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The field of computational intelligence has grown tremendously over that past five years, thanks to evolving soft computing and artificial intelligent methodologies, tools and techniques for envisaging the essence of intelligence embedded in real life observations. Consequently, scientists have been able to explain and understand real life processes and practices which previously often remain unexplored by virtue of their underlying imprecision, uncertainties and redundancies, and the unavailability of appropriate methods for describing the incompleteness and vagueness of information represented. With the advent of the field of computational intelligence, researchers are now able to explore and unearth the intelligence, otherwise insurmountable, embedded in the systems under consideration. Computational Intelligence is now not limited to only specific computational fields, it has made inroads in signal processing, smart manufacturing, predictive control, robot navigation, smart cities, and sensor design to name a few. Recent Trends in Computational Intelligence Enabled Research: Theoretical Foundations and Applications explores the use of this computational paradigm across a wide range of applied domains which handle meaningful information. Chapters investigate a broad spectrum of the applications of computational intelligence across different platforms and disciplines, expanding our knowledge base of various research initiatives in this direction. This volume aims to bring together researchers, engineers, developers and practitioners from academia and industry working in all major areas and interdisciplinary areas of computational intelligence, communication systems, computer networks, and soft computing. - Provides insights into the theory, algorithms, implementation, and application of computational intelligence techniques - Covers a wide range of applications of deep learning across various domains which are researching the applications of computational intelligence - Investigates novel techniques and reviews the state-of-the-art in the areas of machine learning, computer vision, soft computing techniques
The increase in computing power and sensor data has driven Information Technology on end devices, such as smart phones or automobiles. The widespread application of IT across the globe includes manufacturing, engineering, retail, e-commerce, health care, education, financial services, banking, space exploration, politics (to help predict the sentiments of voter demographics), etc. The papers in this conference proceeding examine and discuss various interdisciplinary researches that could accelerate the advent of Information Technology.
This book constitutes the refereed proceedings of the 17th Conference on Artificial Intelligence in Medicine, AIME 2019, held in Poznan, Poland, in June 2019. The 22 revised full and 31 short papers presented were carefully reviewed and selected from 134 submissions. The papers are organized in the following topical sections: deep learning; simulation; knowledge representation; probabilistic models; behavior monitoring; clustering, natural language processing, and decision support; feature selection; image processing; general machine learning; and unsupervised learning.
This book offers an excellent presentation of intelligent engineering and informatics foundations for researchers in this field as well as many examples with industrial application. It contains extended versions of selected papers presented at the inaugural ACASE 2012 Conference dedicated to the Applications of Systems Engineering. This conference was held from the 6th to the 8th of February 2012, at the University of Technology, Sydney, Australia, organized by the University of Technology, Sydney (Australia), Wroclaw University of Technology (Poland) and the University of Applied Sciences in Hagenberg (Austria). The book is organized into three main parts. Part I contains papers devoted to the heuristic approaches that are applicable in situations where the problem cannot be solved by exact methods, due to various characteristics or dimensionality problems. Part II covers essential issues of the network management, presents intelligent models of the next generation of networks and distributed systems as well as discusses applications of modern numerical methods in large intractable systems. Part III covers salient issues of complexity in intelligent system applications. This part also contains papers and articles which discuss concurrency issues that arise when multiple systems attempt to use the same radio space and the inter-connected system applications in the field of medical simulation and training.
In recent years, biometrics has developed rapidly with its worldwide applications for daily life. New trends and novel developments have been proposed to acquire and process many different biometric traits. The ignored challenges in the past and potential problems need to be thought together and deeply integrated. The key objective of the book is to keep up with the new technologies on some recent theoretical development as well as new trends of applications in biometrics. The topics covered in this book reflect well both aspects of development. They include the new development in forensic speaker recognition, 3D and thermo face recognition, finger vein recognition, contact-less biometric system, hand geometry recognition, biometric performance evaluation, multi-biometric template protection, and novel subfields in the new challenge fields. The book consists of 13 chapters. It is divided into four sections, namely, theory and method, performance evaluation, security and template protection, and other applications. The book was reviewed by editors Dr. Jucheng Yang and Dr. Shanjuan Xie. We deeply appreciate the efforts of our guest editors: Dr. Norman Poh, Dr. Loris Nanni, Dr. Dongsun Park, Dr. Sook Yoon and Ms. Congcong Xiong, as well as a number of anonymous reviewers.
