Optimized feature selection and advanced machine learning for stroke risk prediction in revascularized coronary artery disease patients by Yong Si, Armin Abdollahi, Negin Ashrafi, Greg Placencia, Elham Pishgar, Kamiar Alaei, Maryam Pishgar

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Learning‐based tracking control of AUV: Mixed policy improvement and game‐based disturbance rejection by Jun Ye, Hongbo Gao, Manjiang Hu, Yougang Bian, Qingjia Cui, Xiaohui Qin, Rongjun Ding

“…By combining prior dynamic knowledge and actual sampled data, the proposed approach effectively mitigates the defect caused by the inaccurate dynamic model and significantly improves the training speed of the ADP algorithm. …”
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Optimized multi-unit coordinated scheduling based on improved IGDT: Low-carbon scheduling research for the electric-heat-oxygen integrated energy system by Zhe Yin, Zhifan Zhang, Ruijin Zhu, Yifan Zhang, Jiyuan Wang, Wenxing Tang

“…This model combines the entropy weight method (EWM) and non-dominated sorting genetic algorithm II (NSGA-II), improving the objectivity and rationality of uncertainty weight settings in risk-averse strategy (RAS) and risk-seeking strategy (RSS). …”
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Towards Automated Cadastral Map Improvement: A Clustering Approach for Error Pattern Recognition by Konstantinos Vantas, Vasiliki Mirkopoulou

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Multi-objective optimization of current-assisted splitting spinning of small module tooth-shaped part based on the combination of BP neural network and NSGA-II algorithm by Zhou Haoyang, Xia Qinxiang, Xiao Gangfeng, Chen Can

“…The results show that the material at the tooth tip along the radial direction is in the state of tensile stress along radial and compressive stresses along tangential and axial directions, which promotes the radial flowing of the material and is beneficial the tooth filling of SMTSPs; the tooth saturation increases obviously under pulse current comparing without pulse current; the BPNN combined with the NSGA-II algorithm can reliably optimize the process parameters of the CASS, improving the forming quality of SMTSPs; experiments verified the feasibility of the process and the accuracy of the predictive model based on the optimization results.…”
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A Virtual Power Plant-Integrated Proactive Voltage Regulation Framework for Urban Distribution Networks: Enhanced Termite Life Cycle Optimization Algorithm and Dynamic Coordination by Yonglin Li, Zhao Liu, Changtao Kan, Rongfei Qiao, Yue Yu, Changgang Li

“…While virtual power plants (VPPs) and network reconfiguration mitigate operational risks, extant methods inadequately model load flexibility and suffer from algorithmic stagnation in non-convex optimization. …”
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A Hybrid CNN-LSTM Model With Attention Mechanism for Improved Intrusion Detection in Wireless IoT Sensor Networks by Pendukeni Phalaagae, Adamu Murtala Zungeru, Abid Yahya, Boyce Sigweni, Selvaraj Rajalakshmi

“…Additionally, the improved dynamic PSO algorithm optimizes feature selection in real time, enhancing classification accuracy and adaptability to evolving IoT network threats. …”
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Mod Tanh‐Activated Physical Neural Network MPPT Control Algorithm for Varying Irradiance Conditions by Khuong Nguyen‐Vinh, Surender Rangaraju, Michal Jasinski

“…ABSTRACT The increasing adoption of solar photovoltaic systems necessitates efficient maximum power point tracking (MPPT) algorithms to ensure optimal performance. This study proposes a Mod tanh‐activated physical neural network (MAPNN)‐based MPPT control algorithm, which addresses inefficiencies in existing models caused by spectral mismatch and improper converter control. …”
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Optimization analysis of air cooled open cathode proton exchange membrane fuel cell flow channel structure by Zhijun Deng, Qingwei Wang, Xun Fang, Yaru Han, Kunxiang Liu, Chen Zhao

“…In addition, in order to further improve the power density of the fuel cell, two agent models, support vector regression and Gaussian process regression, are constructed and trained, and a genetic algorithm is used to find the parameter optimization for the bending angle, width and height of the cathode channel. …”
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Optimizing prediction of metastasis among colorectal cancer patients using machine learning technology by Raoof Nopour

