الصفحة 4
الصفحة 4
Soft Computing for Hybrid Intelligent Systems
Soft Computing (SC) consists of several intelligent computing paradigms, including fuzzy logic, neural networks, and evolutionary algorithms, This edited book comprises papers on diverse aspects of soft computing and hybrid intelligent systems. There are theoretical aspects as well as application papers. The first part consists of papers with the main theme of intelligent control, The second part contains papers with the main theme of pattern recognition, The third part contains papers with the themes of intelligent agents and social systems, The fourth part contains papers that deal with the hardware implementation of intelligent systems for solving particular problems. The fifth part contains papers that deal with modeling, simulation and optimization for real-world applications.
Soft Computing as Transdisciplinary Science and Technology ; Proceedings of the fourth IEEE International Workshop WSTST´05
Presents the proceedings of the Fourth International Workshop on Soft Computing as Transdisciplinary Science and Technology (WSTST '05), May 25-27, 2005, Muroran, Japan. It brings together the original work of international soft computing/computational intelligence researchers, developers, practitioners, and users. This proceedings provide contributions to all areas of soft computing including intelligent hybrid systems, agent-based systems, intelligent data mining, decision support systems, cognitive and reactive distributed artificial intelligence (AI), internet modelling, human interface, and applications in science and technology.
Soft Computing Applications in Business
Soft computing techniques are widely used in most businesses. This book consists of several important papers on the applications of soft computing techniques for the business field.The soft computing techniques used in this book include (or very closely related to): Bayesian networks, biclustering methods, case-based reasoning, data mining, Dempster-Shafer theory, ensemble learning, evolutionary programming, fuzzy decision trees, hidden Markov models, intelligent agents, k-means clustering, maximum likelihood Hebbian learning, neural networks, opportunistic scheduling, probability distributions combined with Monte Carlo methods, rough sets, self organizing maps, support vector machines, uncertain reasoning, other statistical and machine learning techniques, and combinations of these techniques.
Soft Computing and its Engineering Applications ; 2nd International Conference, icSoftComp 2020, Changa, Anand, India, December 11–12, 2020, Proceedings
Constitutes the refereed proceedings of the Second International Conference on Soft Computing and its Engineering Applications, icSoftComp 2020, held in Changa, India, in December 2020. Due to the COVID-19 pandemic the conference was held online. The 24 full papers and 4 short papers presented were carefully reviewed and selected from 252 submissions. The papers present recent research on theory and applications in fuzzy computing, neuro computing, and evolutionary computing.
Soft Computing : Methodologies and Applications
This carefully edited book covers a wide range of application areas of soft computing like optimization, data analysis and data mining, fault diagnosis, control as well as traffic and transportation systems. It contains 25 revised contributions from the 8th Online World Conferences on Soft Computing (WSC8). The collected papers show how the major soft computing techniques, fuzzy systems, neural networks and evolutionary algorithms and especially hybrid systems combining methods from these fields, lead to successful industrial applications. The reader will find an interesting, inspiring and wide variety of soft computing techniques and applications in this book.
Simulation-based Algorithms for Markov Decision Processes
Markov decision process (MDP) models are widely used for modeling sequential decision-making problems that arise in engineering, economics, computer science, and the social sciences. It is well-known that many real-world problems modeled by MDPs have huge state and/or action spaces, leading to the notorious curse of dimensionality that makes practical solution of the resulting models intractable. In other cases, the system of interest is complex enough that it is not feasible to specify some of the MDP model parameters explicitly, but simulation samples are readily available (e.g., for random transitions and costs). For these settings, various sampling and population-based numerical algorithms have been developed recently to overcome the difficulties of computing an optimal solution in terms of a policy and/or value function.
Simulation, Modeling, and Programming for Autonomous Robots ; 1st International Conference, SIMPAR 2008 Venice, Italy, November 3-6, 2008. Proceedings
The book address all current issues of robotics applications and simulation environments thereof, such as 3D robot simulation, reliability, scalability and validation of robot simulation, simulated sensors and actuators, offline simulation of robot design, online simulation with realtime constraints, simulation with software/hardware-in-the-loop, middleware for robotics, modeling framework for robots and environments, testing and validation of robot control software, standardization for robotic services, communication infrastructures in distributed robotics, interaction between sensor networks and robots, human robot interaction, and multirobot. The papers are organized in topical sections on simulation, programming, and applications.
Simulated Evolution and Learning ; 7th International Conference, SEAL 2008, Melbourne, Australia, December 7-10, 2008. Proceedings
Covers are evolutionary learning; evolutionary optimisation; hybrid learning; adaptive systems; theoretical issues in evolutionary computation; and real-world applications of evolutionary computation techniques.
Signal Processing Techniques for Knowledge Extraction and Information Fusion
This state-of-the-art resource brings together the latest findings from the cross-fertilization of signal processing, machine learning and computer science. The emphasis is on demonstrating synergy of different signal processing methods with knowledge extraction and heterogeneous information fusion. Issues related to the processing of signals with low signal-to-noise ratio, solving real-world multi-channel problems, and using adaptive techniques where nonstationarity, uncertainty and complexity play major roles are addressed. Particular methods include Independent Component Analysis, Support Vector Machines, Distributed and Collaborative Adaptive Filtering, Empirical Mode Decomposition, Self Organizing Maps, Fuzzy Logic, Evolutionary Algorithms and several others used frequently in these fields. Also included are both important and novel applications from telecommunications, renewable energy and biomedical engineering.
