GEN - Genetic Engineering and Biotechnology News

Unifying Bioprocessing Data to Transform Biomanufacturing with AI

Bioprocessing data is often scattered across electronic laboratory notebooks (ELNs), laboratory information management systems (LIMS), instruments, spreadsheets, and legacy systems that don’t talk to ...
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 ...
Brown University

Faster topology optimization: An emerging industrial design technique gets a speed boost

A new algorithm helps topology optimizers skip unnecessary iterations, making optimization and design faster, more stable and more useful. PROVIDENCE, R.I. [Brown University] — With the rise of 3D ...
Frontiers

Control parameter identification method for virtual synchronous generator considering electric vehicles based on dynamic particle swarm optimization

1 Research Department of State Grid Zhejiang Electric Power Research Institute, Hangzhou, China 2 Research Department of State Grad Aksu Electric Power Supply Company, Aksu, China To address the ...
Scientific Research Publishing

Optimization Design of Curved Wing Box Based on BP-Multi-Objective Genetic Algorithm ()

College of Aircraft Engineering, Nanchang Hangkong University, Nanchang, China. Since time immemorial, achieving high performance, structural lightweight, and cost-effectiveness of aircraft has been a ...
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 ...
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 ...