Application of Metaheuristics for Optimizing Predictive Models in iHealth: A Case Study on Hypotension Prediction in Dialysis Patients by Felipe Cisternas-Caneo, María Santamera-Lastras, José Barrera-Garcia, Broderick Crawford, Ricardo Soto, Cristóbal Brante-Aguilera, Alberto Garcés-Jiménez, Diego Rodriguez-Puyol, José Manuel Gómez-Pulido

“…Dialysis session data from 758 patients collected between January 2016 and October 2019 were analyzed. Particle Swarm Optimization, Grey Wolf Optimizer, Pendulum Search Algorithm, and Whale Optimization Algorithm were employed to reduce the feature space, removing approximately 45% of clinical and analytical variables while maintaining high recall for the minority class of patients experiencing hypotension. …”
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Multiple objectives escaping bird search optimization and its application in stock market prediction based on transformer model by Dedai Wei, Zimo Wang, Minyu Qiu, Juntao Yu, Jiaquan Yu, Yurun Jin, Xinye Sha, Kaichen Ouyang

“…To address this issue, this paper proposes an innovative multi-objective optimization algorithm—the Multi-Objective Escape Bird Algorithm (MOEBS)—and introduces the MOEBS-Transformer architecture to enhance the efficiency and effectiveness of hyper-parameter optimization for Transformer models. …”
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Optimizing Energy Efficiency in Vehicular Edge-Cloud Networks Through Deep Reinforcement Learning-Based Computation Offloading by Ibrahim A. Elgendy, Ammar Muthanna, Abdullah Alshahrani, Dina S. M. Hassan, Reem Alkanhel, Mohamed Elkawkagy

“…To further improve system efficiency, a novel caching strategy is introduced, enabling edge servers to store completed tasks, which in turn reduces both latency and energy consumption. An optimization model is also proposed to minimize energy expenditure while ensuring that latency constraints are satisfied during computation offloading. …”
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Integrated energy microgrids participating in voltage regulation ancillary services: An improved ADMM based distributed optimization approach by Hao Xiao, Wei Pei, Daoxin Han, Xiaowei Pu, Jiarui Wang

“…Moreover, an improved accelerated consensus alternating direction method of multipliers algorithm is proposed to accelerate distributed optimization solutions of the model while protecting user privacy. …”
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Development of View Optimization Techniques for Structural Monitoring Systems Using Post-Processing of Structural Analysis and Image Processing by Yonghui Park

“…The proposed framework for view optimization utilized the results from structural analysis performed in ABAQUS to extract initial camera positions and direction vectors, which served as inputs for an optimization algorithm. …”
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A Preemptive Scan Speed Control Strategy Based on Topographic Data for Optimized Atomic Force Microscopy Imaging by Thi Thu Nguyen, Oyoo Michael Juma, Luke Oduor Otieno, Thi Ngoc Nguyen, Yong Joong Lee

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Optimized Super-Twisting Sliding Mode Control with Parameter Estimation for Autonomous Vehicle Longitudinal Motion on Downhill Road by Kbrom Lbsu Gdey, Woo Young Choi

“…Longitudinal motion control is a critical aspect of autonomous vehicle area, requiring a well-designed controller to ensure optimal system performance, safety, and comfort under varying driving conditions. …”
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Intelligent Prediction Model of the Triaxial Compressive Strength of Rock Subjected to Freeze-Thaw Cycles Based on a Genetic Algorithm and Artificial Neural Network by Xin Xiong, Feng Gao, Keping Zhou, Yuxu Gao, Chun Yang

“…The structure, initial connection weights, and biases of the ANN were optimized progressively based on GA. After obtaining the optimal GA-ANN model, the performance of the GA-ANN model was compared with that of a simple ANN model. …”
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Enhancing Power Quality in Standalone Microgrids Powered by Wind and Battery Systems Using HO Algorithm Based Super Twisting Sliding Mode Controllers by Sana Sahbani, Oumnia Licer, Hassane Mahmoudi, Abdennebi Hasnaoui, Mustapha Kchikach

