Results 71 to 80 of about 11,354 (208)

Modeling Solar PV Efficiency: Machine Learning‐Enhanced Algorithms for Diode Model Parameter Extraction

Energy Science &Engineering, Volume 14, Issue 1, Page 475-488, January 2026.
ABSTRACT Solar photovoltaic (PV) systems can be significantly enhanced through the use of accurate solar cell models. Unfortunately, the absence of precise parameters from manufacturers limits the accuracy of these models. Given the impossibility of reliable modeling without such parameters, this paper introduces a multi‐objective optimization ...
Manish Kumar Singla, Muhammed Ali S.A., Mohammad Aljaidi, Jyoti Gupta, Ramesh Kumar, EI‐Sayed M. EI‐Kenawy, Amal H. Alharbi   +6 more
wiley   +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

A Faster Convergence Artificial Bee Colony Algorithm in Sensor Deployment for Wireless Sensor Networks

International Journal of Distributed Sensor Networks, 2013
In wireless sensor networks (WSN), sensor deployment is one of the main topics for enhancing the sensor's coverage rate. In this paper, by modifying updating equation of onlooker bee and scout bee of original artificial bee colony (ABC) algorithm, a ...
Xiangyu Yu, Jiaxin Zhang, Jiaru Fan, Tao Zhang   +3 more
doaj   +1 more source

A Comparison of Nature Inspired Algorithms for Multi-threshold Image Segmentation

, 2013
In the field of image analysis, segmentation is one of the most important preprocessing steps. One way to achieve segmentation is by mean of threshold selection, where each pixel that belongs to a determined class islabeled according to the selected ...
Cuevas, Erik, Osuna-Enciso, Valentín, Sossa, Humberto   +2 more
core   +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

Intelligent decision-making for mine airflow on demand based on the improved artificial bee colony algorithm

Gong-kuang zidonghua
To address the issue of slow convergence speed in solving the unconstrained optimization mathematical model of mine airflow control using existing metaheuristic algorithms, an intelligent decision-making method for mine airflow on demand based on an ...
ZHANG Lang, LEI Shuang, LI Wei, LIU Yanqing   +3 more
doaj   +1 more source

Dynamic Stability Analysis of Multi‐Infeed Wind Power System With Composite Dynamic Short Circuit Ratio

IET Generation, Transmission &Distribution, Volume 20, Issue 1, January/December 2026.
A GEDMM is proposed to represent the MIWPS as multiple VSISs and model each of them as the VTDS2M whose unknown parameters are identified with the proposed hybrid optimized square root cubature Kalman filter (HOSRCKF). To solve the issues that the physical meanings of existing short circuit ratios (SCRs) are unclear and the critical values of existing ...
Mengxian Sun, Dongdong Li, Weilun Zhong, Dajun Yu   +3 more
wiley   +1 more source

Adaptive Exploration Artificial Bee Colony for Mathematical Optimization

AI
The artificial bee colony (ABC) algorithm is a famous swarm intelligence method utilized across various disciplines due to its robustness. However, it exhibits limitations in exploration mechanisms, particularly in high-dimensional or complex landscapes.
Shaymaa Alsamia, Edina Koch, Hazim Albedran, Richard Ray   +3 more
doaj   +1 more source

Metaheuristic‐Based Load Frequency Control of Multi‐Source Renewable Systems With SMES and AC‐DC Parallel Tie‐Lines

IET Generation, Transmission &Distribution, Volume 20, Issue 1, January/December 2026.
This study proposes a hybrid evolutionary exploration algorithm (HEEA) that integrates genetic algorithm and grey wolf optimiser to co‐tune PID controller gains and SMES parameters in a two‐area AC‐DC interconnected renewable system. The proposed method achieves faster convergence, lower ITAE and improved stability compared to existing metaheuristics ...
Md. Shahan Sarker
wiley   +1 more source

Joint Optimisation of the Gate and Taxi Route During Peak Hours: A Fusion Algorithm of Adaptive Genetic and Artificial Bee Colony

IET Intelligent Transport Systems, Volume 20, Issue 1, January/December 2026.
This paper develops a novel joint optimisation model using column generation (CG) for airport parking gate and taxi route assignment, especially during peak hours. It proposes a parallel fusion algorithm combining artificial bee colony and adaptive genetic algorithm to solve the model efficiently.
Fujun Wang, Dongqing Liu, Xiangyi Li, Wei Zhang, Hongfei Liu, Jun Bi   +5 more
wiley   +1 more source