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Computer vision systems ; 6th International conference, ICVS 2008 Santorini, Greece, May 12-15, 2008 Proceedings
This book constitutes the refereed proceedings of the 6th International Conference on Computer Vision Systems, ICVS 2008, held in Santorini, Greece, May 12-15, 2008.
Computational intelligence in economics and finance ; Vol. II
Computational intelligence (CI), as an alternative to statistical and econometric approaches, has been applied to a wide range of economics and finance problems in recent years, for example to price forecasting and market efficiency. This book contains research ranging from applications in financial markets and business administration to various economics problems. Not only are empirical studies utilizing various CI algorithms presented, but so also are theoretical models based on computational methods. In addition to direct applications of computational intelligence, readers can also observe how these methods are combined with conventional analytical methods such as statistical and econometric models to yield preferred results.
Computational intelligence and security ; Vol. 3801 ; International Conference, CIS 2005, Xi'an, China, December 15-19, 2005, Proceedings, Part I
The two volume set LNAI 3801 and LNAI 3802 constitute the refereed proceedings of the annual International Conference on Computational Intelligence and Security, CIS 2005, held in Xi'an, China, in December 2005. The 338 revised papers presented - 254 regular and 84 extended papers - were carefully reviewed and selected from over 1800 submissions. The first volume is organized in topical sections on learning and fuzzy systems, evolutionary computation, intelligent agents and systems, intelligent information retrieval, support vector machines, swarm intelligence, data mining, pattern recognition, and applications.
Computational Discovery of Scientific Knowledge : Introduction, Techniques, and Applications in Environmental and Life Sciences
Advances in technology have enabled the collection of data from scientific observations, simulations, and experiments at an ever-increasing pace. For the scientist and engineer to benefit from these enhanced data collecting capabilities, it is becoming clear that semi-automated data analysis techniques must be applied to find the useful information in the data. Computational scientific discovery methods can be used to this end: they focus on applying computational methods to automate scientific activities, such as finding laws from observational data. In contrast to mining scientific data, which focuses on building highly predictive models, computational scientific discovery puts a strong emphasis on discovering knowledge represented in formalisms used by scientists and engineers, such as numeric equations and reaction pathways. This state-of-the-art survey provides an introduction to computational approaches to the discovery of scientific knowledge and gives an overview of recent advances in this area, including techniques and applications in environmental and life sciences.
Machine Learning: ECML 2007 ; 18th European Conference on Machine Learning, Warsaw, Poland, September 17-21, 2007, Proceedings
The two premier annual European conferences in the areas of machine learning and data mining have been collocated ever since the ?rst joint conference in Freiburg, 2001. The European Conference on Machine Learning (ECML) traces its origins to 1986, when the ?rst European Working Session on Learning was held in Orsay, France. The European Conference on Principles and Practice of KnowledgeDiscoveryinDatabases(PKDD) was?rstheldin1997inTrondheim, Norway.
Linear Genetic Programming
Linear Genetic Programming examines the evolution of imperative computer programs written as linear sequences of instructions. In contrast to functional expressions or syntax trees used in traditional Genetic Programming (GP), Linear Genetic Programming (LGP) employs a linear program structure as genetic material whose primary characteristics are exploited to achieve acceleration of both execution time and evolutionary progress.
Bioinspired optimization methods and their applications ; 9th International conference, BIOMA 2020, Brussels, Belgium, November 19–20, 2020, Proceedings
This book constitutes the refereed proceedings of the 9th International Conference on Bioinspired Optimization Methods and Their Applications, BIOMA 2020, held in Brussels, Belgium, in November 2020. The 24 full papers presented in this book were carefully reviewed and selected from 68 submissions. The papers in this BIOMA proceedings specialized in bioinspired algorithms as a means for solving the optimization problems and came in two categories: theoretical studies and methodology advancements on the one hand, and algorithm adjustments and their applications on the other.
Autonomic communication ; Vol. 3854 : 2nd International IFIP Workshop, WAC 2005, Athens, Greece, October 2-5, 2005, Revised Selected Papers
The Second IFIP Workshop on Autonomic Communication (WAC 2005) took place on October 2–5, 2005, IFIP TC6 provided scientific sponsorship through Working Groups IFIP WG6. 6 (Management of Networks and Distributed Systems) and IFIP WG6. 3 (Performance of Communication Systems). The workshop was organized at a time when the – yet to be well defined – field of autonomic communication (AC) is attracting the interest of both the scientific community and the research funding organizations. The latter is manifested, on one hand, by the numerous recent relevant research exploratory forums, workshop panels, preliminary forward-looking position papers, research outlooks and frameworks and, on the other hand, by the commitment of the FET program of the European Commission in Europe to funding long-term research in this area for the next four years.
Automatic Quantum Computer Programming : A Genetic Programming Approach
Computer science will be radically transformed if ongoing efforts to build large-scale quantum computers eventually succeed and if the properties of these computers meet optimistic expectations. Nevertheless, computer scientists still lack a thorough understanding of the power of quantum computing, and it is not always clear how best to utilize the power that it is understood. This dilemma exists because quantum algorithms are difficult to grasp and even more difficult to write. Despite large-scale international efforts, only a few important quantum algorithms are documented, leaving many essential questions about the potential of quantum algorithms unanswered.
Automated technology for verification and analysis ; 6th International Symposium, ATVA 2008, Seoul, Korea, October 20-23, 2008. Proceedings
This book constitutes the refereed proceedings of the 6th International Symposium on Automated Technology for Verification and Analysis, ATVA 2008, held in Seoul, Korea, in October 2008.
