The educational competition optimizer

J Lian, T Zhu, L Ma, X Wu, AA Heidari… - … Journal of Systems …, 2024 - Taylor & Francis
In recent research, metaheuristic strategies stand out as powerful tools for complex
optimization, capturing widespread attention. This study proposes the Educational …

[HTML][HTML] An advanced kernel search optimization for dynamic economic emission dispatch with new energy sources

R Dong, L Sun, Z Cai, AA Heidari, L Liu… - International Journal of …, 2024 - Elsevier
Integrating renewable energy sources, such as wind and photovoltaic power generation,
into the power grid is crucial for sustainable power system development and mitigating …

B-mode ultrasound-based CAD by learning using privileged information with dual-level missing modality completion

X Wang, X Ren, G Jin, S Ying, J Wang, J Li… - Computers in Biology and …, 2024 - Elsevier
Learning using privileged information (LUPI) has shown its effectiveness to improve the B-
mode ultrasound (BUS) based computer-aided diagnosis (CAD) by transferring knowledge …

Advancing forensic-based investigation incorporating slime mould search for gene selection of high-dimensional genetic data

F Qiu, AA Heidari, Y Chen, H Chen, G Liang - Scientific Reports, 2024 - nature.com
Modern medicine has produced large genetic datasets of high dimensions through
advanced gene sequencing technology, and processing these data is of great significance …

An improved multi-strategy Golden Jackal algorithm for real world engineering problems

M Elhoseny, M Abdel-salam, IM El-Hasnony - Knowledge-Based Systems, 2024 - Elsevier
Abstract The Golden Jackal Optimization (GJO) algorithm is a novel, nature-inspired
optimization technique that has gained recognition as a highly promising metaheuristic due …

Predictive modeling for early detection of biliary atresia in infants with cholestasis: Insights from a machine learning study

X Chen, D Zhao, H Ji, Y Chen, Y Li, Z Zuo - Computers in Biology and …, 2024 - Elsevier
Cholestasis, characterized by the obstruction of bile flow, poses a significant concern in
neonates and infants. It can result in jaundice, inadequate weight gain, and liver dysfunction …

Predictive modeling of deep vein thrombosis risk in hospitalized patients: A Q-learning enhanced feature selection model

R Li, S Chen, J Xia, H Zhou, Q Shen, Q Li… - Computers in Biology and …, 2024 - Elsevier
Deep vein thrombosis (DVT) represents a critical health concern due to its potential to lead
to pulmonary embolism, a life-threatening complication. Early identification and prediction of …

Enhanced Runge-Kutta-driven feature selection model for early detection of gastroesophageal reflux disease

J Mao, Z Zhu, M Xia, M Zhou, L Wang, J Xia… - Computers in Biology …, 2024 - Elsevier
Gastroesophageal reflux disease (GERD) profoundly compromises the quality of life, with
prolonged untreated cases posing a heightened risk of severe complications such as …

An efficient weighted slime mould algorithm for engineering optimization

Q Sun, C Wang, Y Chen, AA Heidari, H Chen… - Journal of Big Data, 2024 - Springer
In engineering applications, optimal parameter design is crucial. While Slime Mould
Algorithm (SMA) excels in parameter discovery under constrained conditions, it faces …

Enhanced PSO feature selection with Runge-Kutta and Gaussian sampling for precise gastric cancer recurrence prediction

J Zhao, JC Li, J Yao, G Lin, C Chen, H Ye, X He… - Computers in Biology …, 2024 - Elsevier
Gastric cancer (GC), characterized by its inconspicuous initial symptoms and rapid
invasiveness, presents a formidable challenge. Overlooking postoperative intervention …