Explaining When Deep Learning Models Are Better for Time Series Forecasting by Martín Solís, Luis-Alexander Calvo-Valverde

“…There is a gap of knowledge about the conditions that explain why a method has a better forecasting performance than another. Specifically, this research aims to find the factors that can influence deep learning models to work better with time series. …”
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Retail Sales Forecasting Using Deep Learning: Systematic Literature Review by Linda Eglite, Ilze Birzniece

“…This systematic literature review examines the deep learning (DL) models for retail sales forecast. The accuracy of a retail sales forecast is a prevalent force for uninterrupted business operations. …”
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Bicycle Traffic Flow Forecasting Methodology for Different Functional Zones of The City by Miglė Zabielaitė-Skirmantė, Marija Burinskienė

“…Existing bicycle traffic flow forecasting methodologies are characterised by complex calculations, specific software, and the need for abundant data. …”
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Emerging role of generative AI in renewable energy forecasting and system optimization by Erdiwansyah, Rizalman Mamat, Syafrizal, Mohd Fairusham Ghazali, Firdaus Basrawi, S.M. Rosdi

“…The rapid integration of renewable energy sources (RES) into modern power systems introduces significant challenges in forecasting accuracy, grid stability, and energy optimization. …”
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Runoff Generation Mechanisms of Flash Flood Forecasting in Guanshan River Basin by LI Miao, TANG Wen-jian, DONG Lin-yao, ZENG Yu-jie

“…[Objectives] This study aims to improve the accuracy and efficiency of flash flood forecasting in the Guanshan River Basin and other similar small mountainous watersheds frequently affected by flood disasters by analyzing the runoff generation mechanisms of flash floods. …”
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Forecasts Plus Assessments of Renewable Generation Performance, the Effect of Earth’s Geographic Location on Solar and Wind Generation by César Berna-Escriche, Lucas Álvarez-Piñeiro, David Blanco

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RESEARCH OF THE MAIN DIRECTIONS OF FORECASTING OF COST INDICATORS OF DEVELOPMENT OF AVIATION ENGINEERING by A. Zinchenko, N. Cherner, M. Bobrova

“…Authors have analysed features of cost forecasting on development of aviation engineering of new generation. …”
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Forecasting Macroeconomic Dynamics in Ukraine: The Impact of a Full-Scale War by Olena Dobrovolska, Olena Kolotilina, Mariia Ostapenko

“…The significance of this research lies in its focus on an economy facing severe wartime disruptions and providing crucial forecasts for recovery and policy planning. The study uses the ARIMA (Autoregressive Integrated Moving Average) model to analyse various economic indicators, including GDP, inflation, unemployment, public debt, foreign direct investment, and currency devaluation. …”
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Forecasting Models Based on Fuzzy Logic: An Application on International Coffee Prices by Chellai Fatih

“…Analysing and forecasting the dynamics of coffee prices is of great interest to producers, consumers, and other market actors in managing and making rational decisions. …”
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Future of Agrivoltaic projects: A review from the technological forecasting perspective by Leticia Pekk, Petar Sabev Varbanov, Ting Pan, Zoltan Weltsch, Bernadett Radli-Burjan, Andras Hary, Xue-Chao Wang

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Integrating environmental clustering to enhance epidemic forecasting with machine learning models by Yosra Didi, Ahlam Walha, Ali Wali

“…Our key contributions are threefold: (1) we analyse the relationship between environmental variables (temperature, humidity, and air quality) and COVID-19 trends across countries; (2) we propose a two-stage approach combining K-means clustering to group countries based on environmental conditions, followed by region-specific machine learning models using Support Vector Regression (SVR), Prophet, and Long Short-Term Memory (LSTM) networks for both univariate and multivariate time series forecasting; and (3) we demonstrate that LSTM significantly outperforms other models, achieving superior accuracy for 30-day COVID-19 case predictions. …”
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Forecasting Battery Cell Production in Europe: A Risk Assessment Model by Tim Wicke, Lukas Weymann, Christoph Neef, Jens Tübke

