HARMONIZATION OF HISTORICAL DATA AND EXPERT MODELS FOR FORECASTING DEMAND FOR RAIL TRANSPORTATION by A. Zamkovoy, S. Kudiyarov, R. Martyshkin, V. Strizhov

“…The problem of rail freight traffic volume forecasts using retrospective data, analysis of the impact of external factors on the cargo base and the distribution of goods shipments by transport mode is solved. …”
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Introducing ProsperNN—a Python package for forecasting with neural networks by Nico Beck, Julia Schemm, Claudia Ehrig, Benedikt Sonnleitner, Ursula Neumann, Hans Georg Zimmermann

“…We present the package prosper_nn, that provides four neural network architectures dedicated to time series forecasting, implemented in PyTorch. In addition, prosper_nn contains the first sensitivity analysis suitable for recurrent neural networks (RNN) and a heatmap to visualize forecasting uncertainty, which was previously only available in Java. …”
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Automatic control of air temperature in the greenhouse considering the weather forecast data by A. G. Senkov

“…Theoretical mathematical expressions for the regulation algorithm and analysis of regulation quality are obtained and the results of numerical modeling of the temperature control process are presented. …”
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Forecasting of an arterial hypertensia at women depending on age and character of labor activity by G. V. Artamonova, S. A. Maksimov, Ye. V. Indukayeva, E. B. Shapovalova, S. A. Makarov, O. A. Ivanova, M. Yu. Ogarkov, A. Ye. Skripchenko

“…The analysis of possibilities of forecasting of an arterial hypertensia depending on age and character of professional work of 607 women of mass trades is carried out. …”
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DIGITALIZATION, FINANCIAL INSOLVENCY AND BANKRUPTCY RISK FORECASTING OF BULGARIAN AGRICULTURAL ENTERPRISES by Rumyana ANGELOVA, Dimitrina STOYANCHEVA

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ASSESSMENT AND RELATIONSHIPS BETWEEN PHYSICAL AND ECONOMIC ACCESSIBILITY OF FOOD: STATUS AND FORECAST by Elena DERUNOVA, Natal’ya KIREEVA, Olesya PRUSCHAK

“…Based on the regression analysis, factors determining the physical and economic accessibility of food have been identified. …”
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Short-Term Load Forecasting Based on Feature Selection and Combination Model by Yusong XU, Shanhua ZOU, Xianling LU

“…Finally, a neural network is set up for experimental analysis. The simulation results show that the proposed combination model has a great high forecasting accuracy and robustness.…”
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Hybrid Human and Machine Learning Algorithms to Forecast the European Stock Market by Germán G. Creamer, Yasuaki Sakamoto, Jeffrey V. Nickerson, Yong Ren

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Theoretical Solutions for Forecasting the Response of the Existing Pipeline Induce by Tunneling underneath by Yao Rong, Guohui Feng, Yang Sun, Yujie Li, Guanyu Chen, Haibin Ding, Changjie Xu

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FORECASTING THE VALUE OF THE EXPORT OF UKRAINIAN AGRICULTURAL PRODUCTS BASED ON FUZZY SETS by Olesia TOTSKA

“…Ukraine’s acquisition of the status of a candidate for EU membership and the desire to take a worthy position in the global agro-food markets necessitates a permanent monitoring and forecasting of the value of Ukrainian exports of agricultural products. …”
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GLACIERS IN THE MEYNYPILGYNSKY RANGE: CURRENT STATE AND DEVELOPMENT FORECAST OF GLACIER SYSTEMS by M. D. Ananicheva, G. A. Kapustin, A. Yu. Mikhailov

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Application of the ARIMA-GARCH Model for Forecasting Indonesia's Monthly Inflation Rate by Anisa, Ira Yudistira, Tony Yulianto

“…Inflation data will be modeled using the ARIMA model and then continued by modeling the residuals using the GARCH model if heteroscedasticity occurs in the ARIMA model residuals. Based on data analysis that has been done, the best model for inflation forecasting cases in Indonesia is the ARIMA (2,0,2) - GARCH (0,1) model with a MAPE value of 17.78%.…”
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Forecast Model of TV Show Rating Based on Convolutional Neural Network by Lingfeng Wang

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Federated Learning-Based Load Forecasting for Energy Aggregation Service Providers by HUANG Yichuan, SONG Yuhui, JING Zhaoxia

“…The results of a case analysis using actual data from a large energy aggregation service provider in a southern city in China demonstrate that the proposed model significantly improves operational efficiency and forecasting accuracy.…”
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Numerical Studies on Forecast Error Correction of GRAPES Model with Variational Approach by Dengxin He, Zhimin Zhou, Zhaoping Kang, Lin Liu

“…According to the hindcast daily data of geopotential height on 500 hPa generated by GRAPES model on January and July from 2002 to 2010, preliminary analysis is carried out on characteristics of forecast error in East Asia. …”
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A Methodology for Electricity Demand Forecasting Using a Hybrid Approach by Fanidhar Dewangan, Monalisa Biswal, Nand Kishor

“…Load forecasting (LF) plays a crucial role in energy production planning and scheduling, simplifying budgeting processes, and improving power supply reliability. …”
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An Optimized Power Load Forecasting Algorithm Based on VMD‐SMA‐LSTM by Wei Liu, Fan Hua, Yongping Cui, Yangchao Xu, Han Liu

“…ABSTRACT Accurate load forecasting can scientifically guide the optimal operation and scheduling of urban power grids. …”
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Impact of two high resolution altimetry mission concepts on ocean forecasting by Mounir Benkiran, Pierre-Yves Le Traon, Pierre-Yves Le Traon, Elisabeth Rémy, Yann Drillet

“…These two configurations greatly improve ocean forecasting and monitoring capabilities. Compared to a constellation of three nadir altimeters (the present configuration), analysis and forecast errors are reduced by a factor of 2. …”
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Information and communication technologies in political crisis management: resilience, forecasting, and response by Evgeny N. Pashentsev, Yury Y. Kolotaev

“…Abstract This article explores the integration of information and communication technologies (ICT) in social and political crisis management, focusing on their role in forecasting and response. ICT applications, including predictive analytics, artificial intelligence, and blockchain, enhance situational awareness, decision-making, and systemic adaptability, offering new tools to address crises ranging from natural disasters to political unrest. …”
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Urban Parking Demand Forecasting Using xLSTM-Informer Model by Jimei Ma, Zhong Wang

“…Accurate parking demand forecasting plays a pivotal role in supporting intelligent traffic management, resource allocation, and the efficient operation of parking facilities. …”
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