A recent study introduces an advanced anomaly-based intrusion detection system (IDS) designed to address the increasing cyber ...

The Particle Swarm Optimization (PSO) algorithm is widely recognized for its simplicity and efficiency, but it suffers from issues such as local optima trapping and degraded performance in ...

Abstract: Particle swarm optimization (PSO) is a type of swarm intelligence algorithm that is frequently used to resolve specific global optimization problems due to its rapid convergence and ease of ...

Morningstar Quantitative Ratings for Stocks are generated using an algorithm that compares companies that are not under analyst coverage to peer companies that do receive analyst-driven ratings.

This project integrates Convolutional Neural Networks (CNN) for tumor classification and a hybrid Particle Swarm Optimization-Whale Optimization Algorithm (PSO-WOA) for precise image segmentation. The ...

Various advanced optimization methods, including genetic algorithm, particle swarm optimization, artificial bee colony optimization, and teaching-learning-based optimization, are used to determine the ...

However, the integration of optimization algorithms and computer software has significantly reduced the research and development cycle. The internal structure of traditional straight-beam-rib wings is ...

This four-volume handbook covers important concepts and tools used in the fields of financial econometrics, mathematics, statistics, and machine learning. Econometric methods have been applied in ...

In order to reduce the impact of imbalance samples on load identification, the SVM SMOTE algorithm is used to balance the ... Load Identification of Weighted Random Forest Based on Particle Swarm ...

[JMLR (CCF-A)] PyPop7: A Pure-Python Library for POPulation-based Black-Box Optimization (BBO), especially *Large-Scale* variants (including evolutionary algorithms, swarm-based randomized optimizers, ...