The New York Times

Bessent Plans to Attend Tariff Arguments at the Supreme Court

Treasury Secretary Scott Bessent dismissed the idea that his presence could be seen as an attempt to intimidate the court on a case that President Trump considers vital to his economic policy. By ...
Frontiers

Intelligent optimization of slope step parameters in open pit mines containing weak interbedded layers based on machine learning and multi-objective optimization methods

1 Faculty of Land Resources Engineering, Kunming University of Science and Technology Kunming, Kunming, China 2 Pangang Group Mining Company Limited Panzhihua, Panzhihua, Sichuan, China The stability ...
IEEE

Two-Stage Genetic Algorithm Offline Parameter Optimization of Adaptive Extended Kalman Filter for Robust Battery State-Of-Charge Estimation

Abstract: Accurately estimating battery state of charge (SOC) in electric vehicle applications (EVs) is crucial to ensure a safe and reliable vehicle operation. However, robust SOC estimation under ...
GitHub

Multi-Factorial Evolutionary Algorithm With Online Transfer Parameter Estimation (MFEA-II) in Python

This repository implement MFEA-II MFEA-II Official Matlab Version. Tested on MTSOO benchmark. This repo could be used as a template or starter code for conducting multitasking optimization on other ...
Frontiers

Random forest grid fault prediction based on genetic algorithm optimization

The operation of the power grid is closely related to meteorological disasters. Changes in meteorological conditions may have an impact on the operation and stability of the power system, leading to ...
C&EN

ProcessOptimizer, an Open-Source Python Package for Easy Optimization of Real-World Processes Using Bayesian Optimization: Showcase of Features and Example of Use

ProcessOptimizer is a Python package designed to provide easy access to advanced machine learning techniques, specifically Bayesian optimization using, e.g., Gaussian processes. Aimed at ...
SciELO

Proposition for Path Loss Prediction Models with the Inclusion of Altitude Parameter and Optimization Through Evolutionary Algorithms

In this paper, it is presented a general optimization methodology for improving empirical models predicting Okumura-Hata, Cost-231, ECC-33, and Egli using Genetic and Differential Evolution Algorithms ...
IEEE

Eliminating Network Depth: Genetic Algorithm for Parameter Optimization in CNNs

Abstract: Recent advances in Convolutional Neural Networks (CNNs) have significantly enhanced image classification performance. However, CNNs often require large numbers of parameters, leading to ...