Machine learning predicts improvement of functional outcomes in spinal cord injury patients after inpatient rehabilitation by Mohammad Rasoolinejad, Irene Say, Peter B. Wu, Xinran Liu, Yan Zhou, Yan Zhou, Nathan Zhang, Emily R. Rosario, Daniel C. Lu, Daniel C. Lu, Daniel C. Lu

“…The ability to accurately predict functional outcomes for SCI patients is essential for optimizing rehabilitation strategies, guiding patient and family decision making, and improving patient care.MethodsWe conducted a retrospective analysis of 589 SCI patients admitted to a single acute rehabilitation facility and used the dataset to train advanced machine learning algorithms to predict patients' rehabilitation outcomes. …”
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MetaForecaster: A PSO-Driven Neural Model for Sustainable Industrial Air Quality Management by Marzia Ahmed, Shahrin Islam, Mohd Herwan Sulaiman, Md Maruf Hassan, Touhid Bhuiyan

“…The PSO algorithm strategically optimizes network weights and biases, utilizing the mean squared error (MSE) as the fitness metric to ensure prediction accuracy. …”
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A Temporal Convolutional Network–Bidirectional Long Short-Term Memory (TCN-BiLSTM) Prediction Model for Temporal Faults in Industrial Equipment by Jinyin Bai, Wei Zhu, Shuhong Liu, Chenhao Ye, Peng Zheng, Xiangchen Wang

“…First, preprocessed industrial operation data are fed into the model, and hyperparameter optimization is conducted using the Optuna framework to improve training efficiency and generalization capability. …”
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The Application of Artificial Intelligent Algorithms in Electric Propulsion by Tian Bin, An Bingchen, Xie Kan, Yang Sulan

“…These algorithms can not only train models based on data to optimize the performance of electric thrusters, but also analyze and solve the mathematical and physical models of plasmas within electric thrusters. …”
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Modeling 5G-NR User Blocking Probability in Conditional Handover-Enabled Heterogeneous Networks by Amiraslan Haghrah, Javad Musevi Niya, Jafar Pourrostam

“…To demonstrate the practical applicability of the proposed model, we present a case study involving a multi-objective optimization problem solved using the Non-Dominated Sorting Genetic Algorithm II (NSGA-II). …”
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A dual layer secure and energy-efficient model for border surveillance using sea lion inspired strategy in wireless sensor networks by Jayachandran J, Vimaladevi K

“…This paper presents a Dual Layer Sea Lion Optimization algorithm (DL-SLnOA) model, a bio-inspired, clustering and routing that focuses on energy efficiency and security to enhance performance under challenging conditions. …”
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Knowledge- and Model-Driven Deep Reinforcement Learning for Efficient Federated Edge Learning: Single- and Multi-Agent Frameworks by Yangchen Li, Lingzhi Zhao, Tianle Wang, Lianghui Ding, Feng Yang

“…We formulate a joint optimization problem for FL worker selection and algorithm parameter configuration to minimize the final test loss subject to time and energy constraints. …”
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Bi-objective optimization of magnetic core loss and magnetic energy transfer of magnetic element based on a hybrid model integrating GAN and NSGA-II by Xiaoyan Shen, Hongkui Zhong, Haixin Wu, Yaqian Mao, Ruiqing Han

“…Furthermore, a comparison with the NSGA-II algorithm is conducted to verify the efficiency of the bi-objective optimization model.…”
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Fault Location and Route Selection Strategy of Distribution Network Based on Distributed Sensing Configuration and Fuzzy C-Means by Bo Li, Guochao Qian, Lijun Tang, Peng Sun, Zhensheng Wu

“…When a fault occurs in the distribution network, the sensor device based on optimal configuration collects fault feature data, combines it with the FCM clustering algorithm to classify nodes according to fault feature similarity, and divides the most significant fault-affected section as the core fault area. …”
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Enhancing fever of unknown origin diagnosis: machine learning approaches to predict metagenomic next-generation sequencing positivity by Zhi Gao, Zhi Gao, Zhi Gao, Yongfang Jiang, Yongfang Jiang, Yongfang Jiang, Mengxuan Chen, Mengxuan Chen, Mengxuan Chen, Weihang Wang, Weihang Wang, Weihang Wang, Qiyao Liu, Qiyao Liu, Qiyao Liu, Jing Ma, Jing Ma, Jing Ma

