Bücher der Reihe Studies in Computational Intelligence

This book presents the outcomes of the 16th International Conference on Software Engineering, Artificial Intelligence Research, Management and Applications (SERA 2018), which was held in Kunming, China on June 13-15, 2018.

The book focuses on machine learning. The second part then describes the application of machine learning in the classification problem, while the third part presents an overview of real-world applications of swarm-based optimization algorithms. The concept of machine learning (ML) is not new in the field of computing.

This book presents appealing contributions on computational intelligence and mathematics, connecting both areas and offering solutions to a number of interesting, real-world problems.

The topics discussed include particle swarm optimization, the artificial bee colony algorithm, Spider Monkey optimization algorithm, genetic algorithms, constrained multi-objective evolutionary algorithms, genetic programming, and evolutionary fuzzy systems.

Building on the successful first and second volumes, this book is the third volume of the Springer book on the Robot Operating System (ROS): The Complete Reference. Further, the ROS is being integrated into various robots and systems and is becoming an embedded technology in emerging robotics platforms.

This book presents the scientific outcomes of the 6th International Conference on Applied Computing and Information Technology (ACIT 2018), which was held in Kunming, China on June 13-15, 2018.

This book gathers revised and extended versions of the best papers presented at the 8th International Joint Conference on Computational Intelligence (IJCCI 2016), which was held in Porto, Portugal from 9 to 11 November 2016.

the modeling of physical processes, wildfire modeling, modeling processes in chemical engineering, workforce planning, wireless access network topology, parameter settings for controlling various processes, berth allocation, identification of homogeneous domains, and quantum computing.

It covers a wide range of methods and technologies, including deep neural networks, large-scale neural models, brain-computer interface, signal processing methods, as well as models of perception, studies on emotion recognition, self-organization and many more.

As such the book explores the latest trends in fashion creative processes, facial features detection, visual odometry, transfer learning, face recognition, feature description, plankton and scene classification, video face alignment, video searching, and object segmentation.

Proceedings of SOHOMA 2018

This book presents a selection of highly relevant works concerning the Internet of Things, including: IoT Architectures, Standardization, Smart Cities, Smart Health, the communication of Smart Things, and outstanding IoT use cases.

This book presents novel classification algorithms for four challenging prediction tasks, namely learning from imbalanced, semi-supervised, multi-instance and multi-label data.

This book provides insights into the research in the fields of artificial intelligence in combination with Internet of Things (IoT) technologies.

This book highlights cutting-edge research in the field of network science, offering scientists, researchers, students and practitioners a unique update on the latest advances in theory, together with a wealth of applications.

This book presents innovative and high-quality research regarding the implementation of Semantic Web technologies for knowledge representation and developing intelligent applications in various domains.

This book presents the outcomes of the 3rd IEEE/ACIS International Conference on Big Data, Cloud Computing, Data Science & Engineering (BCD 2018), which was held on July 10-12, 2018 in Kanazawa.

The aim of the conference was to bring together researchers and scientists, businesspeople and entrepreneurs, teachers, engineers, computer users, and students to discuss the various fields of computer science, to share their experiences, and to exchange new ideas and information in a meaningful way.

This book presents recent research in the field of interaction between computational intelligence and mathematics. In the current technological age, we face the challenges of tackling very complex problems - in the usual sense, but also in the mathematical and theoretical computer science sense. However, even the most up-to-date results in mathematics, are unable to provide exact solutions of such problems, and no further technical advances will ever make it possible to find general and exact solutions. Constantly developing technologies (including social technologies) necessitate handling very complex problems. This has led to a search for acceptably "good" or precise solutions, which can be achieved by the combination of traditional mathematical techniques and computational intelligence tools, in order to solve the various problems emerging in many different areas to a satisfactory degree.Important funding programs, such as the European Commission's current framework programme for research and innovation - Horizon 2020 - are devoted to the development of new instruments to deal with the current challenges. Without doubt, research topics associated with the interactions between computational intelligence and traditional mathematics play a key role. Presenting contributions from engineers, scientists and mathematicians, this book offers a series of novel solutions for meaningful and real-world problems that connect those research areas.

This book gathers the peer-reviewed proceedings of the 12th Annual Meeting of the Bulgarian Section of the Society for Industrial and Applied Mathematics, BGSIAM'17, held in Sofia, Bulgaria, in December 2017.

Akin to evolutionary and swarm-based optimization algorithms, socio-cultural algorithms belong to the category of metaheuristics (problem-independent computational methods) and are inspired by natural and social tendencies observed in humans by which they learn from one another through social interactions.

In the context of growing demand for big data analytics, cloud computing offers an ideal platform for processing big data tasks due to its flexible scalability and adaptability.

