State of Charge Estimation of Lithium Battery Utilizing Strong Tracking H-Infinity Filtering Algorithm by Tianqing Yuan, Yang Liu, Jing Bai, Hao Sun

“…Simulation experiments indicate that, compared to the HIF algorithm, the STF-HIF algorithm achieves a maximum absolute SOC estimation error (MaxAE) of 0.69%, 0.72%, and 1.22%, with mean absolute errors (MAE) of 0.27%, 0.25%, and 0.38%, and root mean square errors (RMSE) of 0.33%, 0.30%, and 0.46% under dynamic stress testing (DST), federal urban driving schedules (FUDS), and Beijing dynamic stress testing (BJDST) conditions, respectively.…”
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Machine learning algorithms applied to the diagnosis of COVID-19 based on epidemiological, clinical, and laboratory data by Silvia Elaine Cardozo Macedo, Marina de Borba Oliveira Freire, Oscar Schmitt Kremer, Ricardo Bica Noal, Fabiano Sandrini Moraes, Mauro André Barbosa Cunha

“…Epidemiological, clinical, and laboratory data were processed by machine learning algorithms in order to identify patterns. Mean AUC values were calculated for each combination of model and oversampling/undersampling techniques during cross-validation. …”
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Optimizing protein-ligand docking through machine learning: algorithm selection with AutoDock Vina by Ala’ Omar Hasan Zayed

“…Methods We developed a comprehensive algorithm set comprising eighty-one distinct configurations of the Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm within AutoDock Vina. …”
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A new approach to error inequalities: From Euler-Maclaurin bounds to cubically convergent algorithm by Miguel Vivas-Cortez, Usama Asif, Muhammad Zakria Javed, Muhammad Uzair Awan, Yahya Almalki, Omar Mutab Alsalami

“…With the help of a new auxiliary result and some well-known ones, like Hölder's, the power mean, improved Hölder, improved power mean, convexity, and bounded features of the function, we obtained new bounds for Euler-Maclaurin's inequality. …”
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Prediction of energy consumption in four sectors using support vector regression optimized with genetic algorithm by Md. Sadikul Hasan, Md. Tarequzzaman, Md. Moznuzzaman, Md Abdul Ahad Juel

“…The proposed model's efficacy is assessed by calculating the R2 value, mean absolute error (MAE), root mean squared error (RMSE), and residual plot. …”
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Short-Term Power Load Prediction Based on Level Processing Method and Improved GWO Algorithm by Yuntong Li

“…The genetic algorithm is applied to optimize the traditional grey wolf algorithm. …”
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An algorithm to assess importance of predictors in systematic reviews of prediction models: a case study with simulations by Ruohua Yan, Chen Wang, Chao Zhang, Xiaohang Liu, Dong Zhang, Xiaoxia Peng

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CLASSIFICATION AND PREDICTION OF BENTHIC HABITAT FROM SCIENTIFIC ECHOSOUNDER DATA: APPLICATION OF MACHINE LEARNING ALGORITHMS by Baigo HAMUNA, Sri PUJIYATI, Jonson Lumban GAOL, Totok HESTIRIANOTO

“… This study aims to map three main benthic habitats (coral, seagrass, and sand) in Kapota Atoll (Wakatobi, Indonesia) using single-beam echosounder (SBES) Simrad EK15. …”
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Innovative approaches to beam forming antenna array systems with adaptive Partial Update NLMS algorithms by Zahraa A. Shubber, Thamer M. Jamel, Ali.K. Nahar

“…For the most part, we will be discussing PU Normalized Least Mean Square (PU NLMS) algorithms like M-max NLMS, Periodic-NLMS, and Stochastic-NLMS. …”
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Beyond accuracy: a framework for evaluating algorithmic bias and performance, applied to automated sleep scoring by Michal Bechny, Luigi Fiorillo, Julia van der Meer, Markus Schmidt, Claudio Bassetti, Athina Tzovara, Francesca Faraci

“…Additionally, performance metrics are typically reported as the mean of on-subject results, neglecting critical scenarios—such as different quantiles—that could better convey the algorithm’s capabilities and limitations to clinicians as end-users. …”
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Improving Performance of the Convolutional Neural Networks for Electricity Theft Detection by using Cheetah Optimization Algorithm by Hassan Ghaedi, Seyed Reza Kamel Tabbakh, Reza Ghaemi

“…Meta-heuristic-based search methods are suitable for solving these problems. Therefore, the main contribution of this paper is to use the high ability of the cheetah optimization algorithm (CHOA) to optimally extract CNN hyper-parameters. …”
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Pseudorange estimation algorithm combining code and carrier phase based on Gaussian sum particle filtering by LI Li-min1, GONG Wen-bin1, LIU Hui-jie1, YU Jin-pei1

