Medical and psychological predictors of prodromal period of repeated episode of major depressive disorder by V. V. Chugunov, E. N. Kireeva

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ANALISIS PRAKIRAAN PRODUKSI DAN KONSUMSI BERAS INDONESIA by Apri Andani

“…To answer this aim, then it was carried out by the analysis of the forecast by using the method of Box-Jenkins with the model of ARIMA. …”
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Identifying key drivers affecting the future of virtual reality in medical education by Zeinab Mohammadi, Rita Mojtahedzadeh, Arash Najimi, Maryam Alizadeh, Aeen Mohammadi

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Prospects for the pink salmon fishery in the Russian waters of the Bering and Okhotsk Seas in 2024 based on the analysis of the juveniles trawl surveys aboard RV TINRO and RV Profe... by A. A. Somov, E. A. Shevlyakov, A. N. Starovoitov, V. A. Shevlyakov, N. A. Dederer, I. V. Melnikov

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COMPARISON IN PREDICTING THE SHORT-TERM USING THE SARIMA, DSARIMA AND TSARIMA METHODS by Muhammad Giovani, Indira Anggriani, Syalam Ali Wira Dinata Simatupang

“…In the face of a change for the better in the future, a careful analysis and design of a data processing system is needed, in which a predictive framework can formulate the right policy to be one of the efforts to make a good decision. …”
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Sustainable Mobility and Emissions: The Role of the Sale Structure in the Automotive Energy Transition by Olga Orynycz, Ondrej Stopka, Anna Borucka, Ewa Kulesza, Jerzy Merkisz, Petr Kolařík

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Federated Learning Enhanced MLP–LSTM Modeling in an Integrated Deep Learning Pipeline for Stock Market Prediction by Jayaraman Kumarappan, Elakkiya Rajasekar, Subramaniyaswamy Vairavasundaram, Ketan Kotecha, Ambarish Kulkarni

Subjects: “…Stock market now casting and forecasting…”
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Geomorphological and Isotope-Geochemical Methods in Assessing the Gas Potential of a Territory (Using the Example of the Angara-Lena Oil and Gas Region) by Smirnov Aleksandr Sergeevich, Nourgaliev Danis, Chernova Inna Yur'evna, Ziganshin Eduard

Subjects: “…gas potential forecasting…”
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Macroeconomic Modeling in Post-pandemic Times by Anton I. Votinov1, Julia A. Polshchikova, Karen A. Nersisyan

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Instantaneous 2D extreme wind speed prediction using the novel Wind Gust Prediction Net based on purely convolutional neural mechanism by Zeguo Zhang, Jianchuan Yin

Subjects: “…Spatial–temporal wind gust forecasting…”
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Review of modern models and methods of analysis of time series of dynamics of processes in social, economic and socio-technical systems by E. G. Andrianova, S. A. Golovin, S. V. Zykov, S. A. Lesko, E. R. Chukalina

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STEPNet: A Spatial and Temporal Encoding Pipeline to Handle Temporal Heterogeneity in Climate Modeling Using AI: A Use Case of Sea Ice Forecasting by Sizhe Wang, Wenwen Li, Chia-Yu Hsu

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Optimizing Smart Grid Load Forecasting via a Hybrid Long Short-Term Memory-XGBoost Framework: Enhancing Accuracy, Robustness, and Energy Management by Falah Dakheel, Mesut Çevik

“…The results extend the literature on the development of fusion-based machine learning models for time series forecasting, and the future work of energy consumption analysis, anomaly detection, and resource allocation in SM grids.…”
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Chiller power consumption forecasting for commercial building based on hybrid convolution neural networks-long short-term memory model with barnacles mating optimizer by Mohd Herwan Sulaiman, Zuriani Mustaffa

“…Despite advances in deep learning, existing forecasting models often struggle with the complex temporal dependencies and non-linear patterns in chiller operation data. …”
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Forecasting and optimization of the kilovoltage X-ray therapy office within the framework of clinical guidelines of the Association of oncologists of Russia (AOR) of the Ministry o... by L. N. Izurov, J. A. Zuenkova

“…The results were evaluated using correlation analysis. In order to forecast the use of material and human resources, an economic method of mathematical modeling was used. …”
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A comparative study of multivariate CNN, BiLSTM and hybrid CNN–BiLSTM models for forecasting foreign exchange rate using deep learning by Elysee Nsengiyumva, Joseph K. Mung’atu, Charles Ruranga

“…These results highlight its superior accuracy and potential for future enhancements in foreign exchange forecasting.…”
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University proceedings. Volga region. Technical sciences by A.V. Kostin, P.P. Makarychev

“…The purpose of the study, the results of which are presented in the article, is to develop non-parametric regression models for the analysis and forecasting of fires, tragic events on the water, accidents on water pipes, road traffic accidents in the region. …”

Forecasting the long-term impacts of land use and cover changes on runoff coefficient and flood hydrograph: a case study of the Upper Citanduy Basin, Indonesia by Pengki Irawan, Junaedi Setiawan

“…Land use and land cover (LULC) change significantly affects hydrological processes in ungauged basins, where data limitations hinder accurate analysis and modeling. This study assesses the long-term impacts of LULC changes on the runoff coefficient (RC) and flood hydrograph in the Upper Citanduy Basin, Indonesia, using data from 2014, 2019, and 2024 to project future scenarios through 2029. …”
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A Hybrid Methodology Using Machine Learning Techniques and Feature Engineering Applied to Time Series for Medium- and Long-Term Energy Market Price Forecasting by Flávia Pessoa Monteiro, Suzane Monteiro, Carlos Rodrigues, Josivan Reis, Ubiratan Bezerra, Maria Emília Tostes, Frederico A. F. Almeida

“…In the electricity market, the issue of contract negotiation prices between generators/traders and buyers is of particular relevance, as an accurate contract modeling leads to increased financial returns and business sustainability for the various participating agents, encouraging investments in specialized sectors for price forecasting and risk analysis. This paper presents a methodology applied in experiments on energy forward curve scenarios using a set of techniques, including Long Short-Term Memory (LSTM), Extreme Gradient Boosting (XGBoost), Seasonal AutoRegressive Integrated Moving Average with eXogenous regressors (SARIMAX), and Feature Engineering to generate a 10-year projection of the Conventional Long-Term Price. …”
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Evaluating the Performance of SWAN model in forecasting storm surges over the Persian Gulf and Oman Sea in a case study (June 7-10, 2023) by Zahra Ghassabi, Sara Karami, Behzad Layeghi

“…The results showed that at sometimes, the pattern of the significant wave height (Hs) in the output of the SWAN model using ERA5 data and the forecast of the WRF model are somewhat similar, but in the forecast, the Hs in the Strait of Hormuz and its surroundings has been overestimated in many cases. …”
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