Predicting the Speed of Chinese Elite Cross-Country Skiers: A Neural Network Approach Based on the Measurement of Key Biomechanical and Physiological Parameters by Huijuan Shi, Xiaolan Zhu, Shuang Zhao, Hans-Christer Holmberg, Hui Liu

“…The developed neural network model demonstrated high precision in predicting skiing speeds, evidenced by a strong correlation with actual speeds (correlation coefficient of 0.953) and 97.1% of predictions falling within the 95% Bland–Altman agreement limits, affirming the model’s reliability and effectiveness in forecasting skiing performance.…”
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Long Short-Term Memory-Based Impact of Traffic Incidents: Case Study of Seoul Expressway, Korea by Sang-Hoon Bae, Duy Quang Tran, Bog-gi Park, Huy Tran Quang, Luan Nguyen Huu

“…Finally, the long short-term memory (LSTM) is implemented for training the dataset and forecasting traffic incidents for the prediction model. …”
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Modelling the Temperature of a Data Centre Cooling System Using Machine Learning Methods by Adam Kula, Daniel Dąbrowski, Marcin Blachnik, Maciej Sajkowski, Albert Smalcerz, Zygmunt Kamiński

“…In this paper, we discuss the dataset creation process as well as the process of evaluating a model for forecasting the temperature in the warm corridor of the data centre. …”
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Dynamical changes in seismic properties prior to, during, and after the 2014–2015 Holuhraun eruption, Iceland by M. R. P. Sudibyo, E. P. S. Eibl, S. Hainzl, S. Hainzl, M. Ohrnberger

“…During the eruption, PE and PPE fit the lava discharge rate, showing their potential to forecast the duration of the eruption. While one parameter may be more sensitive to one stage, the other may respond better to another stage. …”
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EMPIRICAL ASPECTS OF THE INFLUENCE OF THE COOPERATION OF FISCAL INSTITUTIONS ON PROPERTY TAX ADMINISTRATION by Oksana Desyatnyuk, Andriy Krysovatyy, Bohdana Shuliuk, Fedir Tkachyk, Vadym Maslii

“…Theoretical and methodical approaches to forecasting property tax revenues to local budgets of Ukraine have been further developed, taking into account fiscal policy trends under martial law and using the «forecasting» module of the SPSS statistics package. …”
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The differences in microbial communities and Tick-Borne pathogens between Dermacentor marginatus and Hyalomma asiaticum collected from the Northwestern Xinjiang Uygur Autonomous Re... by Like Duan, Xiaona Yang, Lin Zhang, Xuexia Hou, Lijuan He, Jingwen Li, Qin Hao

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Prognostic Nomogram for Predicting Survival in Asian Patients With Small‐Cell Lung Cancer: A Comprehensive Population‐Based Study and External Verification by Yuanli Xia, Jingjing Qu, Yufang Wang, Yanping Zhu, Jianying Zhou, Jianya Zhou

“…It offers a more precise and reliable means of forecasting the prognosis of Asian SCLC patients.…”
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Impact of climate change on river flow, using a hybrid model of LARS_WG and LSTM: A case study in the Kashkan Basin by Fatemeh Avazpour, Mohammad Reza Hadian, Ali Talebi, Ali Torabi Haghighi

“…This study investigates river flow variability in the Kashkan Basin, southwest Iran, through the application of a hybrid approach involving the use of Long Ashton Research Station Weather Generator (LARS-WG) for climate downscaling and Long Short-Term Memory (LSTM) networks in the river flow forecasting. Advanced techniques like Extreme Gradient Boosting (XGBoost), Shapley Additive exPlanations (SHAP), and Analysis of Variance (ANOVA) were employed in order to decide the significant influencing factors of river flow, including rainfall, temperature, and past values of river flow. …”
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Great Gerbils (Rhombomys opimus) in Central Asia Are Spreading to Higher Latitudes and Altitudes by Xuan Liu, Li Xu, Jianghua Zheng, Jun Lin, Xuan Li, Liang Liu, Ruikang Tian, Chen Mu