“…Using the SHAP method, the five most important factors for predicting mNGS-positive results were albumin, procalcitonin, blood culture, disease type, and sample type.ConclusionThe validated LightGBM-based predictive model could have practical clinical value in enhancing the application of mNGS in the etiological diagnosis of FUO, representing a powerful tool to optimize the timing of mNGS.…”
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Supply Chains Problem During Crises: A Data-Driven Approach by Farima Salamian, Amirmohammad Paksaz, Behrooz Khalil Loo, Mobina Mousapour Mamoudan, Mohammad Aghsami, Amir Aghsami

“…The solution methodology combines the Grasshopper Optimization Algorithm (GOA) and the ɛ-constraint method, efficiently addressing the multi-objective nature of the problem. …”
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Enhancing Stock Portfolio Selection with Trapezoidal Bipolar Fuzzy VIKOR Technique with Boruta-GA Hybrid Optimization Model: A Multicriteria Decision-Making Approach by Sunil Kumar Sharma

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Research on Multi-train Cooperative Utilization of Regenerative Braking Energy for Low-speed Maglev Traffic by JIAO Yanjun, LIU Sikai, MA Xiao, LIU Shaoke

“…The elite reservation strategy and migration strategy were adopted to improve the stability and speed of the optimization process in the algorithm. …”
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Faulted Line Segment Location Method for Low-Voltage Distribution Network Based on Adjacency Matrix by Yongfeng YAO, Qizhe WANG, Huiping WANG, Jia JIA, Xibin XIA

“…Based on these works, the fault line segment location model of low-voltage distribution network considering multiple faults is developed, and the particle swarm optimization algorithm is used to solve the model. …”
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EWT多重分解与若干新型元启发式算法优化的多层感知器月径流预测 by CAI Liang, BAO Yanfei, CUI Dongwen

“…To improve the accuracy of monthly runoff time series prediction, enhance the performance of multi-layer perceptron (MLP), and compare and verify the optimization effects of four new metaheuristic algorithms on benchmarking functions and instance objective functions, including catch fish optimization algorithm (CFOA), flood algorithm (FLA), arctic puffin optimization (APO), educational competition optimization (ECO), and particle swarm optimization (PSO), an EWT^III-CFOA/FLA/APO/ECO/PSO-MLP prediction model was proposed. …”
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Influence of Tire Parameters on Contact Patch and Axle Force Generation against Short Obstacles Using DOE Approach by Vikas Birajdar, Seyed Jamaleddin Mostafavi Yazdi, Madhu Kandampadath, Mohammad Behroozi, Javad Baqersad

“…This algorithm filters the geometries of uneven surfaces and must be seamlessly integrated with a rigid ring model. …”
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SHERA: SHAP-Enhanced Resource Allocation for VM Scheduling and Efficient Cloud Computing by Ashwin Singh Slathia, Abhiram Sharma, P. B. Krishna, Saksham Anand, Ayush Rathi, Linda Joseph, Xiao-Zhi Gao

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Super-Resolution Reconstruction From Multiple Defocused Infrared Images of Stationary Scene by Yuxing Mao, Benjiang Zhao, Dongmei Yan, Haiwei Jia

“…We have developed an image degradation model by analyzing optical lens imaging, using the particle swarm optimization algorithm to estimate the PSF of the HR image, and using compressed sensing theory to implement SRR based on the noncoherent characteristics of the defocused infrared images. …”
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A solution to the Single-School school bus routing problem considering accessibility and economy by Zizhan Jiang, Jiying Wang, Siyuan Huang, Hua Daniel Xu

“…Heuristic algorithms, such as Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), and Floyd-Warshall, are employed to determine the initial solution, which includes the optimal number of buses and their preliminary routes. …”
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A study of high-resolution remote sensing image landslide detection with optimized anchor boxes and edge enhancement by Kun Wang, Ling Han, Juan Liao

“…Using the You Only Look Once v5 network (YOLOv5) in combination with the Gabor filter, its edge detection, detection anchor frame and small object detection scale are improved and optimized. The YOLOv5(ISODATA) model was finally established for landslide image detection by incorporating the edge control factor and four clustering algorithms (K-means, K-means + +, k-medoid, and Iterative Self-Organizing Data Analysis Techniques Algorithm (ISODATA) to evaluate the accuracy of the detection anchor frame and add small target large-scale sampling. …”
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