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Intelligent Computing Theories and Application
by De-Shuang Huang Vitoantonio Bevilacqua Prashan Premaratne Phalguni GuptaThe International Conference on Intelligent Computing (ICIC) was formed to provide an annual forum dedicated to the emerging and challenging topics in artificial intel- gence, machine learning, pattern recognition, image processing, bioinformatics, and computational biology. It aims to bring together researchers and practitioners from both academia and industry to share ideas, problems, and solutions related to the m- tifaceted aspects of intelligent computing. ICIC 2010, held in Changsha, China, August 18-21, 2010, constituted the 6th - ternational Conference on Intelligent Computing. It built upon the success of ICIC 2009, ICIC 2008, ICIC 2007, ICIC 2006, and ICIC 2005, that were held in Ulsan, Korea, Shanghai, Qingdao, Kunming and Hefei, China, respectively. This year, the conference concentrated mainly on the theories and methodologies as well as the emerging applications of intelligent computing. Its aim was to unify the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in advanced computational intelligence and bridges theoretical research with applications. Therefore, the theme for this conference was "Advanced Intelligent Computing Technology and Applications. " Papers focusing on this theme were solicited, addressing theories, methodologies, and applications in science and technology.
Intelligent Computing Theories and Application
by De-Shuang Huang Kang-Hyun Jo Juan Carlos Figueroa-GarcíaThe International Conference on Intelligent Computing (ICIC) was formed to provide an annual forum dedicated to the emerging and challenging topics in artificial intel- gence, machine learning, pattern recognition, image processing, bioinformatics, and computational biology. It aims to bring together researchers and practitioners from both academia and industry to share ideas, problems, and solutions related to the m- tifaceted aspects of intelligent computing. ICIC 2010, held in Changsha, China, August 18-21, 2010, constituted the 6th - ternational Conference on Intelligent Computing. It built upon the success of ICIC 2009, ICIC 2008, ICIC 2007, ICIC 2006, and ICIC 2005, that were held in Ulsan, Korea, Shanghai, Qingdao, Kunming and Hefei, China, respectively. This year, the conference concentrated mainly on the theories and methodologies as well as the emerging applications of intelligent computing. Its aim was to unify the picture of contemporary intelligent computing techniques as an integral concept that highlights the trends in advanced computational intelligence and bridges theoretical research with applications. Therefore, the theme for this conference was "Advanced Intelligent Computing Technology and Applications. " Papers focusing on this theme were solicited, addressing theories, methodologies, and applications in science and technology.
Intelligent Computing Theories and Methodologies
by De-Shuang Huang Kang-Hyun Jo Abir HussainThis two-volume set LNCS 9225 and LNCS 9226 constitutes - in conjunction with the volume LNAI 9227 - the refereed proceedings of the 11th International Conference on Intelligent Computing, ICIC 2015, held in Fuzhou, China, in August 2015. The total of 191 full and 42 short papers presented in the three ICIC 2015 volumes was carefully reviewed and selected from 671 submissions. The papers are organized in topical sections such as evolutionary computation and learning; compressed sensing, sparse coding and social computing; neural networks, nature inspired computing and optimization; pattern recognition and signal processing; image processing; biomedical informatics theory and methods; differential evolution, particle swarm optimization and niche technology; intelligent computing and knowledge discovery and data mining; soft computing and machine learning; computational biology, protein structure and function prediction; genetic algorithms; artificial bee colony algorithms; swarm intelligence and optimization; social computing; information security; virtual reality and human-computer interaction; healthcare informatics theory and methods; unsupervised learning; collective intelligence; intelligent computing in robotics; intelligent computing in communication networks; intelligent control and automation; intelligent data analysis and prediction; gene expression array analysis; gene regulation modeling and analysis; protein-protein interaction prediction; biology inspired computing and optimization; analysis and visualization of large biological data sets; motif detection; biomarker discovery; modeling; simulation; and optimization of biological systems; biomedical data modeling and mining; intelligent computing in biomedical signal/image analysis; intelligent computing in brain imaging; neuroinformatics; cheminformatics; intelligent computing in computational biology; computational genomics; special session on biomedical data integration and mining in the era of big data; special session on big data analytics; special session on artificial intelligence for ambient assisted living; and special session on swarm intelligence with discrete dynamics.
