No-load and on-load performance analysis of 10-stator-slots five phase flux switching machines with non-overlapped winding configurations by Muhammad Yousuf, Faisal Khan, Ahmed Tameemi, Wasiq Ullah

“…An evolutionary optimization process based on the genetic algorithm (GA) integrated with the JMAG software is executed to optimize the machine models, resulting in significant improvements in the analyzed WFFS machine models. …”
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Precision Medicine in Lung Cancer Screening: A Paradigm Shift in Early Detection—Precision Screening for Lung Cancer by Hsin-Hung Chen, Yun-Ju Wu, Fu-Zong Wu

“…However, implementation must also address challenges related to health equity, algorithmic bias, and system integration. As precision medicine continues to evolve, it holds the promise of optimizing early detection, minimizing harm, and extending the benefits of lung cancer screening to broader and more diverse populations. …”
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UAM Vertiport Network Design Considering Connectivity by Wentao Zhang, Taesung Hwang

“…To efficiently solve the problem and improve solution quality, a hybrid genetic algorithm is developed by incorporating a Minimum Spanning Tree (MST)-based connectivity enforcement mechanism, a fundamental concept in graph theory that connects all nodes in a given network with minimal total link cost, enhanced by a greedy initialization strategy. …”
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Enhanced Transmission Expansion Planning With a High Confidence Strategy Considering Fluctuations in Solar PV Generation and Electricity Demand by Siripat Somchit, Niphon Kaewdornhan, Rongrit Chatthaworn

“…To address this issue, this work proposes an enhanced TEP-based 24-hour situation optimized by an improved Binary Differential Evolution (BDE) algorithm assisted by the logistic map for adjusting the mutation factor and crossover rate. …”
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Development of an interpretable machine learning model based on CT radiomics for the prediction of post acute pancreatitis diabetes mellitus by Xiyao Wan, Yuan Wang, Ziyi Liu, Ziyan Liu, Shuting Zhong, Xiaohua Huang

“…Patients were classified into PPDM-A (n = 109) and non-PPDM-A groups (n = 162), and split into training (n = 189) and testing (n = 82) cohorts at a 7:3 ratio. 1223 radiomic features were extracted from CT images in the plain, arterial and venous phases, respectively. The radiomics model was developed based on the optimal features retained after dimensionality reduction, utilizing the extreme gradient boosting (XGBoost) algorithm. …”
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Enhancing Daylight and Energy Efficiency in Hot Climate Regions with a Perforated Shading System Using a Hybrid Approach Considering Different Case Studies by Basma Gaber, Changhong Zhan, Xueying Han, Mohamed Omar, Guanghao Li

“…A hybrid approach integrating parametric modeling, machine learning, multi-criteria decision-making (MCDM), and genetic algorithm (GA) is used to optimize the design incorporating architects’ preferences. …”
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Advanced biomedical imaging for identifying blood cell type: Integrating segmentation, feature extraction, and GraphSAGE model by Nur Mohammad Fahad, Mohaimenul Azam Khan Raiaan, Arefin Ittesafun Abian, Ripon Kumar Debnath, Sidratul Montaha, Mirjam Jonkman, Sami Azam

“…An improved GraphSAGE model is constructed to classify blood cells. …”
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Machine learning-based identification of histone deacetylase-associated prognostic factors and prognostic modeling for low-grade glioma by Keshan Wen, Weijie Zhu, Ziyi Luo, Wei Wang

“…This model may guide personalized treatment strategies and improve prognostic accuracy, warranting further validation in clinical settings.…”
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An Innovative Online Adaptive High-Efficiency Controller for Micro Gas Turbine: Design and Simulation Validation by Rui Yang, Yongbao Liu, Xing He, Zhimeng Liu

“…When the DL_ELM model detects a gas turbine’s performance change, a particle swarm optimization (PSO) algorithm is employed to iteratively calculate the DFF_DL_OSELM model, determining the optimal speed control scheme to ensure the gas turbine operates at maximum efficiency. …”
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Neural network prediction model based on Levy flight and natural biomimetic technology for its application in cancer prediction. by Ruiyu Zhan

