Results 61 to 70 of about 12,918 (212)

Frequency‐Domain Subspace Identification for Noninvasive Transformer Winding Parameter Estimation and Fault Diagnostics

International Journal of Circuit Theory and Applications, Volume 54, Issue 2, Page 658-677, February 2026.
Noninvasive frequency‐domain method estimates transformer winding parameters from terminal measurements, eliminating the need for design data. ABSTRACT A novel frequency‐domain subspace identification method enables precise estimation of transformer winding ladder network parameters directly from terminal measurements.
K. Lakshmi Prasanna, Manoj Samal, Mithun Mondal, Palash Mishra   +3 more
wiley   +1 more source

Research on Three‐Dimensional Autonomous Obstacle Avoidance Path Planning Methods for UAVs

Transactions on Emerging Telecommunications Technologies, Volume 37, Issue 2, February 2026.
This study presents a three‐dimensional autonomous obstacle‐avoidance path planning method for unmanned aerial vehicles (UAVs) based on a deep reinforcement learning (DRL)‐enhanced Mayfly Algorithm. The traditional Mayfly Algorithm suffers from issues such as random initial population generation and slow convergence.
Chong Wu, Hao Cheng, Hua Wang
wiley   +1 more source

Planning capacity for 5G and beyond wireless networks by discrete fireworks algorithm with ensemble of local search methods

EURASIP Journal on Wireless Communications and Networking, 2020
In densely populated urban centers, planning optimized capacity for the fifth-generation (5G) and beyond wireless networks is a challenging task. In this paper, we propose a mathematical framework for the planning capacity of a 5G and beyond wireless ...
Hafiz Munsub Ali, Jiangchuan Liu, Waleed Ejaz   +2 more
doaj   +1 more source

Sampling rate selection for multi‐loop cascade control systems in an optimal manner

IET Control Theory & Applications, 2023
This article proposes an optimization‐based approach to selecting the sampling periods for classes of linear time‐invariant (LTI) regulators in a cascaded multi‐rate control structure, to account for practical implementation on numeric systems.
Mircea Şuşcă, Vlad Mihaly, Petru Dobra   +2 more
doaj   +1 more source

Fractional‐order controller tuning via minimization of integral of time‐weighted absolute error without multiple closed‐loop tests

Asian Journal of Control, Volume 28, Issue 1, Page 20-33, January 2026.
Abstract This study presents a non‐iterative tuning technique for a linear fractional‐order (FO) controller, based on the integral of the time‐weighted absolute error (ITAE) criterion. Minimizing the ITAE is a traditional approach for tuning FO controllers. This technique reduces the over/undershoot and suppresses the steady‐state error. In contrast to
Ansei Yonezawa, Heisei Yonezawa, Shuichi Yahagi, Itsuro Kajiwara, Shinya Kijimoto   +4 more
wiley   +1 more source

FIELD TRAVERSAL PATH PLANNING FOR AGRICULTURAL ROBOTS IN HILLY AREAS BASED ON DISCRETE ARTIFICIAL BEE COLONY ALGORITHM

INMATEH Agricultural Engineering
In this study, the discrete artificial bee colony (DABC) algorithm was proposed to plan the path of agricultural robots traversing multiple fields in hilly areas.
Xiaodong Lou, Zheng Li
semanticscholar   +1 more source

Multiple Input Delays Estimation Using an Artificial Bee Colony Algorithm

Abstract and Applied Analysis, 2013
This paper focuses on the time delay estimation of the system described in the form of discrete-time state equation with multiple input delays. To estimate the input delays, a new evolutionary computation called the artificial bee colony (ABC) algorithm ...
Wei-Der Chang
doaj   +1 more source

Metaheuristic‐Driven Feature Selection for Blockchain Fraud Detection: A Comparative Study on Machine and Deep Learning Models

IET Blockchain, Volume 6, Issue 1, January/December 2026.
We present a metaheuristic feature‐selection framework—Artificial Bee Colony, Aquila Optimiser and Fox Optimiser—for blockchain fraud detection, benchmarked across machine‐learning and deep‐learning models on large‐scale transaction data. The study evaluates predictive performance (PR‐AUC/ROC‐AUC), stability across seeds and parsimony under cost ...
Hibatou allah Boulsane, Karim Afdel
wiley   +1 more source

An Efficient Optimization Algorithm for Resource-Constrained Steelmaking Scheduling Problems

IEEE Access, 2018
In this paper, we address the steelmaking scheduling problems with multiple constrained resources. The objective is to minimize the maximum completion time. We consider the continuous casting constraint and resource constraints simultaneously.
Junqing Li, Peiyong Duan, Hongyan Sang, Song Wang, Zhengmin Liu, Peng Duan   +5 more
doaj   +1 more source

Reinforcement Learning‐Assisted Meta‐Heuristics for Scheduling Job Shops With Material Handling Robots

IET Collaborative Intelligent Manufacturing, Volume 8, Issue 1, January/December 2026.
This study addresses an integrated job shop scheduling problem with material handling robots, aiming to minimise the maximum completion time. Three meta‐heuristics, seven local search strategies and two reinforcement learning algorithms are proposed to solve the problems.
Qi Jia, Kaizhou Gao, Naiqi Wu, Ponnuthurai Nagaratnam Suganthan   +3 more
wiley   +1 more source