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The inspiration from Biology and the Natural Evolution process has become a research area within computer science. For instance, the description of the arti?cial neuron given by McCulloch and Pitts was inspired from biological observations of neural mechanisms; the power of evolution in nature in the diverse species that make up our world has been related to a particular form of problem solving based on the idea of survival of the ?ttest; similarly, - ti?cial immune systems, ant colony optimisation, automated self-assembling programming, membrane computing, etc. also have their roots in natural phenomena. The ?rst and second editions of the International Workshop on Nature Inspired Cooperati...
This book constitutes the thoroughly refereed post-proceedings of the 12th International Conference on Computer Aided Systems Theory, EUROCAST 2009, held in Las Palmas de Gran Canaria, Spain in February 2009. The 120 revised full papers presented were carefully reviewed and selected for inclusion in the book. The papers are organized in topical sections on systems theory and simulation: formal approaches, computation and simulation in modeling biological Systems, intelligent information processing, applied formal verification, computer vision and image processing, mobile and autonomous systems: robots and cars, simulation based system optimization, signal processing methods in systems design and cybernetics, polynomial models in control system design, heurist problem solving, simulation and formal methods in systems design and engineering, models of co-operative engineering systems.
This book constitutes the refereed proceedings of the Third International Workshop on Hybrid Metaheuristics, HM 2006, held in Gran Canaria, Spain, in October 2006. The 13 revised full papers presented together with one invited paper were carefully reviewed and selected from 42 submissions.
Exploratory data analysis, also known as data mining or knowledge discovery from databases, is typically based on the optimisation of a specific function of a dataset. Such optimisation is often performed with gradient descent or variations thereof. In this book, we first lay the groundwork by reviewing some standard clustering algorithms and projection algorithms before presenting various non-standard criteria for clustering. The family of algorithms developed are shown to perform better than the standard clustering algorithms on a variety of datasets. We then consider extensions of the basic mappings which maintain some topology of the original data space. Finally we show how reinforcement...
Solving complex optimization problems with parallel metaheuristics Parallel Metaheuristics brings together an international group of experts in parallelism and metaheuristics to provide a much-needed synthesis of these two fields. Readers discover how metaheuristic techniques can provide useful and practical solutions for a wide range of problems and application domains, with an emphasis on the fields of telecommunications and bioinformatics. This volume fills a long-existing gap, allowing researchers and practitioners to develop efficient metaheuristic algorithms to find solutions. The book is divided into three parts: * Part One: Introduction to Metaheuristics and Parallelism, including an...
This two-volume set LNCS 7902 and 7903 constitutes the refereed proceedings of the 12th International Work-Conference on Artificial Neural Networks, IWANN 2013, held in Puerto de la Cruz, Tenerife, Spain, in June 2013. The 116 revised papers were carefully reviewed and selected from numerous submissions for presentation in two volumes. The papers explore sections on mathematical and theoretical methods in computational intelligence, neurocomputational formulations, learning and adaptation emulation of cognitive functions, bio-inspired systems and neuro-engineering, advanced topics in computational intelligence and applications.
This book constitutes the refereed proceedings of the Third International Conference on Computational Logistics, held in Shanghai, China, in September 2012. The 15 revised full papers presented were carefully reviewed and selected from various submissions. The papers are organized in topical sections on maritime shipping; logistics and supply chain management; planning and operations; and case studies.
Text classification is becoming a crucial task to analysts in different areas. In the last few decades, the production of textual documents in digital form has increased exponentially. Their applications range from web pages to scientific documents, including emails, news and books. Despite the widespread use of digital texts, handling them is inherently difficult - the large amount of data necessary to represent them and the subjectivity of classification complicate matters. This book gives a concise view on how to use kernel approaches for inductive inference in large scale text classification; it presents a series of new techniques to enhance, scale and distribute text classification tasks. It is not intended to be a comprehensive survey of the state-of-the-art of the whole field of text classification. Its purpose is less ambitious and more practical: to explain and illustrate some of the important methods used in this field, in particular kernel approaches and techniques.
The two-volume set LNCS 12013 and 12014 constitutes the thoroughly refereed proceedings of the 17th International Conference on Computer Aided Systems Theory, EUROCAST 2019, held in Las Palmas de Gran Canaria, Spain, in February 2019. The 123 full papers presented were carefully reviewed and selected from 172 submissions. The papers are organized in the following topical sections: Part I: systems theory and applications; pioneers and landmarks in the development of information and communication technologies; stochastic models and applications to natural, social and technical systems; theory and applications of metaheuristic algorithms; model-based system design, verification and simulation. Part II: applications of signal processing technology; artificial intelligence and data mining for intelligent transportation systems and smart mobility; computer vision, machine learning for image analysis and applications; computer and systems based methods and electronic technologies in medicine; advances in biomedical signal and image processing; systems concepts and methods in touristic flows; systems in industrial robotics, automation and IoT.
We describe in this book, new methods for evolutionary design of intelligent s- tems using soft computing and their applications in modeling, simulation and c- trol. Soft Computing (SC) consists of several intelligent computing paradigms, including fuzzy logic, neural networks, and evolutionary algorithms, which can be used to produce powerful hybrid intelligent systems. The book is organized in four main parts, which contain a group of papers around a similar subject. The first part consists of papers with the main theme of evolutionary design of fuzzy systems in intelligent control, which consists of papers that propose new methods for designing and optimizing intelligent controllers for d...