“…According to the characteristic that code measurements yielded noisy but unambiguous pseudorange estimates and carrier phase measurements were almost noiseless but were affected by integer ambiguity,a novel Gaussian sum particle filter（GSPF） algorithm was proposed to combine the advantages of the two measurements.The theoretical analysis and simulation results show that the proposed algorithm is immune from cycle slips and produces smaller mean square errors.…”
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Distributed Algorithm for Traffic Data Collection and Data Quality Analysis Based on Wireless Sensor Networks by Nan Ding, Guozhen Tan, Wei Zhang, Hongwei Ge

“…Considering the certain correlated characteristics, this algorithm firstly processes the data samples with an aggregation model based on the mean filter, and then, the data quality is analyzed, and partial bad data are repaired by the cusp catastrophe theory. …”
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Hybridization of Machine Learning Algorithms and an Empirical Regression Model for Predicting Debris-Flow-Endangered Areas by Xiang Wang, Mi Tian, Qiang Qin, Jingwei Liang

“…Finally, the performance metrics (i.e., coefficient of determination (R2), root-mean-square error (RMSE), and mean absolute error (MAE)) of the proposed hybrid models are comprehensively investigated and compared with the single predictive model (i.e., MARS, RF, SVM, and the empirical model) under fivefold cross-validation. …”
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Aspect-Based Sentiment Analysis with LDA and IndoBERT Algorithm on Mental Health App: Riliv by Firda Ayu Dwi Aryanti, Ardytha Luthfiarta, Dennis Adiwinata Irwan Soeroso

“…This study used 3068 reviews from September 2015 to December 2024. The main results obtained were 1) Identified the sentiment that positive is highest in 2020, neutral is highest in 2020, and negative is highest in 2018. 2) Identified 4 main aspects of the Riliv application: Access Support, Counseling Services, Meditation Features, and User Interface with LDA. 3) The majority distribution was negative on User Interface, neutral on Counseling Services, and positive on Meditation Features. 4) The effectiveness of IndoBERT compared to the non-transformer baseline algorithm. 5) The most optimal results were obtained with 70% training, 10% validation, and 20% testing, resulting in 95% accuracy.…”
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Advanced Signal Processing Algorithm-Based State Estimation and Denoising of ECG Signals for Biomedical Applications by Saad Arif, Mohammad Maroof Maroof Siddiqui, Nayef Alqahtani, Kamran Shah, Muhammad Attique Attique Khan, Naoufel Kraiem

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Optimizing Vital Signs in Patients With Traumatic Brain Injury: Reinforcement Learning Algorithm Development and Validation by Hongwei Zhang, Mengyuan Diao, Sheng Zhang, Peifeng Ni, Weidong Zhang, Chenxi Wu, Ying Zhu, Wei Hu

“…Compared with clinical doctors, AI algorithms select normal temperatures more frequently (36.56 °C to 36.83 ℃) and recommend mean arterial pressure levels of 87.5‐95.0 mm Hg. …”
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Fault Diagnosis Method of Wind Turbine Pitch Angle Based on PCA-KNN Fusion Algorithm by Xi CHEN, Luping LI, Rui LIU, Bo YANG, Zihao DENG, Zhonggui LI

“…With regard to the four main fault types of the pitch angle of a wind turbine pitch system and the data analysis of the wind turbine, an identification method of abnormal pitch angles of a wind turbine is proposed, depending on nonparametric kernel density estimation and Relief-F based feature extraction for data processing and the PCA-KNN fusion algorithm for fault diagnosis. …”
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ANALYTICAL MODEL OF NOISE STABILITY CALCULATION OF SYSTEMS WITH MULTIPOSITIONAL MODULATION AND CODING BY REED-SOLOMON ALGORITHM by E. B. Lipkovich, V. A. Kovshik, A. A. Serchenya

“…The calculated ratios presented in the article include only the main parameters of the code (free distance, codeword length, relative code speed) and of the modulation type (modulation order, squared noise immunity). …”
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A Fast Fault Location Based on a New Proposed Modern Metaheuristic Optimization Algorithm by Mohammad Parpaei, Hossein Askarian-Abyaneh, Farzad Razavi

“…The main advantage of the presented algorithm is the parallel estimation processing to improve the convergence speed and the accuracy of the objective function of the fault location, and was applied to various fault types and various operating conditions to validate the performance of the proposed approach. …”
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