Short-Period Binary Stars : Observations, Analyses, and Results
Short-period binaries run the gamut from widely separated stars to black-hole pairs; in between are systems that include neutron stars and white dwarfs, and partially evolved systems such as tidally distorted and over-contact systems. These objects represent stages of evolution of binary stars, and their degrees of separation provide critical clues to how their evolutionary paths differ from that of single stars. The widest and least distorted systems provide astronomers with the essential precise data needed to study all stars: mass and radius. The interactions of binary star components, on the other hand, provide a natural laboratory to observe how the matter in these stars behaves under different and often varying physical conditions.
Shortest Connectivity : An Introduction with Applications in Phylogeny
This volume is an introduction to the theory of "Shortest Connectivity", as the core of the so-called "Geometric Network Design Problems", where the general problem can be stated as follows: given a configuration of vertices and/or edges, find a network which contains these objects, satisfies some predetermined requirements, and which minimizes a given objective function that depends on several distance measures. A new application of shortest connectivity is also discussed, namely to create trees which reflect the evolutionary history of "living entities".
Service-Oriented Computing - ICSOC 2006 ; 4th International Conference, Chicago, IL, USA, December 4-7, Proceedings
This volume contains the proceedings of the 4th International Conference on Service- Oriented Computing (ICSOC 2006), which took place in Chicago, USA, 2006. Service-oriented computing brings together ideas and technologies from many d- ferent fields in an evolutionary manner to address research challenges such as service composition, discovery, integration, monitoring and management of services, service quality and security, methodologies for supporting service development, governances in their evolution, as well as their overall life-cycle management.
Sensitivity Analysis : Matrix Methods in Demography and Ecology
This book shows how to use sensitivity analysis in demography. It presents new methods for individuals, cohorts, and populations, with applications to humans, other animals, and plants. The analyses are based on matrix formulations of age-classified, stage-classified, and multistate population models. Methods are presented for linear and nonlinear, deterministic and stochastic, and time-invariant and time-varying cases. Readers will discover results on the sensitivity of statistics of longevity, life disparity, occupancy times, the net reproductive rate, and statistics of Markov chain models in demography. They will also see applications of sensitivity analysis to population growth rates, stable population structures, reproductive value, equilibria under immigration and nonlinearity, and population cycles. Individual stochasticity is a theme throughout, with a focus that goes beyond expected values to include variances in demographic outcomes.
Self-Organizing Systems; First International Workshop, IWSOS 2006 and Third International Workshop on New Trends in Network Architectures and Services, EuroNGI 2006, Passau, Germany, September 18-20, 2006, Proceedings
This book constitutes the refereed proceedings of the First International Workshop on Self-Organizing Systems, IWSOS 2006. The book offers 16 revised full papers and 6 revised short papers together with 2 invited talks and 3 poster papers. The papers are organized in topical sections on dynamics of structured and unstructured overlays, self-organization in peer-to-peer networks, self-organization in wireless environments, self-organization in distributed and grid computing, self-managing and autonomic computing, and more.
Self-Organizing Systems ; 2nd International Workshop, IWSOS 2007, The Lake District, UK, September 11-13, 2007, Proceedings
The 17 revised full papers and five revised short papers presented together with two invited talks were carefully selected from more than 36 submissions. The papers are organized in topical sections on ad hoc routing, peer-to-peer networking, network topology, adaptive and self-organizing networks and multicast and mobility protocols.
Self-Adaptive Heuristics for Evolutionary Computation
This book introduces various types of self-adaptive parameters for evolutionary computation. Biased mutation for evolution strategies is useful for constrained search spaces. Self-adaptive inversion mutation accelerates the search on combinatorial TSP-like problems. After the analysis of self-adaptive crossover operators the book concentrates on premature convergence of self-adaptive mutation control at the constraint boundary. Besides extensive experiments, statistical tests and some theoretical investigations enrich the analysis of the proposed concepts.
Selective Sentinel Lymphadenectomy for Human Solid Cancer
Lymph node (LN) status is the most important prognostic indicator for the clinical outcome of patients in human solid cancer. Recent developments in sentinel lymph node (SLN) concept and technology have resulted in the application of this revolutionary approach to determine if cancer has metastasized. The underlying thesis in solid cancer biology is that metastasis generally starts in an orderly progression, often spreading through the lymphatic channels to the SLN. Thus, the logical approach is to harvest that specific SLN for thorough analysis.
Selected Topics in Cancer Modeling : Genesis, Evolution, Immune Competition, and Therapy
A major challenge in the modeling and simulation of tumor growth is the mathematical description of living matter, which is far more complex than a mathematical description of inert matter. One critical piece of this challenge is creating multiscale models that take into account subcellular, cellular, and macroscopic levels of cancer. The complexity of these different levels requires the development of new mathematical methods and ideas, which are examined in this work. Written by first-rate researchers in the field of mathematical biology, this collection of selected chapters offers a comprehensive overview of state-of-the-art mathematical methods and tools for modeling and analyzing cancer phenomena.
Science with the Atacama Large Millimeter Array : A New Era for Astrophysics
Describes the enormous capabilities of ALMA, the state of the project, and most notably the scientific prospects with such a unique facility. The book includes comprehensive reviews and recent results on most hot topics of modern Astronomy (the formation and evolution of galaxies, the physics and chemistry of the interstellar medium, and the processes of star and planet formation) with prospects to the revolutionary results to be obtained with ALMA. These topics, discussed with special emphasis on millimeter and sub-millimeter astronomy, are presented by some of the most world-wide reputed scientists in their fields.
Scalable Optimization via Probabilistic Modeling : From Algorithms to Applications
The volume Scalable Optimization via Probabilistic Modeling: From Algorithms to Applications is a worthy addition to your library because it succeeds on exactly those dimensions where so many edited.