Intelligent Control: A Stochastic Optimization Based Adaptive Fuzzy Approach (Cognitive Intelligence and Robotics)
by Kaushik Das Sharma Amitava Chatterjee Anjan RakshitThis book discusses systematic designs of stable adaptive fuzzy logic controllers employing hybridizations of Lyapunov strategy-based approaches/H∞ theory-based approaches and contemporary stochastic optimization techniques. The text demonstrates how candidate stochastic optimization techniques like Particle swarm optimization (PSO), harmony search (HS) algorithms, covariance matrix adaptation (CMA) etc. can be utilized in conjunction with the Lyapunov theory/H∞ theory to develop such hybrid control strategies. The goal of developing a series of such hybridization processes is to combine the strengths of both Lyapunov theory/H∞ theory-based local search methods and stochastic optimization-based global search methods, so as to attain superior control algorithms that can simultaneously achieve desired asymptotic performance and provide improved transient responses. The book also demonstrates how these intelligent adaptive control algorithms can be effectively utilized in real-life applications such as in temperature control for air heater systems with transportation delay, vision-based navigation of mobile robots, intelligent control of robot manipulators etc.
Intelligent Control
by Nazmul SiddiqueIntelligent Control considers non-traditional modelling and control approaches to nonlinear systems. Fuzzy logic, neural networks and evolutionary computing techniques are the main tools used. The book presents a modular switching fuzzy logic controller where a PD-type fuzzy controller is executed first followed by a PI-type fuzzy controller thus improving the performance of the controller compared with a PID-type fuzzy controller. The advantage of the switching-type fuzzy controller is that it uses one rule-base thus minimises the rule-base during execution. A single rule-base is developed by merging the membership functions for change of error of the PD-type controller and sum of error of the PI-type controller. Membership functions are then optimized using evolutionary algorithms. Since the two fuzzy controllers were executed in series, necessary further tuning of the differential and integral scaling factors of the controller is then performed. Neural-network-based tuning for the scaling parameters of the fuzzy controller is then described and finally an evolutionary algorithm is applied to the neurally-tuned-fuzzy controller in which the sigmoidal function shape of the neural network is determined. The important issue of stability is addressed and the text demonstrates empirically that the developed controller was stable within the operating range. The text concludes with ideas for future research to show the reader the potential for further study in this area. Intelligent Control will be of interest to researchers from engineering and computer science backgrounds working in the intelligent and adaptive control.
Intelligent Control and Smart Energy Management: Renewable Resources and Transportation (Springer Optimization and Its Applications #181)
by Maude Josée Blondin João Pedro Fernandes Trovão Hicham Chaoui Panos M. PardalosThis volume aims to provide a state-of-the-art and the latest advancements in the field of intelligent control and smart energy management. Techniques, combined with technological advances, have enabled the deployment of new operating systems in many engineering applications, especially in the domain of transport and renewable resources. The control and energy management of transportation and renewable resources are shifting towards autonomous reasoning, learning, planning and operating. As a result, these techniques, also referred to as autonomous control and energy management, will become practically ubiquitous soon. The discussions include methods, based on neural control (and others) as well as distributed and intelligent optimization. While the theoretical concepts are detailed and explained, the techniques presented are tailored to transport and renewable resources applications, such as smart grids and automated vehicles. The reader will grasp the most important theoretical concepts as well as to fathom the challenges and needs related to timely practical applications. Additional content includes research perspectives and future direction as well as insight into the devising of techniques that will meet tomorrow’s scientific needs. This contributed volume is for researchers, graduate students, engineers and practitioners in the domains of control, energy, and transportation.
