KI-Beratung Beta
Vor Ort
Merkzettel Warenkorb
  • Produktbild: Applications of Evolutionary Computation
  • Produktbild: Applications of Evolutionary Computation
Band 15613

Applications of Evolutionary Computation 28th European Conference, EvoApplications 2025, Held as Part of EvoStar 2025, Trieste, Italy, April 23–25, 2025, Proceedings, Part II

Aus der Reihe Lecture Notes in Computer Science

78,99 €

inkl. gesetzl. MwSt., Versandkostenfrei

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

24.04.2025

Abbildungen

XXII, 560 p. 160 illus., 136 illus. in color.

Herausgeber

Pablo García-Sánchez + weitere

Verlag

Springer

Seitenzahl

560

Maße (L/B/H)

23,5/15,5/3,2 cm

Gewicht

873 g

Sprache

Englisch

ISBN

978-3-031-90064-8

Beschreibung

Produktdetails

Einband

Taschenbuch

Erscheinungsdatum

24.04.2025

Abbildungen

XXII, 560 p. 160 illus., 136 illus. in color.

Herausgeber

Verlag

Springer

Seitenzahl

560

Maße (L/B/H)

23,5/15,5/3,2 cm

Gewicht

873 g

Sprache

Englisch

ISBN

978-3-031-90064-8

Herstelleradresse

Springer-Verlag KG
Sachsenplatz 4-6
1201 Wien
AT

Email: ProductSafety@springernature.com

Ein neues Kapitel für Ihre Bücher

Ein neues Kapitel für Ihre Bücher

Schenken Sie Ihren alten Schätzen ein zweites Leben und erhalten Sie dafür eine Thalia Geschenkkarte.

Jetzt verkaufen
Jetzt verkaufen

Noch keine Bewertungen vorhanden

Verfassen Sie die erste Bewertung zu diesem Artikel

Helfen Sie anderen Kundinnen und Kunden durch Ihre Meinung.

Kundinnen und Kunden meinen

Bewertungen (0)
  • Produktbild: Applications of Evolutionary Computation
  • Produktbild: Applications of Evolutionary Computation

  • .- Evolutionary machine learning.

    .- Social Interpretable Reinforcement Learning.

    .- Into the Black Box: Mining Variable Importance with XAI.

    .- Evolving RNNs for Stock Forecasting: A Low Parameter Efficient Alternative to Transformers.

    .- Generate more than one child in your co-evolutionary semi-supervised learning GAN.

    .- EDCA – An Evolutionary Data-Centric AutoML Framework for Efficient Pipelines.

    .- 30 years of particle swarm optimisation.

    .- Proposal of Efficient Particle Swarm Optimization for Constrained Optimization Problems.

    .- A Survey of Modern Hybrid Particle Swarm Optimization Algorithms.

    .- An Investigation of Structural Bias in Particle Swarm Optimization.

    .- GPSO in PTO.

    .- We are Sending you Back... to the Optimum! Fuzzy Time Travel Particle Swarm Optimization.

    .- Memetic Variations of Overlapping Swarm Intelligence.

    .- Analysis of Evolutionary Computation Methods: Theory, Empirics, and Real-World Applications.

    .- Multi-Tree Genetic Programming for Large-scale Dynamic Tugboat Scheduling.

    .- Bio-inspired Algorithms for Green Computing and Sustainable Complex Systems.

    .- Hybridization of techniques based on Genetic Algorithms and Neural Networks to determine the water requirements of fig trees.

    .- Evaluating the Impact of Hysteretic Phenomena and Implementation Choices on Energy Consumption in Evolutionary Algorithms.

    .- Measuring energy consumption of BBOB fitness functions.

    .- Computational Intelligence for Sustainability.

    .- A PSO-based MPPT with Dynamic Monitoring Reset for PV Systems.

    .- An innovative approach for managing the water requirements of fig trees using artificial intelligence.

    .- GPBus: Genetic Programming based Automated Machine Learning for Bus Delay Prediction.

    .- Improving Fairness in Allocation of Emergency Medical Services using Multi-Objective Evolutionary Optimization.

    .- A Multi-Agent System for Optimal Train Scheduling in Single-Track Railways.

    .- EvoLLMs (Integrating Evolutionary Computing with Large Language Models (LLMs).

    .- Evolutionary Bias Identification with Embeddings.

    .- Probing LLMs on Optimization Problems: Can They Recall and Interpret Problem Features?.

    .- Open and Closed-source Models for LLM-generated Metaheuristics Solving Engineering Optimization Problem.

    .- Beyond the Hype: Benchmarking LLM-Evolved Heuristics for Bin Packing.

    .- Controlling the Mutation in Large Language Models for the Efficient Evolution of Algorithms.

    .- Evolutionary Computation in Edge, Fog, and Cloud Computing.

    .- A Communication-aware and Energy-efficient Genetic Programming based Method for Dynamic Resource Allocation in Clouds.

    .- A Genetic Algorithm-Based Parameter Selection for Communication Efficient Federated Learning.

    .- Evolutionary Computation in Image Analysis, Signal Processing, and Pattern Recognition.

    .- Evolving Cellular Automata with Function-Based Conditional Rules for Image Filtering.

    .- Machine Learning and AI in Digital Healthcare and Personalized Medicine.

    .- Addressing Radiotherapy Scheduling with a Bin Packing Problem Formulation: A Comparative Study of Exact Solvers and Genetic Algorithms.

    .- A Symbolic Regression Screening Approach within Peptide Optimisation.

    .- Estimation of total body fat using symbolic regression and evolutionary algorithms.

    .- Soft Computing Applied to Games.

    .- Injecting Combinatorial Optimization into MCTS: Application to the Board Game boop.

    .- Robust search for the underlying objectives in black-box games with binary outcomes.