Abstract: This paper investigates the optimization of production process decisions based on nonlinear programming and particle swarm optimization genetic algorithm ...

Abstract: This paper presents a multi-objective optimization approach using Genetic Algorithms (GAs) to address the Airport Check-In Counter Allocation problem. A hybrid model balancing operational ...

This project implements an advanced Virtual Machine Placement (VMP) optimization system that leverages multi-objective genetic algorithms, machine learning predictions, blockchain technology, and ...

If you’ve ever felt frustrated by Spotify‘s algorithm recommending songs that don’t match your taste, there’s some good news. The streaming giant is finally giving you a way to take control of its ...

The new feature is simply called "Your Algorithm," and is available in the "reels" tab of the social media platform. Instagram said it is giving users more control over their algorithm — with the help ...

Introduction: Optimizing fracturing parameters under multi-factor, complex conditions remains challenging in low-permeability reservoirs. Methods: We extract stage-aware construction-curve features, ...

High-dimensional data often contain noisy and redundant features, posing challenges for accurate and efficient feature selection. To address this, a dynamic multitask learning framework is proposed, ...

Learn the Adagrad optimization algorithm, how it works, and how to implement it from scratch in Python for machine learning models. #Adagrad #Optimization #Python Trump administration looking to sell ...

GeneticSharp is a fast, extensible, multi-platform and multithreading C# Genetic Algorithm library that simplifies the development of applications using Genetic Algorithms (GAs).

Department of Intelligent Energy and Industry, Chung-Ang University, 84 Heukseok-ro, Dongjak-gu, Seoul 06974, Republic of Korea Department of Intelligent Energy and Industry, Chung-Ang University, 84 ...