Intelligent Control of Connected Plug-in Hybrid Electric Vehicles (Advances in Industrial Control)
by Amir Taghavipour Mahyar Vajedi Nasser L. AzadIntelligent Control of Connected Plug-in Hybrid Electric Vehicles presents the development of real-time intelligent control systems for plug-in hybrid electric vehicles, which involves control-oriented modelling, controller design, and performance evaluation. The controllers outlined in the book take advantage of advances in vehicle communications technologies, such as global positioning systems, intelligent transportation systems, geographic information systems, and other on-board sensors, in order to provide look-ahead trip data. The book contains simple and efficient models and fast optimization algorithms for the devised controllers to address the challenge of real-time implementation in the design of complex control systems. Using the look-ahead trip information, the authors of the book propose intelligent optimal model-based control systems to minimize the total energy cost, for both grid-derived electricity and fuel. The multilayer intelligent control system proposed consists of trip planning, an ecological cruise controller, and a route-based energy management system. An algorithm that is designed to take advantage of previewed trip information to optimize battery depletion profiles is presented in the book. Different control strategies are compared and ways in which connecting vehicles via vehicle-to-vehicle communication can improve system performance are detailed. Intelligent Control of Connected Plug-in Hybrid Electric Vehicles is a useful source of information for postgraduate students and researchers in academic institutions participating in automotive research activities. Engineers and designers working in research and development for automotive companies will also find this book of interest.Advances in Industrial Control reports and encourages the transfer of technology in control engineering. The rapid development of control technology has an impact on all areas of the control discipline. The series offers an opportunity for researchers to present an extended exposition of new work in all aspects of industrial control.
Intelligent Data Analysis for COVID-19 Pandemic (Algorithms for Intelligent Systems)
by M. Niranjanamurthy Siddhartha Bhattacharyya Neeraj KumarThis book presents intelligent data analysis as a tool to fight against COVID-19 pandemic. The intelligent data analysis includes machine learning, natural language processing, and computer vision applications to teach computers to use big data-based models for pattern recognition, explanation, and prediction. These functions are discussed in detail in the book to recognize (diagnose), predict, and explain (treat) COVID-19 infections, and help manage socio-economic impacts. It also discusses primary warnings and alerts; tracking and prediction; data dashboards; diagnosis and prognosis; treatments and cures; and social control by the use of intelligent data analysis. It provides analysis reports, solutions using real-time data, and solution through web applications details.
Intelligent Data Analytics in Business: Select Proceedings of ICDABM 2022 (Lecture Notes in Electrical Engineering #1068)
by Kiran Chaudhary Mansaf Alam Narayan C. DebnathThis book includes peer-reviewed contributions presented at the International Conference on Data Analytics in Business and Marketing, ICDABM 2022. The book covers topics in data analytics, intelligent data, data management in business and marketing, big data, computational intelligence, and communication networks. The book presents innovative work by leading academics, researchers, and experts from the industry, which is helpful for young researchers and students.
Intelligent Data Engineering and Analytics: Proceedings of the 11th International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA 2023) (Smart Innovation, Systems and Technologies #371)
by Vikrant Bhateja Fiona Carroll João Manuel R. S. Tavares Sandeep Singh Sengar Peter PeerThe book presents the proceedings of the 11th International Conference on Frontiers of Intelligent Computing: Theory and Applications (FICTA 2023), held at Cardiff School of Technologies, Cardiff Metropolitan University, Cardiff, Wales, UK, during April 11–12, 2023. Researchers, scientists, engineers, and practitioners exchange new ideas and experiences in the domain of intelligent computing theories with prospective applications in various engineering disciplines in the book. This book is divided into two volumes. It covers broad areas of information and decision sciences, with papers exploring both the theoretical and practical aspects of data-intensive computing, data mining, evolutionary computation, knowledge management and networks, sensor networks, signal processing, wireless networks, protocols, and architectures. This book is a valuable resource for postgraduate students in various engineering disciplines.
Intelligent Data Mining in Law Enforcement Analytics: New Neural Networks Applied to Real Problems
by Paolo Massimo Buscema William J. TastleThis book provides a thorough summary of the means currently available to the investigators of Artificial Intelligence for making criminal behavior (both individual and collective) foreseeable, and for assisting their investigative capacities. The volume provides chapters on the introduction of artificial intelligence and machine learning suitable for an upper level undergraduate with exposure to mathematics and some programming skill or a graduate course. It also brings the latest research in Artificial Intelligence to life with its chapters on fascinating applications in the area of law enforcement, though much is also being accomplished in the fields of medicine and bioengineering. Individuals with a background in Artificial Intelligence will find the opening chapters to be an excellent refresher but the greatest excitement will likely be the law enforcement examples, for little has been done in that area. The editors have chosen to shine a bright light on law enforcement analytics utilizing artificial neural network technology to encourage other researchers to become involved in this very important and timely field of study.