Artificial neural networks – ICANN 2007 ; 17th International Conference, Porto, Portugal, September 9-13, 2007, Proceedings, Part I
This book contains learning theory, advances in neural network learning methods, ensemble learning, spiking neural networks, advances in neural network architectures neural network technologies, neural dynamics and complex systems, data analysis, estimation, spatial and spatio-temporal learning, evolutionary computing, meta learning, agents learning, complex-valued neural networks, as well as temporal synchronization and nonlinear dynamics in neural networks.
Artificial immune systems ; Vol. 3627 ; 4th International conference, ICARIS 2005, Banff, Alberta, Canada, August 14-17, 2005, Proceedings
Your immune system is unique. It is in many ways as complex as your brain, butit is not centred in one location, like the brain. It is not a single organ—it consistsof many different cell types, diverse methods of intercellular communication, andmany different organs. Its functionality is blurred throughout you—we can’textract the immune system, or point to where it begins and ends. The immunesystem is not separable from the system it protects. It has integral links to everyorgan of our bodies.This has radical implications for the field of Artificial Immune Systems (AIS),that we are only now beginning to comprehend. One of the first insights is thatmodelling the immune system, or developing any kind of immune algorithm, isdifficult. The immune system is one aspect of biology that we find difficult toapply simple reductionist explanations to. We can very successfully extract sub-processes of the whole and create immune algorithms based on those processes.
Artificial evolution ; 8th International Conference, Evolution artificielle, EA 2007, Tours, France, October 29-31, 2007, revised selected papers
This book constitutes the thoroughly refereed post-conference proceedings of the 8th International Conference on Artificial Evolution, EA 2007, held in Tours, France in October 2007.
Artificial evolution ; 7th International Conference, Evolution artificielle, EA 2005, revised selected papers
This book constitutes the thoroughly refereed post-proceedings of the 7th International Conference on Artificial Evolution, EA 2005, held in Lille, France, in October 2005. They cover all aspects of artificial evolution: genetic programming, machinelearning, combinatorial optimization, co-evolution, self-assembling, artificial lifeand bioinformatics.In addition, the program included an invited talk by David Corne on “Evolu-tionary Computation in Bioinformatics: How to Save Lives and Make ScientificBreakthrough.
Applications and Innovations in Intelligent Systems XV ; Proceedings of AI-2007, the Twenty-seventh SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence
The papers in this volume are the refereed application papers presented at AI-2007, the Twenty-seventh SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, held in Cambridge in December 2007.
Applications and innovations in intelligent systems XII ; Proceedings of AI-2004, the Twenty-fourth SGAI International Conference on Innhovative Techniques and Applications of Artificial Intelligence
The papers in this volume are the refereed application papers presented at AI-2004, the Twenty-fourth SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, held in Cambridge 2004. The papers present new and innovative developments in the field, divided into sections on Synthesis and Prediction, Scheduling and Search, Diagnosis and Monitoring, Classification and Design, and Analysis and Evaluation. This is the twelth volume in the Applications and Innovations series. The series serves as a key reference on the use of AI Technology to enable organisations to solve complex problems and gain significant business benefits. The Technical Stream papers are published as a companion volume under the title Research and Development in Intelligent Systems XXI.
Advanced Intelligent Computing Theories and Applications : With Aspects of Contemporary Intelligent Computing Techniques ; 3rd International Conference on Intelligent Computing, ICIC 2007 Qingdao, China, August 21-24, 2007 Proceedings
The International Conference on Intelligent Computing (ICIC) was formed to provide an annual forum dedicated to the emerging and challenging topics in artificial intelligence, machine learning, bioinformatics, and computational biology, etc. It aims to bring - gether researchers and practitioners from both academia and industry to share ideas, problems and solutions related to the multifaceted aspects of intelligent computing.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.
Adaptive Learning of Polynomial Networks : Genetic Programming, Backpropagation and Bayesian Methods
This book provides theoretical and practical knowledge for develop ment of algorithms that infer linear and nonlinear models. It offers a methodology for inductive learning of polynomial neural network mod els from data. The design of such tools contributes to better statistical data modelling when addressing tasks from various areas like system identification, chaotic time-series prediction, financial forecasting and data mining. The main claim is that the model identification process involves several equally important steps: finding the model structure, estimating the model weight parameters, and tuning these weights with respect to the adopted assumptions about the underlying data distrib ution. When the learning process is organized according to these steps, performed together one after the other or separately, one may expect to discover models that generalize well.
Adaptive Business Intelligence
In the modern information era, managers must recognize the competitive opportunities represented by decision-support tools. Adaptive business intelligence systems combine prediction and optimization techniques to assist decision makers in complex, rapidly changing environments. These systems address the fundamental questions: What is likely to happen in the future? And what is the best decision right now? Adaptive Business Intelligence includes elements of data mining, predictive modeling, forecasting, optimization, and adaptability.
Adaptive and natural computing algorithms ; Proceedings of the International Conference in Coimbra, Portugal, 2005
The ICANNGA series of Conferences has been organised since 1993 and has a long history of promoting the principles and understanding of computational intelligence paradigms within the scientific community and is a reference for established workers in this area.and this book about Proceedings of the International Conference in Coimbra, Portugal, 2005 including Topics Artificial Intelligence Simulation and Modeling / Mathematics of Computing / Computer Applications