“…To tackle this issue, we present an innovative method that harmonizes the Grey Wolf Optimizer (GWO) with Levy flight to optimize the weights and biases of a Backpropagation (BP) neural network-a prominent machine learning model extensively employed in classification tasks. …”
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Smart IoT Energy Optimisation and Localisation Monitoring for E-Bike Sharing by Mawada Mohamed, Siti Fauziah Toha, Md Ataur Rahman, Moh. Khairudin

“…However, existing systems face challenges such as limited input parameters for modeling, leading to inefficiencies in energy optimization algorithms and power assist mechanisms. …”
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Wireless positioning methods for mitigating the influence of environmental and terminal diversity by Jietai WANG, Youlian GUAN, Xiaoniu YANG, Zhenxing LUO, Jianbiao YU

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Joint classification and regression with deep multi task learning model using conventional based patch extraction for brain disease diagnosis by Padmapriya K., Ezhumalai Periyathambi

“…Through cooperative learning of several tasks, the model might make greater use of shared information and improve overall performance. …”
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Prediction of Input–Output Characteristic Curves of Hydraulic Cylinders Based on Three-Layer BP Neural Network by Wei Cai, Yirui Zhang, Jianxin Zhang, Shunshun Guo, Rui Guo

“…In the process of model improvement, a nonlinear adaptive decreasing weight mechanism is introduced to improve the optimization accuracy of the algorithm, facilitating the search for optimal solutions. …”
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Predictive modeling and interpretative analysis of risks of instability in patients with Myasthenia Gravis requiring intensive care unit admission by Chao-Yang Kuo, Emily Chia-Yu Su, Hsu-Ling Yeh, Jiann-Horng Yeh, Hou-Chang Chiu, Chen-Chih Chung

“…This novel, personalized approach to risk stratification elucidates crucial risk factors and has the potential to enhance clinical decision-making, optimize resource allocation, and ultimately improve patient outcomes.…”
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The role of artificial intelligence in vascular care by Nehaar Nimmagadda, BS, Edouard Aboian, MD, Sharon Kiang, MD, Uwe Fischer, MD

“…The review also explores cost-effectiveness data, resource optimization, and challenges such as algorithmic bias and data privacy. …”
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Integrating Metaheuristics and Machine Learning for Enhanced Vehicle Routing: A Comparative Study of Hyperheuristic and VAE-Based Approaches by Kassem Danach, Louai Saker, Hassan Harb

“…In contrast, the VAE-based approach leverages deep learning to model historical routing patterns and autonomously generate new heuristics tailored to problem-specific characteristics. …”
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Meteorological data implications modeling on evapotranspiration variability in arid and semi-arid zones in Saudi Arabia using hybrid metaheuristic by Oulad Naoui Noureddine, Sekkoum Mohamed, Cherif El Amine, Ali Alzaed, Meseret Abeje Gedfew, Sherif S. M. Ghoneim, Enas E. Hussein

“…In this paper, the Bat algorithm (BAT) with the Newton Method (NM), Bird Swarm Algorithm (BSA), Genetic Algorithm (GA), and Chicken Swarm Optimization Algorithm (CSO) are used as a hybrid model in arid and semi-arid zones in Saudi Arabia as well as for modeling rainfall, temperature, and solar radiation implications on evapotranspiration variability. …”
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Phytoplanktonic Photoacclimation Under Clouds by Charlotte Begouen Demeaux, Emmanuel Boss, Jason R. Graff, Michael J. Behrenfeld, Toby K. Westberry

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A Developed Mathematical Model for Designing a Multilevel Sustainable Supply Chain Network Taking into Account Environmental Decisions by Mehrab Paydarfard, Roya Pirzadeh, Ali Ahmadi, Masoud Zohrabi, Farkhondeh Mortaz Hejri, Malek Hasan

“…In addition, the proposed model was optimized by the whale optimization algorithm (WOA) to find the best solution in large-scale instances in a short and reasonable time. …”
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