The Intelligent Enterprise in the Era of Big Data
by Venkat SrinivasanAn innovative guide to the organization and function of enterprises in the technological age In the era of big data and automation, this book presents a cutting-edge approach in how enterprises should organize and function. Striking a practical balance between theory and practice, The Intelligent Enterprise in the Era of Big Data presents an enterprise architecture that embodies the power of the emerging technology environment. Beginning with an introduction to the key challenges that enterprises face, the book systematically outlines a modern enterprise architecture through a detailed discussion of the inseparable elements of such an architecture: efficiency, flexibility, and intelligence. This architecture enables rapid responses to market needs by facilitating intelligent, flexible automation of enterprise business processes and sensing important developments in internal and external environments in near real time. Illustrating all of these elements in an integrated fashion, The Intelligent Enterprise in the Era of Big Data also features: A detailed discussion on issues of time-to-market and flexibility with respect to enterprise application technology Novel analyses illustrated through extensive real-world case studies to help readers better understand the applicability of the architecture and concepts Practical approaches for designing and building intelligent enterprises An appendix that presents various approaches to text analysis with real-world business implications The Intelligent Enterprise in the Era of Big Data is an appropriate reference for business executives, information technology professionals, data scientists, and management consultants.
Intelligent Mathematics II: Applied Mathematics and Approximation Theory
by Oktay Duman George A. AnastassiouThis specialvolume is a collection of outstanding more applied articles presented in AMAT2015 held in Ankara, May 28-31, 2015, at TOBB Economics and TechnologyUniversity. The collectionis suitable for Applied and Computational Mathematics and Engineeringpractitioners, also for related graduate students and researchers. Furthermoreit will be a useful resource for all science and engineering libraries. This bookincludes 29 self-contained and well-edited chapters that can be among othersuseful for seminars in applied and computational mathematics, as well as in engineering.
Intelligent Methods with Applications in Volcanology and Seismology (Advances in Volcanology)
by Alireza Hajian Giuseppe Nunnari Roohollah KimiaefarThis book presents intelligent methods like neural, neuro-fuzzy, machine learning, deep learning and metaheuristic methods and their applications in both volcanology and seismology. The complex system of volcanoes and also earthquakes is a big challenge to identify their behavior using available models, which motivates scientists to apply non-model based methods. As there are lots of seismology and volcanology data sets, i.e., the local and global networks, one solution is using intelligent methods in which data-based algorithms are used.
Intelligent Numerical Methods: Applications to Fractional Calculus
by George A. Anastassiou Ioannis K. ArgyrosIn this monograph the authors present Newton-type, Newton-like and other numerical methods, which involve fractional derivatives and fractional integral operators, for the first time studied in the literature. All for the purpose to solve numerically equations whose associated functions can be also non-differentiable in the ordinary sense. That is among others extending the classical Newton method theory which requires usual differentiability of function. Chapters are self-contained and can be read independently and several advanced courses can be taught out of this book. An extensive list of references is given per chapter. The book's results are expected to find applications in many areas of applied mathematics, stochastics, computer science and engineering. As such this monograph is suitable for researchers, graduate students, and seminars of the above subjects, also to be in all science and engineering libraries.
Intelligent Numerical Methods II: Applications to Multivariate Fractional Calculus
by George A. Anastassiou Ioannis K. ArgyrosIn this short monograph Newton-likeand other similar numerical methods with applications to solving multivariateequations are developed, which involve Caputotype fractional mixed partial derivatives and multivariate fractional Riemann-Liouvilleintegral operators. These are studied for the first time in the literature. Thechapters are self-contained and can be read independently. An extensive list ofreferences is given per chapter. The book's results are expected to findapplications in many areas of applied mathematics, stochastics, computerscience and engineering. As such this short monograph is suitable forresearchers, graduate students, to be used in graduate classes and seminars ofthe above subjects, also to be in all science and engineering libraries.