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A cross-chain model for warehouse receipts in port supply chain based on notary mechanism and ShangMi cryptographic algorithms by Yangbo Chen, Wei Ou, Mengxue Pang, Jianqiang Ma, Qiuling Yue, Wenbao Han

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Sustainable phytoprotection: a smart monitoring and recommendation framework using Puma Optimization for potato pathogen detection by Amal H. Alharbi, Faris H. Rizk, Khaled Sh. Gaber, Marwa M. Eid, Marwa M. Eid, El-Sayed M. El-kenawy, El-Sayed M. El-kenawy, Pushan Kumar Dutta, Doaa Sami Khafaga

“…This study proposes a novel hybrid framework for potato disease classification that integrates copula-based dependency modeling with a Restricted Boltzmann Machine (RBM), further enhanced through hyperparameter tuning using the biologically inspired Puma Optimization (PO) algorithm. …”
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Evaluating energy efficiency in Turkish electric distribution using network DEA and GA models by Serpil Aydin, Talat Şenel

“…This shows that Sakarya EDC operates optimally and is a benchmark for other companies in the sector. …”
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Prediction of dam deformation using adaptive noise CEEMDAN and BiGRU time series modeling by WANG Zixuan, OU Bin, CHEN Dehui, YANG Shiyong, ZHAO Dingzhu, FU Shuyan

“…【Method】The model uses sample entropy reconstruction and the K-means clustering algorithm to optimize the adaptive noise complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) process, generating multiple intrinsic mode functions (IMF). …”
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A Two-Stage Optimization Method for Multi-Runway Departure Sequencing Based on Continuous-Time Markov Chain by Guan Lian, Yingzi Wu, Weizhen Luo, Wenyong Li, Yaping Zhang, Xiaoyue Zhang

“…Then, continuous-time Markov chains (CTMC) were employed to track aircraft state transitions in the taxiway queue, and a nested whale optimization algorithm was proposed to optimize both the pushback sequence and runway resource allocation. …”
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An improved permeability estimation model using integrated approach of hybrid machine learning technique and Shapley additive explanation by Christopher N. Mkono, Chuanbo Shen, Alvin K. Mulashani, Patrice Nyangi

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Histopathological image based breast cancer diagnosis using deep learning and bio inspired optimization by Venkata Nagaraju Thatha, M. Ganesh Karthik, Venu Gopal Gaddam, D. Pramodh Krishna, S. Venkataramana, Kranthi Kumar Lella, Udayaraju Pamula

“…This study introduces an advanced deep learning framework for histopathological image classification, integrating AlexNet and Gated Recurrent Unit (GRU) networks, optimized using the Hippopotamus Optimization Algorithm (HOA). …”
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Development and validation of a risk prediction model for kinesiophobia in postoperative lung cancer patients: an interpretable machine learning algorithm study by Chuang Li, Youbei Lin, Xuyang Xiao, Xinru Guo, Jinrui Fei, Yanyan Lu, Junling Zhao, Lan Zhang

“…Subsequently, six machine learning (ML) models were developed and compared to identify the optimal model. …”
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Multi-Target Firefighting Task Planning Strategy for Multiple UAVs Under Dynamic Forest Fire Environment by Pei Zhu, Shize Jiang, Jiangao Zhang, Ziheng Xu, Zhi Sun, Quan Shao

“…In this process, the study considers only the use of fire-extinguishing balls as the fire suppressant for the UAVs. The improved multi-population grey wolf optimization (MP–GWO) algorithm and non-Dominated sorting genetic algorithm II (NSGA-II) were designed to solve the path planning and task allocation models, respectively. …”
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Optimizing oil production forecasts in Iranian oil fields: a comprehensive analysis using ensemble learning techniques by Mohammad Ghodsi, Pouya Vaziri, Mahdi Kanaani, Behnam Sedaee

“…The inclusion of advanced optimization strategies, such as Genetic Algorithm (GA), Teaching-Learning-Based Optimization (TLBO), and Particle Swarm Optimization (PSO), ensures that each base model reaches its highest potential performance. …”
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