The latest developments in computer science, theoretical software engineering, cognitive science, cognitive informatics, intelligence science, and the crystallization of accumulated knowledge by the fertilization of these areas, have led to the emergence of a transdisciplinary and convergence field known as software and intelligence sciences International Journal of Software Science and Computational Intelligence (IJSSCI) is a transdisciplinary, archived, and rigorously refereed journal that publishes and disseminates cutting-edge research findings and technological developments in the emerging fields of software science and computational intelligence, as well as their engineering applications.
The book presents high quality research papers presented at International Conference on Computational Intelligence (ICCI 2021) held online during 27–28 December, 2021. The topics covered are artificial intelligence, neural network, deep learning techniques, fuzzy theory and systems, rough sets, self-organizing maps, machine learning, chaotic systems, multi-agent systems, computational optimization ensemble classifiers, reinforcement learning, decision trees, support vector machines, hybrid learning, statistical learning. metaheuristics algorithms: evolutionary and swarm-based algorithms like genetic algorithms, genetic programming, differential evolution, particle swarm optimization, whale optimization, spider monkey optimization, firefly algorithm, memetic algorithms. And also machine vision, Internet of Things, image processing, image segmentation, data clustering, sentiment analysis, big data, computer networks, signal processing, supply chain management, web and text mining, distributed systems, bioinformatics, embedded systems, expert system, forecasting, pattern recognition, planning and scheduling, time series analysis, human-computer interaction, web mining, natural language processing, multimedia systems, and quantum computing.
This book constitutes the refereed proceedings of the 20th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 2007, held in Kyoto, Japan. Coverage includes text processing, fuzzy system applications, real-world interaction, data mining, machine learning chance discovery and social networks, e-commerce, heuristic search application systems, and other applications.
This book consists of 20 chapters in which the authors deal with different theoretical and practical aspects of new trends in Collective Computational Intelligence techniques. Computational Collective Intelligence methods and algorithms are one the current trending research topics from areas related to Artificial Intelligence, Soft Computing or Data Mining among others. Computational Collective Intelligence is a rapidly growing field that is most often understood as an AI sub-field dealing with soft computing methods which enable making group decisions and processing knowledge among autonomous units acting in distributed environments. Web-based Systems, Social Networks, and Multi-Agent Systems very often need these tools for working out consistent knowledge states, resolving conflicts and making decisions. The chapters included in this volume cover a selection of topics and new trends in several domains related to Collective Computational Intelligence: Language and Knowledge Processing, Data Mining Methods and Applications, Computer Vision, and Intelligent Computational Methods. This book will be useful for graduate and PhD students in computer science as well as for mature academics, researchers and practitioners interested in the methods and applications of collective computational intelligence in order to create new intelligent systems.
This book gathers the most recent developments in fuzzy & intelligence systems and real complex systems presented at INFUS 2020, held in Istanbul on July 21–23, 2020. The INFUS conferences are a well-established international research forum to advance the foundations and applications of intelligent and fuzzy systems, computational intelligence, and soft computing, highlighting studies on fuzzy & intelligence systems and real complex systems at universities and international research institutions. Covering a range of topics, including the theory and applications of fuzzy set extensions such as intuitionistic fuzzy sets, hesitant fuzzy sets, spherical fuzzy sets, and fuzzy decision-making; machine learning; risk assessment; heuristics; and clustering, the book is a valuable resource for academics, M.Sc. and Ph.D. students, as well as managers and engineers in industry and the service sectors.