A New Custom Deep Learning Model Coupled with a Flood Index for Multi-Step-Ahead Flood Forecasting by Jianming Shen, Moyuan Yang, Juan Zhang, Nan Chen, Binghua Li

“…The results showed that incorporating the flood index <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>I</mi></mrow><mrow><mi>F</mi></mrow></msub></mrow></semantics></math></inline-formula> improved the forecast precision by up to 20%. The analysis of uncertainty revealed that the contributions of modeling factors, such as the datasets, model structures, and their interactions, varied across the forecast periods. …”
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Hail Forecast and Estimation of Its Maximum Size on the Output Data of the Global Atmospheric Model with Tree-Day Lead Time by Artur Khasanbievich Kagermazov, Lezhinka Tanashevna Sozaeva

“…The success of the hail forecast is assessed by the criteria of forecast quality. …”
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Antithrombotic Therapy and the Nearest Forecast of Pulmonary Embolism in Rutine Clinical Practice (Data of the Regional Vascular Center of the Ryazan Region) by N. N. Nikulina, Yu. V. Terekhovskaya, S. S. Yakushin

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A New Frontier in Wind Shear Intensity Forecasting: Stacked Temporal Convolutional Networks and Tree-Based Models Framework by Afaq Khattak, Jianping Zhang, Pak-wai Chan, Feng Chen, Abdulrazak H. Almaliki

“…Wind shear presents a considerable hazard to aviation safety, especially during the critical phases of takeoff and landing. Accurate forecasting of wind shear events is essential to mitigate these risks and improve both flight safety and operational efficiency. …”
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Effects of urbanization on extreme precipitation based on Weather Research and Forecasting model: A case study of heavy rainfall in Beijing by Yujia Pei, Jiahong Liu, Jia Wang, Chao Mei, Lirong Dong, Hao Wang

“…Furthermore, the reliability of the model results was validated through an analysis of the extreme precipitation event that occurred in July 2021, reinforcing the findings of this study. …”
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The enhanced integration of proven techniques to quantify the uncertainty of forecasting extreme flood events based on numerical weather prediction models by Mitra Tanhapour, Jaber Soltani, Hadi Shakibian, Bahram Malekmohammadi, Kamila Hlavcova, Silvia Kohnova, Peter Valent

“…Moreover, a comparative analysis was performed between the modeling approaches, i.e., probabilistic inflow forecasting and deterministic inflow forecasting. …”
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Local land‐use decisions drive losses in river biological integrity to 2099: Using machine learning to disentangle interacting drivers of ecological change in policy forecasts by Kimberly Bourne, Ryan S. D. Calder, Shan Zuidema, Celia Y. Chen, Mark E. Borsuk

“…This is partially because climate and LULC perturb ecological outcomes via incompletely understood site‐specific, interacting, and nonlinear mechanisms that are not well suited to analysis using classical statistical methods. This creates uncertainties over the benefits of local‐level interventions such as green infrastructure investments and urban densification, and limits how forecasts can be used to inform decision‐making. …”
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Why Do DJF 2023/24 Upper‐Level 200‐hPa Geopotential Height Forecasts Look Different From the Expected El Niño Response? by Mingyue Chen, Arun Kumar, Michelle L’Heureux, Peitao Peng, Tao Zhang, Martin P. Hoerling, Henry F. Diaz

“…These atypical height anomalies emerged despite the fact a strong El Niño was forecast. The analysis focuses on diagnosing the NMME forecasts of DJF 2023/24 for SSTs and 200‐hPa heights initialized at the beginning of November 2023 relative to other ensemble mean NMME DJF forecasts dating back to 1982. …”
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Impact of multiple radar wind profiler data assimilation on convective-scale short-term rainfall forecasts: OSSE studies over the Beijing–Tianjin–Hebei region by J. Zhao, J. Guo, X. Zheng

“…A detailed examination of the 21 July 2023 case reveals that the FH_RD experiment generally exhibits more skillful storm forecasts in terms of areal coverage, storm mode, and orientation, benefiting from refined mesoscale wind analysis. …”
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Global and China trends and forecasts of disease burden for female lung Cancer from 1990 to 2021: a study based on the global burden of disease 2021 database by Bilu Li, Yuyan Wu, Yanhong Zhang, Chengyun Hu, Xue Li, Shanshan Luo, Chenyu Sun, Iyad Yousef, Yefei Wang, Chaoliang Tang

“…Objective To conduct an in-depth analysis of the trends in disease burden for female lung cancer in China and globally from 1990 to 2021 and to forecast the next 15 years (2022–2037). …”
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ADVANCED NEURAL NETWORKS AND DEEP LEARNING TECHNIQUES IN FINANCIAL MARKET PREDICTION by ENE CEZAR CATALIN

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Demand unconstraining estimation based on big data warehouse in revenue management systems:framework and challenges by Peng GUO

Subjects: “…revenue management;demand forecasting;unconstraining estimation;data warehouse;big data;business intelligence;sentiment analysis…”
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A sentiment-driven three-stage approach for multi-scale carbon price prediction by Yongliang Liu, Chunling Tang, Aiying Zhou, Kai Yang, Huaiyu Yuan

Subjects: “…Carbon trading price forecasting…”
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EVALUATION OF MARKETING STRATEGIES OF FINANCIAL-CREDIT ORGANIZATION IN THE CONDITIONS OF ECONOMIC INSTABILITY by Vitaly Zhuravel, Rustam Ustaev, Natalia Kharchenko

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An Interpretive Structural Model of Factors Influencing Successful Sports Customer Relationship Management: Drivers of CRM within the sports industry by Sajjad Pashaie, Geoff Dickson, Monika Piątkowska, Hamed Golmohammadi

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DEVELOPMENT OF TECHNOLOGY OF THE ASSESSMENT OF STABILITY OF AN ENTERPRISE OF THE CHEMICAL COMPLEX by Mikhail N. Pavlenkov, Natalia A. Smirnova

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RESEARCH OF DEPENDENCE OF TAX REVENUES FROM GROSS REGIONAL PRODUCT PRODUCED IN ST. PETERSBURG by M. Y. Volokobinskiy, I. V. Razumova

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Advances in Traffic Congestion Prediction: An Overview of Emerging Techniques and Methods by Aristeidis Mystakidis, Paraskevas Koukaras, Christos Tjortjis

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A High-Granularity, Machine Learning Informed Spatial Predictive Model for Epidemic Monitoring: The Case of COVID-19 in Lombardy Region, Italy by Lorenzo Gianquintieri, Andrea Pagliosa, Rodolfo Bonora, Enrico Gianluca Caiani

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S&P-500 vs. Nasdaq-100 price movement prediction with LSTM for different daily periods by Xiang Zhang, Eugene Pinsky

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