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Nature-inspired meta-heuristics for power syste...
49,90 € *
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Nature-inspired meta-heuristics for power system optimization-Part 2 ab 49.9 EURO

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Stand: 21.02.2020
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Nature-inspired meta-heuristics for power syste...
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This book presents artificial immune system for optimal scheduling of thermal plants in coordination with fixed head hydro units. Numerical results for two test systems have been presented to demonstrate the performance of the proposed method. Results obtained from the proposed method have been compared to those obtained using differential evolution, particle swarm optimization and evolutionary programming technique.

Anbieter: Dodax
Stand: 21.02.2020
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Spamdexing
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High Quality Content by WIKIPEDIA articles! Spamdexing (also known as search spam, search engine spam or web spam)[1] involves a number of methods, such as repeating unrelated phrases, to manipulate the relevancy or prominence of resources indexed by a search engine, in a manner inconsistent with the purpose of the indexing system. Some consider it to be a part of search engine optimization, though there are many search engine optimization methods that improve the quality and appearance of the content of web sites and serve content useful to many users. Search engines use a variety of algorithms to determine relevancy ranking. Some of these include determining whether the search term appears in the META keywords tag, others whether the search term appears in the body text or URL of a web page. Many search engines check for instances of spamdexing and will remove suspect pages from their indexes. Also, people working for a search-engine organization can quickly block the results-listing from entire websites that use spamdexing, perhaps alerted by user complaints of false matches. The rise of spamdexing in the mid-1990s made the leading search engines of the time less useful.

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Design of Intelligent Systems Based on Fuzzy Lo...
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This book presents recent advances on the design of intelligent systems based on fuzzy logic, neural networks and nature-inspired optimization and their application in areas such as, intelligent control and robotics, pattern recognition, time series prediction and optimization of complex problems. The book is organized in eight main parts, which contain a group of papers around a similar subject. The first part consists of papers with the main theme of theoretical aspects of fuzzy logic, which basically consists of papers that propose new concepts and algorithms based on fuzzy systems. The second part contains papers with the main theme of neural networks theory, which are basically papers dealing with new concepts and algorithms in neural networks. The third part contains papers describing applications of neural networks in diverse areas, such as time series prediction and pattern recognition. The fourth part contains papers describing new nature-inspired optimization algorithms. The fifth part presents diverse applications of nature-inspired optimization algorithms. The sixth part contains papers describing new optimization algorithms. The seventh part contains papers describing applications of fuzzy logic in diverse areas, such as time series prediction and pattern recognition. Finally, the eighth part contains papers that present enhancements to meta-heuristics based on fuzzy logic techniques.

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Colliding Bodies Optimization
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This book presents and applies a novel efficient meta-heuristic optimization algorithm called Colliding Bodies Optimization (CBO) for various optimization problems. The first part of the book introduces the concepts and methods involved, while the second is devoted to the applications. Though optimal design of structures is the main topic, two chapters on optimal analysis and applications in constructional management are also included.This algorithm is based on one-dimensional collisions between bodies, with each agent solution being considered as an object or body with mass. After a collision of two moving bodies with specified masses and velocities, these bodies again separate, with new velocities. This collision causes the agents to move toward better positions in the search space.The main algorithm (CBO) is internally parameter independent, setting it apart from previously developed meta-heuristics. This algorithm is enhanced (ECBO) for more efficient applications in the optimal design of structures.The algorithms are implemented in standard computer programming languages (MATLAB and C++) and two main codes are provided for ease of use.

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Stand: 21.02.2020
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Fiber-Optic Transmission Networks
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Next generation optical communication systems will have to transport a significantly increased data volume at a reduced cost per transmitted bit. To achieve these ambitious goals optimum design is crucial in combination with dynamic adaptation to actual traffic demands and improved energy efficiency.In the first part of the book the author elaborates on the design of optical transmission systems. Several methods for efficient numerical simulation are presented ranging from meta-model based optimization to parallelization techniques for solving the nonlinear Schrödinger equation. Furthermore, fast analytical and semi-analytical models are described to estimate the various degradation effects occurring on the transmission line.In the second part of the book operational aspects of optical networks are investigated. Physical layer impairment-aware routing and regenerator placement are studied. Finally, it is analyzed how the energy efficiency of a multi-layer optical core network can be increased by dynamic adaptation to traffic patterns changing in the course of the day.

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Machine Learning and Knowledge Discovery in Dat...
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The three volume proceedings LNAI 10534 – 10536 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2017, held in Skopje, Macedonia, in September 2017. The total of 101 regular papers presented in part I and part II was carefully reviewed and selected from 364 submissions, there are 47 papers in the applied data science, nectar and demo track. The contributions were organized in topical sections named as follows: Part I: anomaly detection, computer vision, ensembles and meta learning, feature selection and extraction, kernel methods, learning and optimization, matrix and tensor factorization, networks and graphs, neural networks and deep learning. Part II: pattern and sequence mining, privacy and security, probabilistic models and methods, recommendation, regression, reinforcement learning, subgroup discovery, time series and streams, transfer and multi-task learning, unsupervised and semisupervised learning. Part III: applied data science track, nectar track, and demo track.

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Stand: 21.02.2020
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Modelling, Computation and Optimization in Info...
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This proceedings set contains 85 selected full papers presentedat the 3rd International Conference on Modelling, Computation and Optimization in Information Systems and Management Sciences - MCO 2015, held on May 11-13, 2015 at Lorraine University, France. The present part II of the 2 volume set includes articles devoted to Data analysis and Data mining, Heuristic / Meta heuristic methods for operational research applications, Optimization applied to surveillance and threat detection, Maintenance and Scheduling, Post Crises banking and eco-finance modelling, Transportation, as well as Technologies and methods for multi-stakeholder decision analysis in public settings.

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Stand: 21.02.2020
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Nature-Inspired Design of Hybrid Intelligent Sy...
251,63 € *
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This book highlights recent advances in the design of hybrid intelligent systems based on nature-inspired optimization and their application in areas such as intelligent control and robotics, pattern recognition, time series prediction, and optimization of complex problems. The book is divided into seven main parts, the first of which addresses theoretical aspects of and new concepts and algorithms based on type-2 and intuitionistic fuzzy logic systems. The second part focuses on neural network theory, and explores the applications of neural networks in diverse areas, such as time series prediction and pattern recognition. The book's third part presents enhancements to meta-heuristics based on fuzzy logic techniques and describes new nature-inspired optimization algorithms that employ fuzzy dynamic adaptation of parameters, while the fourth part presents diverse applications of nature-inspired optimization algorithms. In turn, the fifth part investigates applications of fuzzy logic in diverse areas, such as time series prediction and pattern recognition. The sixth part examines new optimization algorithms and their applications. Lastly, the seventh part is dedicated to the design and application of different hybrid intelligent systems.

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Stand: 21.02.2020
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