Evaluating the impact of deep learning approaches on solar and photovoltaic power forecasting: A systematic review by Oussama Khouili, Mohamed Hanine, Mohamed Louzazni, Miguel Angel López Flores, Eduardo García Villena, Imran Ashraf

“…Accurate solar and photovoltaic (PV) power forecasting is essential for optimizing grid integration, managing energy storage, and maximizing the efficiency of solar power systems. …”
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Impact of Assimilating Microwave Radiance Data on Forecast of "23·7" Extreme Rainstorm in North China by Zhong Peiwen, Chen Yaodeng, Xie Yanhui, Chen Min, Fan Shuiyong, Li Juan

“…Physical mechanisms that enhance precipitation forecasts are further elucidated through diagnostic analysis. …”
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Estimating the Consumer Price Index using the lognormal diffusion process with exogenous factors: The Colombian case by Antonio Barrera, Arnold de la Peña Cuao, Juan José Serrano-Pérez, Francisco Torres-Ruiz

“…This new approach also gave rise to asking questions concerning impact analysis of economic shocks, and the search of possible scenarios for given CPI dynamics.…”
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Leveraging Real-Time Population-Scale GPS Data to Forecast and Identify Components of Epidemic Dynamics by Dr Alejandra Hidalgo, Dr Steven Schulz, Dr Ashish Thampi, Richard Pastor

“…Sensing real-time contact patterns is a representation of infection dynamics and therefore they are key to forecasting infection rates of SARS-CoV-2—in contrast to the retrospective nature of infection surveillance. …”
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Short-term Precipitation Forecast Correction in Beijing-Tianjin-Hebei Region Based on Deep Learning by Wang Yuhong, Kong Dexuan, Zhu Shoupeng, Zhang Nan, Ji Yan, Zhang Shan, Xu Huan

“…To enhance the quality of short-term precipitation forecast in Beijing-Tianjin-Hebei Region, a U-Net deep learning model is employed to correct short-term precipitation forecasts of 3-12 h based on the forecasting data of INCA (Integrated Nowcasting through Comprehensive Analysis) System and observation data of automatic weather stations during the flood season from 2022 to 2024. …”
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Epigenetic age and fertility timeline: testing an epigenetic clock to forecast in vitro fertilization success rate by Davide Marinello, Marco Reschini, Giorgia Di Stefano, Giorgia Carullo, Maíra Casalechi, Letizia Tarantini, Benedetta Albetti, Valentina Bollati, Paola Viganò, Edgardo Somigliana, Letizia Li Piani

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A novel machine learning models for meteorological drought forecasting in the semi-arid climate  region by Chaitanya Baliram Pande, Dinesh Kumar Vishwakarma, Aman Srivastava, Kanak N. Moharir, Fahad Alshehri, Norashidah Md Din, Lariyah Mohd Sidek, Bojan Đurin, Abebe Debele Tolche

“…The scarcity of historical data  impedes monitoring and forecasting regional droughts. Given the limited studies on ensemble and Machine Learning (ML) models for drought forecasting, this research compares five ML models [Robust Linear Regression, Bagged Trees, Boosted Trees, Support Vector Machine (SVM), and Matern Gaussian Process Regression (GPR)] to determine superior accuracy in the regional context. …”
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Explainable forecasting of air quality index using a hybrid random forest and ARIMA model by Anuradha Yenkikar, Ved Prakash Mishra, Manish Bali, Tabassum Ara

“…This research contributes a replicable, explainable, and efficient AQI forecasting framework suited for deployment in resource-constrained urban environments. …”
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ANALYSIS AND PERSPECTIVES OF PRIVATE POSTAL AND COURIER SERVICES IN ROMANIA DURING 2009-2015 by Silviu Dorin GEORGESCU, Adrian BUDICĂ

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Econometric Analysis of the Effectiveness of Government Incentive Measures for the Development of the Region by I. V. Tregub, M. Iaco

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A Comprehensive Analysis of Imbalance Signal Prediction in the Japanese Electricity Market Using Machine Learning Techniques by Kaiyao Jiang, Yuji Yamada

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Comparative Performance of Autoencoders and Traditional Machine Learning Algorithms in Clinical Data Analysis for Predicting Post-Staged GKRS Tumor Dynamics by Simona Ruxandra Volovăț, Tudor Ovidiu Popa, Dragoș Rusu, Lăcrămioara Ochiuz, Decebal Vasincu, Maricel Agop, Călin Gheorghe Buzea, Cristian Constantin Volovăț