Intelligent Optimization: Principles, Algorithms and Applications
by Shengxiang Yang Sanyou Zeng Changhe Li Shoufei HanThis textbook comprehensively explores the foundational principles, algorithms, and applications of intelligent optimization, making it an ideal resource for both undergraduate and postgraduate artificial intelligence courses. It remains equally valuable for active researchers and individuals engaged in self-study. Serving as a significant reference, it delves into advanced topics within the evolutionary computation field, including multi-objective optimization, dynamic optimization, constrained optimization, robust optimization, expensive optimization, and other pivotal scientific studies related to optimization. Designed to be approachable and inclusive, this textbook equips readers with the essential mathematical background necessary for understanding intelligent optimization. It employs an accessible writing style, complemented by extensive pseudo-code and diagrams that vividly illustrate the mechanisms, principles, and algorithms of optimization. With a focus on practicality, this textbook provides diverse real-world application examples spanning engineering, games, logistics, and other domains, enabling readers to confidently apply intelligent techniques to actual optimization problems. Recognizing the importance of hands-on experience, the textbook introduces the Open-source Framework for Evolutionary Computation platform (OFEC) as a user-friendly tool. This platform serves as a comprehensive toolkit for implementing, evaluating, visualizing, and benchmarking various optimization algorithms. The book guides readers on maximizing the utility of OFEC for conducting experiments and analyses in the field of evolutionary computation, facilitating a deeper understanding of intelligent optimization through practical application.
Intelligent Optimization and Control of Complex Metallurgical Processes (Engineering Applications of Computational Methods #3)
by Xin Chen Min Wu Weihua Cao Jinhua SheThis book discusses the intelligent optimization and control of complex metallurgical processes, including intelligent optimization and control of raw-material proportioning processes, coking process, and reheating furnaces; intelligent control of thermal state parameters in sintering processes; and intelligent decoupling control of gas collection and mixing-and-pressurization processes. The intelligent control and optimization methods presented were originally applied to complex metallurgical processes by the authors, and their effectiveness and their advantages have been theoretically proven and demonstrated practically. This book offers an up-to-date overview of this active research area, and provides readers with state-of-the-art methods for the control of complex metallurgical processes.
Intelligent Optimization of Mold Design and Process Parameters in Injection Molding (Springer Theses)
by Mehdi MoayyedianThis book describes an effective framework for setting the right process parameters and new mold design to reduce the current plastic defects in injection molding. It presents a new approach for the optimization of injection molding process via (i) a new mold runner design which leads to 20 percent reduction in scrap rate, 2.5 percent reduction in manufacturing time, and easier ejection of injected part, (ii) a new mold gate design which leads to less plastic defects; and (iii) the introduction of a number of promising alternatives with high moldability indices. Besides presenting important developments of relevance academic research, the book also includes useful information for people working in the injection molding industry, especially in the green manufacturing field.
Intelligent Processing Algorithms and Applications for GPS Positioning Data of Qinghai-Tibet Railway
by Dewang Chen Ruijun ChengTaking the Qinghai–Tibet Railway as an example, this book introduces intelligent processing for Global Positioning Data (GPS) data. Combining theory with practical applications, it provides essential insights into the Chinese Qinghai–Tibet Railway and novel methods of data processing for GPS satellite positioning, making it a valuable resource for all those working with train control systems, train positioning systems, satellite positioning, and intelligent data processing. As satellite positioning guarantees the safe and efficient operation of train control systems, it focuses on how to best process the GPS data collected, including methods for error detection, reduction and information fusion.
Intelligent Routines II
by George A. Anastassiou Iuliana F. Iatan"Intelligent Routines II: Solving Linear Algebra and Differential Geometry with Sage" contains numerous of examples and problems as well as many unsolved problems. This book extensively applies the successful software Sage, which can be found free online http://www. sagemath. org/. Sage is a recent and popular software for mathematical computation, available freely and simple to use. This book is useful to all applied scientists in mathematics, statistics and engineering, as well for late undergraduate and graduate students of above subjects. It is the first such book in solving symbolically with Sage problems in Linear Algebra and Differential Geometry. Plenty of SAGE applications are given at each step of the exposition.
