kolkata, India during April 5 – 7, 2024. The volume presents diverse range of topics, including smart sensors, automation control algorithms, energy-efficient solutions, and real-time data analytics.
Intelligent Embedded Systems: Select Proceedings of ICNETS2, Volume II (Lecture Notes in Electrical Engineering #492)
by Daniel Thalmann N Subhashini K. Mohanaprasad M S Bala MuruganThis book is a collection of papers from international experts presented at the International Conference on NextGen Electronic Technologies (ICNETS2). ICNETS2 encompassed six symposia covering all aspects of electronics and communications engineering, including relevant nano/micro materials and devices. Highlighting recent research in intelligent embedded systems, the book is a valuable resource for professionals and students working in the core areas of electronics and their applications, especially in signal processing, embedded systems, and networking. The contents of this volume will be of interest to researchers and professionals alike.
Intelligent Energy Demand Forecasting
by Wei-Chiang HongAs industrial, commercial, and residential demands increase and with the rise of privatization and deregulation of the electric energy industry around the world, it is necessary to improve the performance of electric operational management. Intelligent Energy Demand Forecasting offers approaches and methods to calculate optimal electric energy allocation to reach equilibrium of the supply and demand. Evolutionary algorithms and intelligent analytical tools to improve energy demand forecasting accuracy are explored and explained in relation to existing methods. To provide clearer picture of how these hybridized evolutionary algorithms and intelligent analytical tools are processed, Intelligent Energy Demand Forecasting emphasizes on improving the drawbacks of existing algorithms. Written for researchers, postgraduates, and lecturers, Intelligent Energy Demand Forecasting helps to develop the skills and methods to provide more accurate energy demand forecasting by employing novel hybridized evolutionary algorithms and intelligent analytical tools.
Intelligent Engineering Informatics: Proceedings Of The 6th International Conference On Ficta (Advances In Intelligent Systems And Computing #695)
by Suresh Chandra Satapathy Vikrant Bhateja Prasant Kumar Pattnaik Carlos A. Coello CoelloThis book presents the proceedings of the 6th International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA 2017), held in Bhubaneswar, Odisha. The event brought together researchers, scientists, engineers, and practitioners to exchange their new ideas and experiences in the domain of intelligent computing theories with prospective applications to various engineering disciplines. The book is divided into two volumes: Information and Decision Sciences, and Intelligent Engineering Informatics. This volume covers broad areas of Intelligent Engineering Informatics, with papers exploring both the theoretical and practical aspects of various areas like ANN and genetic algorithms, human–computer interaction, intelligent control optimisation, intelligent e-learning systems, machine learning, mobile computing, multi-agent systems, etc. The book also offers a valuable resource for students at the post-graduate level in various engineering disciplines.
Intelligent Engineering Optimisation with the Bees Algorithm (Springer Series in Advanced Manufacturing)
by D. T. Pham Natalia HartonoThis book presents new and advanced results and developments related to the Bees Algorithm, along with its application to a wide range of engineering problems. Modern complex processes and systems are difficult to optimise using conventional mathematical tools as they require models that often cannot be obtained with accuracy or certainty. Optimising such systems demands efficient, model-free optimisation tools. The Bees Algorithm, a swarm-based technique inspired by the foraging behaviour of honeybees, is an ideal tool for tackling challenging optimisation problems. The algorithm is conceptually elegant and extremely easy to apply. All it needs to solve an optimisation problem is a means to evaluate the quality of potential solutions. While the covered applications belong to diverse engineering fields, this book’s focus is on advanced manufacturing and industrial engineering. The book comprises two parts. The first part explores different enhancements made to the original Bees Algorithm to improve its performance. The second part delves into the algorithm's applications in design, manufacturing, production, ergonomics, logistics, transportation, and electrical and electronic engineering. By showcasing the variety of optimisation tasks successfully handled using the Bees Algorithm, the book aims to inspire and motivate engineers and researchers worldwide to adopt the algorithm as a powerful and versatile tool for conquering complex engineering problems in the Industry 4.0 era and beyond.