“…The proposed model combines an evaluation of industry announcements at the project level with a Monte Carlo simulation to translate the announced production projects into a European production capacity forecast. Therefore, the likelihood of implementation for individual projects is analysed within 11 topics (company, country and maturity related) and scenarios for future European production capacities are elaborated. …”
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Economic burden of breast cancer in India, 2000–2021 and forecast to 2030 by Rakesh N Pillai, Aleena Alex, Narassima M.S., Vivek Verma, Ajil Shaji, Keechilat Pavithran, D. K. Vijaykumar, Denny John

“…Using the fitted ARIMA model, prevalence rates were forecasted from 2022 to 2030, with 95% confidence intervals to capture prediction uncertainty. …”
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Dropsonde Data Impact on Rain Forecasts in Taiwan Under Southwesterly Flow Conditions with Observing System Simulation Experiments by Fang-Ching Chien, Yen-Chao Chiu

“…The inclusion of dropsonde DA in the T5D24 experiment further enhanced precipitation forecasting, aligning more closely with NR, particularly in southern Taiwan. …”
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New Challenges for Tropical Cyclone Track and Intensity Forecasting in Unfavorable External Environment in Western North Pacific. Part I. Formations South of 20° N by Russell L. Elsberry, Hsiao-Chung Tsai, Wen-Hsin Huang, Timothy P. Marchok

“…An early westward turn south of 20° N by Kong-Rey (23 W) leading to a long westward path along 17° N and then a poleward turn to strike Taiwan were all track forecasting challenges. Four-dimensional COAMPS-TC Dynamic Initialization analyses utilizing high-density Himawari-9 atmospheric motion vectors are proposed to better define the TC intensities, vortex structure, and unfavorable environment for diagnostic studies and as initial conditions for regional model predictions. …”
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Changes in Approaches to the Analysis and Forecasting of Domestic Mechanical Engineering within Manufacturing Industries by V. N. Borisov, Yu. V. Zinchenko

“…The following methods were applied in the study: a systems approach, functional, comparative economic, and statistical analyses, as well as the authors’ methodological developments.   …”
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USE OF TRADITIONAL KNOWLEDGE TO FORECAST FLOOD: EVIDENCE FROM RIVERINE FLOODPLAIN IN BANGLADESH by Md Sanaul Haque Mondal

“…The data from the questionnaire survey was assessed using descriptive and inferential statistical tests. Data analyses were performed in SPSS version 26. Respondents' awareness of TK to forecast floods in riverine contexts was classified into categories: weather phenomena, cloud formation, rainfall patterns, river behavior, and observing plants and animals’ behavior. …”
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Solar Power Generation Forecasting in Smart Cities and Explanation Based on Explainable AI by Ovanes Petrosian, Yuyi Zhang

“…The application of black-box models, namely ensemble and deep learning, has significantly advanced the effectiveness of solar power generation forecasting. However, these models lack explainability, which hinders comprehensive investigations into environmental influences. …”
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What Young E-Consumers Want? Forecasting Parcel Lockers Choice in Rome by Gabriele Iannaccone, Edoardo Marcucci, Valerio Gatta

“…Furthermore, this option enables consolidated shipping and reduced delivery trip costs. This paper analyses and compares consumer preferences for alternative collection strategies. …”
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Multiscale model for forecasting Sabin 2 vaccine virus household and community transmission. by Michael Famulare, Wesley Wong, Rashidul Haque, James A Platts-Mills, Parimalendu Saha, Asma B Aziz, Tahmina Ahmed, Md Ohedul Islam, Md Jashim Uddin, Ananda S Bandyopadhyay, Mohammed Yunus, Khalequ Zaman, Mami Taniuchi

“…We also show that assuming homogeneous contact rates (mass action), as is common of poliovirus forecast models, does not accurately represent the clinical trial and risks overestimating forecasted poliovirus outbreak probability. …”
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