Intelligent Support for Computer Science Education: Pedagogy Enhanced by Artificial Intelligence
by Barbara Di Eugenio Davide Fossati Nick GreenIntelligent Support for Computer Science Education presents the authors’ research journey into the effectiveness of human tutoring, with the goal of developing educational technology that can be used to improve introductory Computer Science education at the undergraduate level. Nowadays, Computer Science education is central to the concerns of society, as attested by the penetration of information technology in all aspects of our lives; consequently, in the last few years interest in Computer Science at all levels of schooling, especially at the college level, has been flourishing. However, introductory concepts in Computer Science such as data structures and recursion are difficult for novices to grasp. Key Features: Includes a comprehensive and succinct overview of the Computer Science education landscape at all levels of education. Provides in-depth analysis of one-on-one human tutoring dialogues in introductory Computer Science at college level. Describes a scalable, plug-in based Intelligent Tutoring System architecture, portable to different topics and pedagogical strategies. Presents systematic, controlled evaluation of different versions of the system in ecologically valid settings (18 actual classes and their laboratory sessions). Provides a time-series analysis of student behavior when interacting with the system. This book will be of special interest to the Computer Science education community, specifically instructors of introductory courses at the college level, and Advanced Placement (AP) courses at the high school level. Additionally, all the authors’ work is relevant to the Educational Technology community, especially to those working in Intelligent Tutoring Systems, their interfaces, and Educational Data Mining, in particular as applied to human-human pedagogical interactions and to user interaction with educational software.
Intelligent Systems and Applications in Business and Finance (Studies in Fuzziness and Soft Computing #415)
by Pasi Luukka Jan StoklasaThis book presents a selection of current research results in the field of intelligent systems and draws attention to their practical applications and issues connected with the areas of decision-making, economics, business and finance. The nature of the contributions is interdisciplinary – combining psychological and behavioural aspects with the theory and practice of decision-support, design of intelligent systems and development of machine learning tools. The authors, among other topics, discuss the multi-expert evaluation with intangible criteria, suggest a redefinition of the standard multiple-criteria decision-making framework, propose novel methods for causal map analysis and new feature selection methods. The topics are selected to stress the potential of the up-to-date intelligent methods to deal with practical problems relevant in these areas and to provide inspiration for advanced students, researchers and practitioners in the respective fields.
Intelligent Systems and Computing (Lecture Notes on Data Engineering and Communications Technologies #207)
by Bing-Yuan Cao Shu-Feng Wang Seyed Hadi Nasseri Yu-Bin ZhongThis book includes high quality research papers submitted at the 2022 “Four Session (ICFIE, ICORG, GDORS, CGHMORS) Celebration” Joint International Conference held on December 28, 2022 and the online meeting of the Fuzzy Information and Engineering Branch of the China Operations Research Society on September 17, 2022. It covers topics in the fields of certainty, stochastic uncertainty, and fuzzy uncertainty, including computer science and mathematics, operations research and control, artificial intelligence, information and engineering technology, barrier-free communication for people with disabilities, digital logistics and knowledge representation, medical applications, queuing theory and game theory, algorithms and optimization methods. The book is a valuable reference book for scholars, engineers, management professionals, and graduate, undergraduate, and vocational students interested in computer science, mathematics, and fuzzy mathematics and operations research, as well as their applications in information technology and engineering.
Intelligent Systems and Sustainable Computing: Proceedings of ICISSC 2021 (Smart Innovation, Systems and Technologies #289)
by V. Sivakumar Reddy V. Kamakshi Prasad D. N. Mallikarjuna Rao Suresh Chandra SatapathyThe book is a collection of best selected research papers presented at the International Conference on Intelligent Systems and Sustainable Computing (ICISSC 2021), held in School of Engineering, Malla Reddy University, Hyderabad, India, during 24–25 September 2021. The book covers recent research in intelligent systems, intelligent business systems, soft computing, swarm intelligence, artificial intelligence and neural networks, data mining & data warehousing, cloud computing, distributed computing, big data analytics, Internet of Things (IoT), machine learning, speech processing, sustainable high-performance systems, VLSI and embedded systems, image and video processing, and signal processing and communication.