“…<b>Methods:</b> This retrospective analysis utilized clinical data from 77 patients treated at the “Prof. …”
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From macro to micro: Enhancing real GDP predictions through business tendency and bank loans surveys by Oguzhan Cepni, Furkan Emirmahmutoglu

Subjects: “…Macroeconomic forecasting…”
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Evaluation of the communication efficacy of main-stream-value-oriented TV using social media analysis: A method based on improved Bass models by Xiao Ding, Man Jin, Zhe Feng

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The Impact of the COVID-19 Pandemic on the Dynamics of Development of Construction Companies and the Primary Housing Market: Assessment of the Damage Caused, Current State, Forecas... by Burhan Reshat Rexhepi, Labeat Mustafa, Mejreme Krasniqi Sadiku, Burim Isa Berisha, Sedat Ukshin Ahmeti, Orhan Reshat Rexhepi

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The Burden of Peripheral Artery Disease in China From 1990 to 2019 and Forecasts for 2030: Findings From the Global Burden of Disease Study 2019 by Ye Hu, Ye Hu, Jiyue Gao, Jiyue Gao, Qiping Zhuo, Qiping Zhuo, Huixin Liu, Meiling Wang, Meiling Wang, Nina Jiang, Nina Jiang, Xueqing Wang, Xueqing Wang, Kainan Wang, Kainan Wang, Zuowei Zhao, Zuowei Zhao, Man Li, Man Li

“…Trends in incidence, mortality and DALYs were forecasted by Bayesian age-period-cohort (BAPC) analysis.ResultsIn 2019, the number of new cases and prevalence of PAD in China accounted for nearly a quarter of the global proportion. …”
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Global burden of alcoholic cardiomyopathy in middle-aged men (1990–2021) and projections to 2050: a systematic analysis of the Global Burden of Disease 2021 data by Yaqing Zhou, Tao Liu, Yao Meng, Zhenjun Ji, Zhongpu Chen, Genshan Ma

“…Additionally, we projected future trends until 2050 using time-series forecasting models.MethodsWe extracted ACM-related mortality, disability-adjusted life years (DALYs), years lived with disability (YLDs), and years of life lost (YLLs) from the GBD 2021 dataset across 204 countries and territories. …”
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Research and Application of Data-driven Forecast Method for Water Level Increment of Small and Medium-sized Rivers by DING Wu, LIN Hanxiong, WANG Hangang, ZHANG Wei, YANG Bin

“…Focusing on the forecast of flash flood disasters in small and medium-sized rivers,this paper adopts three data-driven forecast models to forecast the maximum water level increment.With Paitan Town,Zengcheng District,Guangzhou City as the research area,the mathematical modeling and accuracy evaluation of the three models are carried out.The analysis shows that the forecast accuracy of machine learning is the highest,but the forecast results are not interpretable.The forecast accuracy of the similarity analysis model is medium,and the prediction results have good cognition and interpretability.The overall prediction accuracy of the “rainfall-water level increment” relationship model is the lowest,but its operation is simple.The calculation of the similarity analysis model and machine learning model is relatively complex,relying on computer-aided calculation,and the results of the “rainfall-water level increment” relationship model can be plotted as graphs.Considering the forecast accuracy and convenience,multiple models such as the machine learning model and similarity analysis model can be applied for the forecast to improve the forecast accuracy if there is support from auxiliary equipment such as computers and mobile phone applications.Without support from computers and other basic equipment,the “rainfall-water level increment” relationship model can provide a convenient forecast method for flash flood forecast and early warning in small and medium-sized rivers.…”
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[Horizon Scanning Of Therapeutic Alternatives For Generalized Myasthenia Gravis And Five-Year Healthcare Expenditure Forecast Model] by Silvia Adami, Paolo Emilio Alboni, Adriano Cristinziano, Concetta La Seta, Andrea Marinozzi, Emanuele Colalillo, Rossella Bitonti

“…OBJECTIVE: The objective of the analysis was to assess and quantify the economic impact of generalized Myasthenia Gravis (gMG) in Italy over the next five years (2025—2029) using Horizon Scanning and expenditure forecasting methodologies. …”
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Forecasting Crude Oil Price and Stock Price by Jump Stochastic Time Effective Neural Network Model by Jun Wang, Huopo Pan, Fajiang Liu

“…Moreover, the correlation properties are studied by the detrended fluctuation analysis, and the results illustrate that there are positive correlations both in the absolute returns of actual data and predictive data.…”
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