Intelligent Equipment, Robots, and Vehicles: 7th International Conference on Life System Modeling and Simulation, LSMS 2021 and 7th International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2021, Hangzhou, China, October 30 – November 1, 2021, Proceedings, Part III (Communications in Computer and Information Science #1469)
by Chen Peng Qinglong Han Sean McLoone Baolin ZhangThe three-volume set CCIS 1467, CCIS 1468, and CCIS 1469 constitutes the thoroughly refereed proceedings of the 7th International Conference on Life System Modeling and Simulation, LSMS 2021, and of the 7th International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2021, held in Hangzhou, China, in October 2021. The 159 revised papers presented were carefully reviewed and selected from over 430 submissions.The papers of this volume are organized in topical sections on: Medical Imaging and Analysis Using Intelligence Computing; Biomedical signal processing, imaging, visualization and surgical robotics; Computational method in taxonomy study and neural dynamics; Intelligent medical apparatus, clinical applications and intelligent design of biochips; Power and Energy Systems; Computational Intelligence in Utilization of Clean and Renewable Energy Resources, and Intelligent Modelling, Control and Supervision for Energy Saving and Pollution Reduction; Intelligent Methods in Developing Electric Vehicles, Engines and Equipment; Intelligent Control Methods in Energy Infrastructure Development and Distributed Power Generation Systems; Intelligent Modeling, Simulation and Control of Power Electronics and Power Networks; Intelligent Techniques for Sustainable Energy and Green Built Environment, Water Treatment and Waste Management; Intelligent Robot and Simulation; Intelligent Data Processing, Analysis and Control in Complex Systems; Advanced Neural Network Theory and Algorithms; Advanced Computational Methods and Applications; Fuzzy, Neural, and Fuzzy-neuro Hybrids; Intelligent Modelling, Monitoring, and Control of Complex Nonlinear Systems; Intelligent manufacturing, autonomous systems, intelligent robotic systems; Computational Intelligence and Applications.
Intelligent Fault Diagnosis and Health Assessment for Complex Electro-Mechanical Systems
by Ruqiang Yan Weihua Li Xiaoli ZhangBased on AI and machine learning, this book systematically presents the theories and methods for complex electro-mechanical system fault prognosis, intelligent diagnosis, and health state assessment in modern industry. The book emphasizes feature extraction, incipient fault prediction, fault classification, and degradation assessment, which are based on supervised-, semi-supervised-, manifold-, and deep learning; machinery degradation state tracking and prognosis by phase space reconstruction; and complex electro-mechanical system reliability assessment and health maintenance based on running state info. These theories and methods are integrated with practical industrial applications, which can help the readers get into the field more smoothly and provide an important reference for their study, research, and engineering practice.
Intelligent Feature Selection for Machine Learning Using the Dynamic Wavelet Fingerprint
by Mark K. HindersThis book discusses various applications of machine learning using a new approach, the dynamic wavelet fingerprint technique, to identify features for machine learning and pattern classification in time-domain signals. Whether for medical imaging or structural health monitoring, it develops analysis techniques and measurement technologies for the quantitative characterization of materials, tissues and structures by non-invasive means. Intelligent Feature Selection for Machine Learning using the Dynamic Wavelet Fingerprint begins by providing background information on machine learning and the wavelet fingerprint technique. It then progresses through six technical chapters, applying the methods discussed to particular real-world problems. Theses chapters are presented in such a way that they can be read on their own, depending on the reader’s area of interest, or read together to provide a comprehensive overview of the topic. Given its scope, the book will be of interest to practitioners, engineers and researchers seeking to leverage the latest advances in machine learning in order to develop solutions to practical problems in structural health monitoring, medical imaging, autonomous vehicles, wireless technology, and historical conservation.
Intelligent Financial Portfolio Composition based on Evolutionary Computation Strategies
by Antonio Gorgulho Rui F.M.F. Neves Nuno C.G. HortaThe management of financial portfolios or funds constitutes a widely known problematic in financial markets which normally requires a rigorous analysis in order to select the most profitable assets. This subject is becoming popular among computer scientists which try to adapt known Intelligent Computation techniques to the market's domain. This book proposes a potential system based on Genetic Algorithms, which aims to manage a financial portfolio by using technical analysis indicators. The results are promising since the approach clearly outperforms the remaining approaches during the recent market crash.