Results 121 to 130 of about 29,061 (311)

Interactive Heuristic D* Path Planning Solution Based on PSO for Two-Link Robotic Arm in Dynamic Environment

, 2019
Firas A. Raheem, Umniah I. Hameed
openalex   +2 more sources

Application of Meta-Heuristic Algorithm for Finding the Best Solution for the Optimal Power Flow Problem

, 2021
Thanh Long Duong, Ngoc Thuy Nguyen, Thuan Nguyen, R Palomino, V Quintana, O Alsac, B Scott, D Sun, B Ashley, B Brewer, A Hughes, W Tinney, R Burchett, H Happ, D Vierath, X Yan, V Quintana, M Abido, Y Jason, P Kit, A Fergany, H Hasanien, A Bhattacharya, P Chattopadhyay, M Nayak, C Nayak, P Rout, H Pulluri, R Naresh, V Sharma, M Siva1, R Balamurugan, L Lakshminarasimman, S Duman, U Guvenc, Y Sonmez, N, Yorukeren, M Adaryani, A Karami, A Mohamed, Y Mohamed, A Gaafary, A Hemeida, W Warid, H Hizam, N Mariun, N Wahab, C Thitithamrongchai, B Arporn, S Sayah, K Zehar, M Kumari, S Maheswarapu, A Kumar, L Premalatha, G Chen, Z Lu, Z Zhang, M Abdo, S Kamel, M Ebeed, J Yu, F Jurado, T Niknam, M Narimani, M Jabbari, A Malekpour, A Murtadha, A Layth, M Ghasemi, S Ghavidel, M Ghanbarian, M Gharibzadeh, A Vahed, H Bouchekara, M Abido, A Chaib, A Attia, R Sehiemy, H Hasanien, P Le, T Duong, D Vo, T Le, S Nguyen, J Radosavljevi, D Klimenta, M Jevti, N Arsi, W Zhao, L Wang, Z Zhang, S Mouassa, F Jurado, T Bouktir, M Raja   +96 more
openalex   +1 more source

FastCat: Autonomous Discovery of Multielement Layered Double Hydroxide Alloy Catalysts for Alkaline Oxygen Evolution Reaction

Advanced Intelligent Discovery, EarlyView.
A machine learning‐guided self‐driving laboratory screened over 500 nickel‐based layered double‐hydroxide catalysts for alkaline oxygen evolution. Out of the eight metals, the robot uncovered a quaternary Ni–Fe–Cr–Co catalysts requiring only 231 mV overpotential to reach 20 mA cm−2.
Nis Fisker‐Bødker, Enzo Raffaele Moretti, Jin Hyun Chang, Tejs Vegge   +3 more
wiley   +1 more source

Advances in Thermal Modeling and Simulation of Lithium‐Ion Batteries with Machine Learning Approaches

Advanced Intelligent Discovery, EarlyView.
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin, Kang Fu, Junjie Ding, Kai Sun, Peng Tan   +4 more
wiley   +1 more source

Solutions and Solution Costs for "Exact and Meta-Heuristic Approaches for Unrelated Parallel Machine Scheduling"

, 2020
M. Moser, Nysret Musliu, Andrea Schaerf, Felix Winter   +3 more
openalex   +2 more sources

A heuristic approach to the prediction of a periodic solution for a damping nonlinear oscillator with the non-perturbative technique [PDF]

, 2023
Yusry O. El‐Dib, Nasser S. Elgazery, Haifa A. Alyousef   +2 more
openalex   +1 more source

FIRE‐GNN: Force‐Informed, Relaxed Equivariance Graph Neural Network for Rapid and Accurate Prediction of Surface Properties

Advanced Intelligent Discovery, EarlyView.
This study introduces FIRE‐GNN, a force‐informed, relaxed equivariant graph neural network for predicting surface work functions and cleavage energies from slab structures. By incorporating surface‐normal symmetry breaking and machine learning interatomic potential‐derived force information, the approach achieves state‐of‐the‐art accuracy and enables ...
Circe Hsu, Claire Schlesinger, Karan Mudaliar, Jordan Leung, Robin Walters, Peter Schindler   +5 more
wiley   +1 more source

Solution approach using heuristic and artificial neural networks methods in assembly line balancing problems: A case study in the lighting industry [PDF]

Yelda Karatepe Mumcu
openalex   +1 more source

An optimal power flow solution to deregulated electricity power market using meta-heuristic algorithms considering load congestion environment [PDF]

, 2022
Vijaya Bhaskar K, S. Ramesh, Elena Verdú, K. Karunanithi, S P Raja   +4 more
openalex   +1 more source

Real‐Time Sampling‐Based Model Predictive Control Based on Reverse Kullback–Leibler Divergence and Its Adaptive Acceleration

Advanced Intelligent Systems, EarlyView.
This study presents a new sampling‐based model predictive control minimizing reverse Kullback‐Leibler divergence to quickly find a local optimum. In addition, a modified Nesterov's acceleration method is introduced for faster convergence. The method is effective for real‐time simulations and real‐world operability improvement on a force‐driven mobile ...
Taisuke Kobayashi, Kota Fukumoto
wiley   +1 more source