Applications of Evolutionary Computation: Lecture Notes in Computer Science, cartea 12104
Editat de Pedro A. Castillo, Juan Luis Jiménez Laredo, Francisco Fernández de Vegaen Limba Engleză Paperback – 11 mar 2020
The 44 full papers presented in this book were carefully reviewed and selected from 62 submissions. The papers cover a wide spectrum of topics, ranging from applications of bio-inspired techniques on social networks, evolutionary computation in digital healthcare and personalized medicine, soft-computing applied to games, applications of deep-bioinspired algorithms, parallel and distributed systems, and evolutionary machine learning.
Din seria Lecture Notes in Computer Science
- 20%
Preț: 558.53 lei - 20%
Preț: 571.88 lei - 20%
Preț: 675.83 lei - 20%
Preț: 1020.28 lei - 20%
Preț: 620.33 lei - 20%
Preț: 560.93 lei - 20%
Preț: 633.70 lei - 20%
Preț: 678.21 lei - 20%
Preț: 1359.66 lei - 20%
Preț: 560.93 lei - 20%
Preț: 733.68 lei - 20%
Preț: 793.92 lei - 15%
Preț: 558.12 lei - 20%
Preț: 793.92 lei - 20%
Preț: 560.93 lei - 20%
Preț: 748.63 lei - 20%
Preț: 562.49 lei - 20%
Preț: 1246.46 lei - 20%
Preț: 449.81 lei - 20%
Preț: 556.96 lei - 20%
Preț: 562.49 lei - 20%
Preț: 851.78 lei - 20%
Preț: 313.10 lei - 18%
Preț: 945.44 lei - 20%
Preț: 314.86 lei - 20%
Preț: 560.93 lei - 20%
Preț: 313.87 lei - 20%
Preț: 1033.45 lei - 20%
Preț: 563.29 lei - 20%
Preț: 733.68 lei - 20%
Preț: 1137.10 lei - 20%
Preț: 735.28 lei - 20%
Preț: 1079.23 lei - 20%
Preț: 560.11 lei - 20%
Preț: 791.54 lei - 15%
Preț: 672.87 lei - 20%
Preț: 1032.47 lei - 20%
Preț: 617.17 lei - 20%
Preț: 1022.15 lei - 20%
Preț: 984.64 lei - 20%
Preț: 620.33 lei - 20%
Preț: 979.25 lei - 20%
Preț: 402.28 lei - 20%
Preț: 316.28 lei - 20%
Preț: 636.06 lei - 20%
Preț: 320.24 lei - 20%
Preț: 328.94 lei
Preț: 343.86 lei
Preț vechi: 429.81 lei
-20%
Puncte Express: 516
Preț estimativ în valută:
60.80€ • 70.27$ • 52.53£
60.80€ • 70.27$ • 52.53£
Carte tipărită la comandă
Livrare economică 04-18 mai
Specificații
ISBN-13: 9783030437213
ISBN-10: 3030437213
Pagini: 724
Ilustrații: XVII, 704 p. 251 illus., 177 illus. in color.
Dimensiuni: 155 x 235 x 39 mm
Greutate: 1.08 kg
Ediția:1st edition 2020
Editura: Springer
Colecția Lecture Notes in Computer Science
Seria Lecture Notes in Computer Science
Locul publicării:Cham, Switzerland
ISBN-10: 3030437213
Pagini: 724
Ilustrații: XVII, 704 p. 251 illus., 177 illus. in color.
Dimensiuni: 155 x 235 x 39 mm
Greutate: 1.08 kg
Ediția:1st edition 2020
Editura: Springer
Colecția Lecture Notes in Computer Science
Seria Lecture Notes in Computer Science
Locul publicării:Cham, Switzerland
Cuprins
Applications of Evolutionary Computation.- A Local Search for Numerical Optimisation based on Covariance Matrix Diagonalisation.- EvoCluster: An Open-Source Nature-Inspired Optimization Clustering Framework in Python.- Optimizing the Hyperparameters of a Mixed Integer Linear Programming Solver to Speed Up Electric Vehicle Charging Control.- Automatic rule extraction from access rules using Genetic Programming.- Search Trajectory Networks of Population-based Algorithms in Continuous Spaces.- Evolving-controllers versus learning-controllers for morphologically evolvable robots.- Simulation-driven multi-objective evolution for traffic light optimization.- Automatic Generation of Adversarial Metamorphic Malware Using MAP-Elites.- EvoDynamic: a framework for the evolution of generally represented dynamical systems and its application to criticality.- A Decomposition-Based Evolutionary Algorithm with Adaptive Weight Vectors for Multi- and Many-objective Optimization.- Differential Evolution Multi-Objective for Tertiary Protein Structure Prediction.- Particle Swarm Optimization: A Wrapper-based Feature Selection Method for Ransomware Detection and Classification.- A method for estimating the computational complexity of multimodal functions.- Locating Odour Sources with Geometric Syntactic Genetic Programming.- Designing cable-stayed bridges with Genetic Algorithms.- A fast, scalable meta-heuristic for network slicing under traffic uncertainty.- What is Your MOVE: Modeling Adversarial Network Environments.- Using evolution to design modular robots: An empirical approach to select module designs.- Iterated Granular Neighborhood Algorithm for the Taxi Sharing Problem.- Applications of Bio-inspired techniques on Social Networks.- Multiobjective Optimization of a Targeted Vaccination Scheme in the Presence of Non-diagnosed Cases.- Community Detection in Attributed Graphs with Differential Evolution.- Applications of Deep Bioinspired Algorithms.- Fake news detection usingtime series and user features classification.- Social Learning vs Self-teaching in a Multi-agent Neural Network System.- Evolving Instinctive Behaviour in Resource-Constrained Autonomous Agents Using Grammatical Evolution.- An Adversarial Optimization Approach for the Development of Robust Controllers.- Soft Computing Applied to Games.- Efficient Heuristic Policy Optimisation for a Challenging Strategic Card Game.- Finding Behavioural Patterns Among League of Legends Players Through Hidden Markov Models.- Learning the Designer's Preferences to Drive Evolution.- Testing hybrid computational intelligence algorithms for general game playing.- Evolutionary Computation in Digital Healthcare and Personalized Medicine.- Accelerated Design of HIFU Treatment Plans Using Island-based Evolutionary Strategy.- Using Genetic Algorithms for the prediction of cognitive impairments.- Short and Medium Term Blood Glucose Prediction using Multi-Objective Grammatical Evolution.- Evolutionary Machine Learning.- A Greedy Iterative Layered Framework for Training Feed Forward Neural Networks.- Evolution of Scikit-Learn Pipelines with Dynamic Structured Grammatical Evolution.- An Empirical Exploration of Deep Recurrent Connections Using Neuro-Evolution.- Using Skill Rating as Fitness on the Evolution of GANs.- A Local Search with a Surrogate Assisted Option for Instance Reduction.- Evolutionary Latent Space Exploration of Generative Adversarial Networks.- Neuro-Evolutionary Transfer Learning through Structural Adaptation.- Ant-based Neural Topology Search (ANTS) for Optimizing Recurrent Networks.- Parallel and Distributed Systems.- A MIMD interpreter for Genetic Programming.- Security Risk Optimization for Multi-Cloud Applications.- Using evolutionary algorithms for server hardening via the moving target defense technique.- An Event-based Architecture for Cross-Breed Multi-population Bio-inspired Optimization Algorithms.