Advanced Methodology for Fraud Detection in Energy Using Machine Learning Algorithms by Silviu Gresoi, Grigore Stamatescu, Ioana Făgărășan

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A Multi-Fusion Early Warning Method for Vehicle–Pedestrian Collision Risk at Unsignalized Intersections by Weijing Zhu, Junji Dai, Xiaoqin Zhou, Xu Gao, Rui Cheng, Bingheng Yang, Enchu Li, Qingmei Lü, Wenting Wang, Qiuyan Tan

Subjects: “…pedestrian trajectory prediction…”
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Atmospheric Modeling for Wildfire Prediction by Fathima Nuzla Ismail, Brendon J. Woodford, Sherlock A. Licorish

“…Our study focuses on developing wildfire prediction models using one-class classification algorithms. …”
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Melanoma risk prediction models by Nikolić Jelena, Lončar-Turukalo Tatjana, Sladojević Srđan, Marinković Marija, Janjić Zlata

“…The aim of this study was to identify most significant factors for melanoma prediction in our population and to create prognostic models for identification and differentiation of individuals at risk. …”
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Forecasting returns volatility of cryptocurrency by applying various deep learning algorithms by Farman Ullah Khan, Faridoon Khan, Parvez Ahmed Shaikh

“…Abstract The study aims at forecasting the return volatility of the cryptocurrencies using several machine learning algorithms, like neural network autoregressive (NNETAR), cubic smoothing spline (CSS), and group method of data handling neural network (GMDH-NN) algorithm. …”
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Machine Learning Models to Predict Google Stock Prices by Cosmina Elena Bucura, Paolo Giudici

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A hybrid BOA-SVR approach for predicting aerobic organic and nitrogen removal in a gas-liquid-solid circulating fluidized bed bioreactor by Shaikh Abdur Razzak, Nahid Sultana, S.M. Zakir Hossain, Muhammad Muhitur Rahman, Yue Yuan, Mohammad Mozahar Hossain, Jesse Zhu

“…This study introduces the hybrid of the Bayesian optimization algorithm and support vector regression (BOA-SVR) models to predict the removal of aerobic organic (total chemical oxygen demand, COD) and nitrogen compounds such as total Kjeldahl Nitrogen (TKN), ammonium nitrogen (NH4-N), and nitrate nitrogen (NO3-N) from municipal wastewater in a gas-liquid-solid circulating fluidized bed (GLSCFB) bioreactor. …”
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Mapping and interpretability of aftershock hazards using hybrid machine learning algorithms by Bo Liu, Haijia Wen, Mingrui Di, Junhao Huang, Mingyong Liao, Jingyuan Yu, Yutao Xiang

“…By employing the stacking algorithm to optimize and combine XGBoost and LightGBM models, the proposed model significantly improves the prediction performance. …”
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Accurate estimation of permeability reduction resulted from low salinity water flooding in clay-rich sandstones by Xiaojuan Zhang, Muntadher Abed Hussein, Tarak Vora, Anupam Yadav, Asha Rajiv, Aman Shankhyan, Sachin Jaidka, Mehul Manu, Farzona Alimova, Issa Mohammed Kadhim, Zainab Jamal Hamoodah, Fadhil Faez, Ahmad Khalid

“…The results show that random forest and ensemble learning algorithms delivered the highest predictive accuracy, evidenced by the most substantial coefficient of determination (R2) and minimal error metrics. …”
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Optimizing Renewable Energy Integration Using IoT and Machine Learning Algorithms by Orken Mamyrbayev, Ainur Akhmediyarova, Dina Oralbekova, Janna Alimkulova, Zhibek Alibiyeva

“…Results showed significant improvements in forecasting accuracy, with the LSTM model achieving a 59.1% reduction in Mean Absolute Percentage Error compared to the persistence model. …”
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Battery State of Health Estimation Methods: Implementation and Comparison of 11 Algorithms by Eojin Kim, Sunghun Jung

“…Unlike previous research, this work emphasizes empirical validation using real-world battery datasets and evaluates each algorithm based on predictive accuracy, computational complexity, and practical applicability. …”
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Plantar pressure classification and feature extraction based on multiple fusion algorithms by Xiaotian Bai, Xiao Hou, Yiling Song, Zhengyan Tang, Hongfeng Huo, Jingmin Liu

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Logatom articulation index evaluation of speech enhanced by blind source separation and single-channel noise reduction by Szymon DRGAS, Jędrzej KOCIŃSKI, Aleksander P. SĘK

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Enhancing power transformer health assessment through dimensional reduction and ensemble approaches in Dissolved Gas Analysis by Abdelmoumene Hechifa, Saurabh Dutta, Abdelaziz Lakehal, Hazlee Azil Illias, Arnaud Nanfak, Chouaib Labiod

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Adaptive algorithms for enhancement of speech subject to a high-level noise by Mariusz LATOS, Marek PAWEŁCZYK

“…One is the line enhancer, where the predictive realisation of the Wiener approach is used. …”
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Quantification of MODIS Land Surface Temperature Downscaled by Machine Learning Algorithms by Qi Su, Xiangchen Meng, Lin Sun, Zhongqiang Guo

“…By establishing non-linear relationships between LST and predictive variables through eXtreme Gradient Boosting (XGBoost) and Random Forest (RF) algorithms, the proposed framework was rigorously validated using in situ measurements across China’s Heihe River Basin. …”
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TRENDS IN SPANISH LITERATURE. HOW NEW TECHNOLOGIES INFLUENCE THE PROCESS OF LITERARY CREATION by Alina-Viorela PRELIPCEAN

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A Review on Automated Detection and Identification Algorithms for Highway Pavement Distress by Zhenglong Lv, Zhexin Hao, Yuhan Zhu, Cong Lu

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Automated Input Variable Selection for Analog Methods Using Genetic Algorithms by P. Horton, O. Martius, S. L. Grimm

“…Previous work showed the potential of genetic algorithms (GAs) to optimize most of the AM parameters. …”
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Bandit Algorithms for Efficient Toxicity Detection in Competitive Online Video Games by Jacob Morrier, Rafal Kocielnik, R. Michael Alvarez

“…When no pre-existing predictive model of toxic behavior is available, one must be estimated in real-time. …”
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