Описание: The Italian community in Artificial Life and Evolutionary computation has grown remarkably over the years. This book presents a collection of its major interests and achievements (including contributions from foreign countries). It provides a broad picture of the Italian activities in this field.
Описание: This book comprises nine selected works on numerical and computational methods for solving multiobjective optimization, game theory, and machine learning problems.
Описание: Provides an in-depth and even treatment of the three pillars of computational intelligence and how they relate to one another This book covers the three fundamental topics that form the basis of computational intelligence: neural networks, fuzzy systems, and evolutionary computation.
Автор: Shengxiang Yang; Xin Yao Название: Evolutionary Computation for Dynamic Optimization Problems ISBN: 3642384153 ISBN-13(EAN): 9783642384158 Издательство: Springer Рейтинг: Цена: 32652.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides a compilation on the state-of-the-art and recent advances of evolutionary computation for dynamic optimization problems.
Описание: Recent Advances in Swarm Intelligence and Evolutionary Computation
Автор: Bin Hu; Manuel L?pez-Ib??ez Название: Evolutionary Computation in Combinatorial Optimization ISBN: 3319554522 ISBN-13(EAN): 9783319554525 Издательство: Springer Рейтинг: Цена: 7685.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: A Computational Study of Neighborhood Operators for Job-shop Scheduling Problems with Regular Objectives.- A Genetic Algorithm for Multi-Component Optimization Problems: the Case of the Travelling Thief Problem.- A Hybrid Feature Selection Algorithm Based on Large Neighborhood Search.- A Memetic Algorithm to Maximise the Employee Substitutability in Personnel Shift Scheduling.- Construct, Merge, Solve and Adapt versus Large Neighborhood Search for Solving the Multi-Dimensional Knapsack Problem: Which One Works Better When.- Decomposing SAT Instances with Pseudo Backbones.- Efficient Consideration of Soft Time Windows in a Large Neighborhood Search for the Districting and Routing Problem for Security Control.- Estimation of Distribution Algorithms for the Firefighter Problem.- LCS-Based Selective Route Exchange Crossover for the Pickup and Delivery Problem with Time Windows.- Multi-rendezvous Spacecraft Trajectory Optimization with Beam P-ACO.- Optimizing Charging Station Locations for Electric Car-Sharing Systems.- Selection of Auxiliary Objectives Using Landscape Features and Offline Learned Classifier.- Sparse, Continuous Policy Representations for Uniform Online Bin Packing via Regression of Interpolants.- The Weighted Independent Domination Problem: ILP Model and Algorithmic
Описание: This book comprises selected research papers from the 2015 edition of the EVOLVE conference, which was held on June 18-June 24, 2015 in Iasi, Romania.
Автор: Ashish Ghosh Название: Evolutionary Computation in Data Mining ISBN: 3642421954 ISBN-13(EAN): 9783642421952 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Data mining (DM) consists of extracting interesting knowledge from re- world, large & complex data sets; The goal of data preprocessing methods is to transform the data to facilitate the application of a (or several) given DM algorithm(s), whereas the goal of knowledge refinement methods is to validate and refine discovered knowledge.
Автор: Cuevas, Erik, Osuna, Valentin, Oliva, Diego Название: Evolutionary Computation Techniques: A Comparative Perspective ISBN: 3319511084 ISBN-13(EAN): 9783319511085 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book compares the performance of various evolutionary computation (EC) techniques when they are faced with complex optimization problems extracted from different engineering domains.
Описание: This book provides strong theoretical support for analyzing the behavior of evolutionary algorithms and for bridging probability, set-oriented numerics and evolutionary computation. Offers theoretical findings, optimization problems and new perspectives.
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