“…To mitigate these issues, a control strategy utilizing Super Twisting Sliding Mode (STSM) controllers tuned by the Hippopotamus Optimization Algorithm (HOA) is proposed. The HOA algorithm efficiently determines optimal STSM controller parameters, leading to improved system performance and stability. …”
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Feasibility study of “double-low” scanning protocol combined with artificial intelligence iterative reconstruction algorithm for abdominal computed tomography enhancement in patien... by Mei-Tong Ji, Ren-Ren Wang, Qi Wang, Han-Shuo Li, Yong-Xia Zhao

“…Karl 3D level 5 was the optimal algorithm level for group A, while AIIR level 4 was the optimal algorithm level for group B. …”
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Advanced long-term actual evapotranspiration estimation in humid climates for 1958–2021 based on machine learning models enhanced by the RReliefF algorithm by Ahmed Elbeltagi, Salim Heddam, Okan Mert Katipoğlu, Abdullah A. Alsumaiei, Mustafa Al-Mukhtar

“…To address this issue and guarantee more accurate ET predictions, this study attempts the following: i) to assess the performance of five machine learning (ML) models optimized by the RReliefF algorithm in estimating actual ET values for each month in four Chinese provinces under various agroclimatic conditions; and ii) to select the optimal model based on statistical metrics while minimizing discrepancies between the estimated and actual ET values. …”
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Personalized metronomic radiopharmaceutical therapy through injection profile optimization via physiologically based pharmacokinetic (PBPK) modeling by Aryan Golzaryan, M. Soltani, Farshad Moradi Kashkooli, Babak Saboury, Arman Rahmim

“…We designed a treatment algorithm to select optimal regimens with high AD, while investigating what we term radiopharmaceutical delivery payload (RDP). …”
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A novel fault diagnosis method for gearbox based on RVMD and TELM with composite chaotic grey wolf optimizer by Xuebin Huang, Anfeng Xu, Hongbing Liu, Bingcheng Ye

“…A novel grey wolf optimization algorithm, named composite chaotic grey wolf optimizer (CCGWO), is used to optimize the kernel parameter of TELM. …”
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Hybrid Harris hawks-optimized random forest model for detecting multi-element geochemical anomalies related to mineralization by Hamid Sabbaghi, Nader Fathianpour

“…In this study, Harris hawks optimization (HHO) algorithm was employed to optimize known hyperparameters of the random forest (RF) method for detecting multi-element geochemical anomalies related to mineralization occurrences in the Feyzabad district of the Razavi Khorasan province, NE Iran. …”
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Enhanced SOC estimation method for lithium-ion batteries using Bayesian-optimized TCN–LSTM neural networks by Taotao Hu, Xiting Zhu, Maokai Tian

“…This study uses Bayesian optimization to fine-tune the hyperparameters of the TCN–LSTM model, ensuring optimal performance. …”
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Intelligent Classification Method for Rail Defects in Magnetic Flux Leakage Testing Based on Feature Selection and Parameter Optimization by Kailun Ji, Ping Wang, Yinliang Jia

“…For real-world limited samples (100 sets), adaptive optimization achieved 80% accuracy while boosting minority class (“spalling”) F1-score by 0.25 with 50% false alarm reduction. …”
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A Multi-Objective Optimization Method for Carbon–REC Trading in an Integrated Energy System of High-Speed Railways by Wei-Na Zhang, Zhe Xu, Ying-Yi Hong, Fang-Yu Liu, Zhong-Qin Bi

“…The proposed EDMOA algorithm optimizes storage configurations across multiple operational climatic regimes. …”
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Optimizing China's carbon quota allocation for peak emissions: A novel AMLC framework tailored to regional dynamics. by Lanlan Lian, Xiaojun Ma, Yimeng Wang, Qingli Dong

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A Novel Hybrid Deep Learning Model Based on Simulated Annealing and Cuckoo Search Algorithms for Automatic Radiomics-Based COVID-19 Diagnosis by Basma Jumaa Saleh, Zaid Omar, Muhammad Amir As’ari, Vikrant Bhateja, Lila Iznita Izhar

“…To further enhance COVID-19 lesion estimation, novel optimization strategies, including a hybrid simulated annealing-cuckoo search (SA-CS) algorithm, are introduced alongside the original SA method. …”
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A dimension reduction assisted credit scoring method for big data with categorical features by Tatjana Miljkovic, Pei Wang

“…The evidence suggests that even small improvements in the accuracy of existing credit-scoring models may optimize profits while effectively managing risk exposure. …”
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