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Research on the Influence of SST in Different Regions on the Interannual Variability of Winter Fog Days over Eastern China by Qisheng CEN, Peng LIU

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Predictive modeling of air quality in the Tehran megacity via deep learning techniques by Abdullah Kaviani Rad, Mohammad Javad Nematollahi, Abbas Pak, Mohammadreza Mahmoudi

“…The feature importance analysis suggested that CO, O3 and NO2, SO2 and PM10, and PM2.5 are most affected by temperature, humidity, PM2.5, and PM10, respectively. …”
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Study on the Change Characteristics of and Population Exposure to Heatwave Events on the North China Plain by Long-Fei Zhan, Yanjun Wang, Hemin Sun, Jianqing Zhai, Mingjin Zhan

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USING ARTIFICIAL INTELLIGENCE (AI) AND DEEP LEARNING TECHNIQUES IN FINANCIAL RISK MANAGEMENT by Joseph Olorunfemi AKANDE

“…Our analysis highlights the extensive use of sophisticated statistical models in financial risk management. …”
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Grade Indicators and Distribution Characteristics of Heat Damage to Summer Maize in the Huang–Huai–Hai Plain by Qing Li, Peijuan Wang, Xin Li, Junxian Tang, Yang Li, Yuanda Zhang, Yuping Ma

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Antibiotic use and financial impact of a comprehensive beta-lactam allergy management program by Karan Raja, Lakhini Vyas, Susan Morrison, Donald Beggs, Mitesh Patel, Mona Philips

“…Difference between actual and forecasted DOT was deemed DOT avoided (DOT-A) for each consecutively enrolled patient. …”
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Imported malaria in Cabo Verde (2010-2024): Risks to post-elimination stability. by Adilson José DePina, Giovanni Leite Lima, António Lima Moreira, El Hadji Amadou Niang, Klauss Kleydmann S Garcia

“…Joinpoint Regression Analysis was performed to assess time trends, and Holt-Winters additive models were applied for time-series forecasting. …”
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ARBOALVO: A Bayesian spatiotemporal learning and predictive model for dengue cases in the endemic Northeast city of Natal, Rio Grande do Norte, Brazil. by Mariane Branco Alves, Rafael Santos Erbisti, Aline Araújo Nobre, Taynãna César Simões, Alessandre de Medeiros Tavares, Márcia Cristina Melo, Rodrigo Moreira Pedreira, Jan Pierre Martins de Araújo, Marilia Sá Carvalho, Nildimar Alves Honório

“…<h4>Conclusions/significance</h4>The proposed Bayesian space-time analysis can contribute to the operational control of dengue and Aedes aegypti by identifying priority areas and forecasting dengue cases for the next four weeks. …”
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A Hybrid Machine Learning Approach for High-Accuracy Energy Consumption Prediction Using Indoor Environmental Quality Sensors by Bibars Amangeldy, Nurdaulet Tasmurzayev, Timur Imankulov, Baglan Imanbek, Waldemar Wójcik, Yedil Nurakhov

“…Accurate forecasting of energy consumption in buildings is essential for achieving energy efficiency and reducing carbon emissions. …”
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An explainable AI-based hybrid machine learning model for interpretability and enhanced crop yield prediction by Anuradha Yenkikar, Ved Prakash Mishra, Manish Bali, Tabassum Ara

“…The use of machine learning (ML) in crop yield prediction has significantly improved forecast accuracy. However, the adoption of these models by policymakers and farmers is hindered by their lack of interpretability. …”
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Consumption Trends of Antifungal and Antiprotozoal Agents for Human Systemic Use in Kazakhstan from 2017 to 2023 by Yuliya Semenova, Assiya Kussainova, Laura Kassym, Ainur Aimurziyeva, Daniil Semenov, Lisa Lim

“…This study aims to fill this gap by providing a comprehensive analysis of nationwide consumption trends in Kazakhstan over a seven-year period (2017–2023). …”
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