Results 31 to 40 of about 261 (126)

Quasi Opposition–Based Learning With Artificial Rabbit Optimization for Feature Selection of Breast Cancer

Engineering Reports, Volume 8, Issue 3, March 2026.
Workflow of proposed QOBL‐ARO with GS‐SVM method for BC using mammogram images. ABSTRACT Mammogram images are the most appropriate modality for breast cancer (BC) diagnosis which supports early diagnosis in women. However, the handcrafted features are insufficient for effective BC classification, which negatively impacts the model's accuracy and leads ...
Bassamma Patil, P. Vishwanath, S. M. Anowarul Haque   +2 more
wiley   +1 more source

Optimizing Fast Learning Network Using Fuzzy Adaptive Metaheuristic Algorithms for Robust Intrusion Detection

Applied Computational Intelligence and Soft Computing, Volume 2026, Issue 1, 2026.
In today’s digital era, the prevalence of cyberattacks requires robust security measures to keep sensitive and confidential information and infrastructure safe and secure. The intrusion detection system (IDS) plays the most vital role in this aspect by serving as a first‐line defense against these malicious activities and potential breaches. This paper
Fakhrud Din, Fida Ur Rahman, Dost Muhammad, Mohammad Hasan Ali, Mushtaq Ali, Malika Bendechache, Cheng-Jian Lin   +6 more
wiley   +1 more source

Early fault diagnosis of transformer winding based on ReliefF-mRMR leakage magnetic field feature optimization and improved LSSVM

Diance yu yibiao
Aiming at the problem of complex transformer structure and small amount of early winding fault sample data, in order to improve the accuracy of transformer winding fault type diagnosis, this paper proposes an early fault diagnosis model of transformer ...
LIU Jianfeng, DONG Qianwen, TIAN Shuxin, LIU Mengqi, MEI Zhicong, ZHOU Hai   +5 more
doaj   +1 more source

Accurate and Efficient Behavioral Modeling of GaN HEMTs Using An Optimized Light Gradient Boosting Machine

Advanced Theory and Simulations, Volume 8, Issue 9, September 2025.
Machine Learning (ML) and optimization have permeated almost every aspect of engineering applications. Recent years have seen great traction toward ML‐based GaN HEMT modelling. However, ML‐based GaN HEMT models are mostly developed using variants of Artificial Neural Network (ANN).
Saddam Husain, Mohammad Hashmi, Fadhel M. Ghannouchi   +2 more
wiley   +1 more source

Optimization on Electric Construction Machinery Considering Time‐of‐Use Electricity Price Based on the Improved Crested Porcupine Optimizer Algorithm

Energy Science &Engineering, Volume 13, Issue 6, Page 2973-2986, June 2025.
Flowchart of the methodology used for this study ABSTRACT Optimization scheduling plays a pivotal role in construction projects, significantly influencing both the overall project schedule and its efficiency. This study focuses on optimizing the scheduling of electric highway engineering projects within roadbed construction.
Dawei Wang, Bo Gao, Lei Zhang
wiley   +1 more source

Hybrid Neural Network Approach for Tea Leaf Disease Detection Using Pelican and Mayfly Optimization Algorithms

Jurnal Riset Informatika
This study addresses the problem of plant diseases and the difficulty of detecting them, and it presents a unique technique for the automatic detection of tea leaf diseases by combining neural networks and optimization techniques.
Saja Bilal Hafedh Al-Karawi, Hakan Koyuncu   +1 more
doaj   +1 more source

Comprehensive Optimization of PID Controller Parameters for DC Motor Speed Management Using a Modified Jellyfish Search Algorithm

Optimal Control Applications and Methods, Volume 46, Issue 1, Page 320-342, January/February 2025.
Conceptual design of PID controller optimization for DC motors using nature‐inspired algorithms. ABSTRACT The proportional integral derivative (PID) controller plays a crucial role in various industrial applications. However, conventional methods often fail to provide optimal parameter values.
Aykut Fatih Güven, Onur Özdal Mengi, Mohamed A. Elseify, Salah Kamel   +3 more
wiley   +1 more source

An Efficient Cluster Based Routing in Wireless Sensor Networks Using Multiobjective‐Perturbed Learning and Mutation Strategy Based Artificial Rabbits Optimisation

IET Communications, Volume 19, Issue 1, January/December 2025.
An important objective of this research is to enhance the network lifecycle and data delivery over the WSN. This research proposes the M‐PMARO for choosing the optimum CH that helps to balance the energy expenditure and achieves the reliable communication over the network.
Babiyola Arulanandam, Khalid Nazim Abdul Sattar, Rocío Pérez de Prado, Bidare Divakarachar Parameshchari   +3 more
wiley   +1 more source

Reservoir Porosity Prediction Based on BiLSTM-AM Optimized by Improved Pelican Optimization Algorithm

Energies
To accurately predict reservoir porosity, a method based on bi-directional long short-term memory with attention mechanism (BiLSTM-AM) optimized by the improved pelican optimization algorithm (IPOA) is proposed.
Lei Qiao, Nansi He, You Cui, Jichang Zhu, Kun Xiao   +4 more
doaj   +1 more source

RETRACTED: Segment Routing for WSN Using Hybrid Optimisation With Energy Efficient Game Theory Based Clustering Technique

IET Communications, Volume 19, Issue 1, January/December 2025.
1. This research focuses on wireless sensor networks (WSNs) and proposes a three‐phase approach to achieve energy‐efficient routing. 2. The approach consists of node deployment using Voronoi diagrams, clustering, cluster Head (CH) selection using energy‐efficient game theory, and a routing strategy based on improved pelican optimisation (ImPe) segment ...
S. Sangeetha, T. Aruldoss Albert Victoire, C. Kumar, Sourav Barua   +3 more
wiley   +1 more source