This volume comprises a selection of works presented at the Numerical and Evolutionary Optimization (NEO 2016) workshop held in September 2016 in Tlalnepantla, Mexico. The development of powerful search and optimization techniques is of great importance in today's world and requires researchers and practitioners to tackle a growing number of challenging real-world problems. In particular, there are two well-established and widely known ¿elds that are commonly applied in this area: (i) traditional numerical optimization techniques and (ii) comparatively recent bio-inspired heuristics. Both paradigms have their unique strengths and weaknesses, allowing them to solve some challenging problems while still failing in others.The goal of the NEO workshop series is to bring together experts from these and related ¿elds to discuss, compare and merge their complementary perspectives in order to develop fast and reliable hybrid methods that maximize the strengths and minimize the weaknesses of the underlying paradigms. In doing so, NEO promotes the development of new techniques that are applicable to a broader class of problems. Moreover, NEO fosters the understanding and adequate treatment of real-world problems particularly in emerging ¿elds that affect all of us, such as healthcare, smart cities, big data, among many others. The extended papers presented in the book contribute to achieving this goal.

This book reports on recent advances in software engineering research and practice. Divided into 15 chapters, it addresses: languages and tools; development processes; modelling, simulation and verification; and education. In the first category, the book includes chapters on domain-specific languages, software complexity, testing and tools. In the second, it reports on test-driven development, processing of business rules, and software management. In turn, subsequent chapters address modelling, simulation and verification of real-time systems, mobile systems and computer networks, and a scrum-based framework. The book was written by researchers and practitioners, the goal being to achieve a synergistic combination of research results achieved in academia and best practices used in the industry, and to provide a valuable reference guide for both groups.

This book is a collection of representative and novel works in the field of data mining, knowledge discovery, clustering and classification. Discussing both theoretical and practical aspects of "Knowledge Discovery and Management" (KDM), it is intended for researchers interested in these fields, including PhD and MSc students, and researchers from public or private laboratories. The contributions included are extended and reworked versions of six of the best papers that were originally presented in French at the EGC'2016 conference held in Reims (France) in January 2016. This was the 16th edition of this successful conference, which takes place each year, and also featured workshops and other events with the aim of promoting exchanges between researchers and companies concerned with KDM and its applications in business, administration, industry and public organizations. For more details about the EGC society, please consult egc.asso.fr.

This book presents recent research on Advanced Computing in Industrial Mathematics, which is one of the most prominent interdisciplinary areas, bringing together mathematics, computer science, scientific computations, engineering, physics, chemistry, medicine, etc.

This book presents a collection of contributions addressing recent advances and research in synergistic combinations of topics in the joint fields of intelligent computing and distributed computing. It focuses on the following specific topics: distributed data mining and machine learning, reasoning and decision-making in distributed environments, distributed evolutionary algorithms, trust and reputation models for distributed systems, scheduling and resource allocation in distributed systems, intelligent multi-agent systems, advanced agent-based and service-based architectures, and Smart Cloud and Internet of Things (IoT) environments. The book represents the combined peer-reviewed proceedings of the 11th International Symposium on Intelligent Distributed Computing (IDC 2017) and the 7th International Workshop on Applications of Software Agents (WASA 2017), both of which were held in Belgrade, Serbia from October 11 to 13, 2017.

This book presents the latest research of the field of optimization, modeling and algorithms, discussing the real-world application problems associated with new innovative methodologies.

This book brings together scientists, researchers, practitioners, and students from academia and industry to present recent and ongoing research activities concerning the latest advances, techniques, and applications of natural language processing systems, and to promote the exchange of new ideas and lessons learned. Taken together, the chapters of this book provide a collection of high-quality research works that address broad challenges in both theoretical and applied aspects of intelligent natural language processing. The book presents the state-of-the-art in research on natural language processing, computational linguistics, applied Arabic linguistics and related areas. New trends in natural language processing systems are rapidly emerging - and finding application in various domains including education, travel and tourism, and healthcare, among others. Many issues encountered during the development of these applications can be resolved by incorporating language technology solutions. The topics covered by the book include: Character and Speech Recognition; Morphological, Syntactic, and Semantic Processing; Information Extraction; Information Retrieval and Question Answering; Text Classification and Text Mining; Text Summarization; Sentiment Analysis; Machine Translation Building and Evaluating Linguistic Resources; and Intelligent Language Tutoring Systems.

This book reviews the state-of-the-art developments in nature-inspired algorithms and their applications in various disciplines, ranging from feature selection and engineering design optimization to scheduling and vehicle routing. It introduces each algorithm and its implementation with case studies as well as extensive literature reviews, and also includes self-contained chapters featuring theoretical analyses, such as convergence analysis and no-free-lunch theorems so as to provide insights into the current nature-inspired optimization algorithms. Topics include ant colony optimization, the bat algorithm, B-spline curve fitting, cuckoo search, feature selection, economic load dispatch, the firefly algorithm, the flower pollination algorithm, knapsack problem, octonian and quaternion representations, particle swarm optimization, scheduling, wireless networks, vehicle routing with time windows, and maximally different alternatives. This timely book serves as a practical guide and reference resource for students, researchers and professionals.