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Theory and Practice of Natural Computing
This book constitutes the refereed proceedings of the First International Conference, TPNC 2012, held in Tarragona, Spain, in October 2012. The 12 revised full papers presented together with 6 invited talks were carefully reviewed and selected from 34 submissions. The papers are organized in topical sections on nature-inspired models of computation; synthesizing nature by means of computation; nature-inspired materials; and information processing in nature.
Applied Optimization and Swarm Intelligence
This book gravitates on the prominent theories and recent developments of swarm intelligence methods, and their application in both synthetic and real-world optimization problems. The special interest will be placed in those algorithmic variants where biological processes observed in nature have underpinned the core operators underlying their search mechanisms. In other words, the book centers its attention on swarm intelligence and nature-inspired methods for efficient optimization and problem solving. The content of this book unleashes a great opportunity for researchers, lecturers and practitioners interested in swarm intelligence, optimization problems and artificial intelligence.
Contemporary Issues in Wireless Communications
Wireless communications have a strong impact on improving the quality of life in this century. Smart phones industry is now considered one of the most attractive fields, so advanced research is conducted in order to improve the quality of service in wireless communication environments. Many design challenges such as power consumption, quality of service, low cost, high data rate and small size are being treated every day. This book aims to provide highlights of the current research in the field of wireless communications. The subjects discussed are very valuable to communication researchers as well as researchers in the wireless related areas. The book chapters cover a wide range of wireless communication topics that are considered key technologies for future applications.
Simulated Evolution and Learning
This book constitutes the refereed proceedings of the 6th International Conference on Simulated Evolution and Learning, SEAL 2006, held in Hefei, China in October 2006. The 117 revised full papers presented were carefully reviewed and selected from 420 submissions.
Transdisciplinary Engineering for Complex Socio-technical Systems
Industry and society are complex socio-technical systems, and both face problems that can only be solved by collaboration between different disciplines. Collaboration between academia and practice is also needed to develop viable solutions. Many engineering problems also require such an approach, which is known as Transdisciplinary Engineering (TE). This book presents the proceedings of the 26th ISTE International Conference on Transdisciplinary Engineering, held in Tokyo, Japan, from 30 July - 1 August 2019. The title of the conference was: Transdisciplinary Engineering for Complex Socio-technical Systems, and of the 86 submitted papers, 68 peer-reviewed papers by authors from 17 countries ...
Adversarial Machine Learning
A critical challenge in deep learning is the vulnerability of deep learning networks to security attacks from intelligent cyber adversaries. Even innocuous perturbations to the training data can be used to manipulate the behaviour of deep networks in unintended ways. In this book, we review the latest developments in adversarial attack technologies in computer vision; natural language processing; and cybersecurity with regard to multidimensional, textual and image data, sequence data, and temporal data. In turn, we assess the robustness properties of deep learning networks to produce a taxonomy of adversarial examples that characterises the security of learning systems using game theoretical...
Applied Machine Learning and Data Analytics
This book constitutes the refereed proceedings of the 5th International Conference on Applied Machine Learning and Data Analytics, AMLDA 2022, held in Reynosa, Tamaulipas, Mexico, during December 22–23, 2022. The 16 full papers and 4 short papers included in this book were carefully reviewed and selected from 89 submissions. They were organized in topical sections as follows: Machine learning, Healthcare and medical imaging informatics; biometrics; forensics; precision agriculture; risk management; robotics and satellite imaging.
DIE ARCHITEKTURTYPEN DES "SELF-ORGANIZING (FEATURE) MAP (SO(F)M)" NACH TEUVO KOHONEN
Das Buch stellt eine leicht überarbeitete Fassung meiner Studienarbeit dar, die ich im Fachbereich Informatik bei Prof. Dr. M. Bogdan im Wintersemester 2003/04 und im Sommersemester 2004 geschrieben habe. Es gibt erstmals einen umfassenden Überblick über die wichtigsten Architekturtypen der "Selbstorganisierende (Merkmals-)Karte" (engl."Self-Organizing (Feature) Map (SO(F)M))" des finnischen Ingenieurs Teuvo Kohonen, auch "Kohonen-Karte" genannt, die eine der bedeutendsten Modelle im Rahmen der Theorie der künstlichen Neuronalen Netzwerke darstellt. Es werden dabei die relevantesten Passagen aus den wichtigsten Artikeln der jeweiligen Autoren zitiert, die die zentralen Konzepte der diversen Architekturmodelle wiedergeben und dann zusammengefaßt und kommentiert.
Optimization Under Uncertainty with Applications to Aerospace Engineering
In an expanding world with limited resources, optimization and uncertainty quantification have become a necessity when handling complex systems and processes. This book provides the foundational material necessary for those who wish to embark on advanced research at the limits of computability, collecting together lecture material from leading experts across the topics of optimization, uncertainty quantification and aerospace engineering. The aerospace sector in particular has stringent performance requirements on highly complex systems, for which solutions are expected to be optimal and reliable at the same time. The text covers a wide range of techniques and methods, from polynomial chaos expansions for uncertainty quantification to Bayesian and Imprecise Probability theories, and from Markov chains to surrogate models based on Gaussian processes. The book will serve as a valuable tool for practitioners, researchers and PhD students.
Integrating Meta-Heuristics and Machine Learning for Real-World Optimization Problems
This book collects different methodologies that permit metaheuristics and machine learning to solve real-world problems. This book has exciting chapters that employ evolutionary and swarm optimization tools combined with machine learning techniques. The fields of applications are from distribution systems until medical diagnosis, and they are also included different surveys and literature reviews that will enrich the reader. Besides, cutting-edge methods such as neuroevolutionary and IoT implementations are presented in some chapters. In this sense, the book provides theory and practical content with novel machine learning and metaheuristic algorithms. The chapters were compiled using a scientific perspective. Accordingly, the book is primarily intended for undergraduate and postgraduate students of Science, Engineering, and Computational Mathematics and can be used in courses on Artificial Intelligence, Advanced Machine Learning, among others. Likewise, the material can be helpful for research from the evolutionary computation, artificial intelligence communities.
