Digital Assets and the Global Economy: How the Use of Statistical Models Can Help Bitcoin Price Prediction by L. P. Bakumenko, N. S. Vasileva

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Reservoir identification of marine facies carbonate shoals in the Middle Permian in the Sichuan Basin by Yunbo Zhang, Yan Feng, Miao Miao, Xingying Yu, Xufeng Liu, Mingjian Wang, Li Sun

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An Optimized Forecasting Approach Based on Grey Theory and Cuckoo Search Algorithm: A Case Study for Electricity Consumption in New South Wales by Ping Jiang, Qingping Zhou, Haiyan Jiang, Yao Dong

“…This study proposes a hybrid model, which includes data selection, an abnormality analysis, a feasibility test, and an optimized grey model to forecast electricity consumption. …”
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Assessment of a New Global Ocean Reanalysis in ENSO Predictions With NOAA UFS by Jieshun Zhu, Wanqiu Wang, Arun Kumar, Yanyun Liu, David DeWitt

“…The effect of ocean initializations is further confirmed by the superiority of GLORe over CFSR as validated against an objective analysis.…”
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Bitcoin Price Regime Shifts: A Bayesian MCMC and Hidden Markov Model Analysis of Macroeconomic Influence by Vaiva Pakštaitė, Ernestas Filatovas, Mindaugas Juodis, Remigijus Paulavičius

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Prediction of fire danger index using a new machine learning based method to enhance power system resiliency against wildfires by Tan Nhat Pham, Rakibuzzaman Shah, Nima Amjady, Syed Islam

“…To do this, first, a volatility analysis approach is presented to analyse the volatility level of the time series data of a fire danger index. …”
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A novel gene signature for forecasting time to next relapse in multiple sclerosis using peripheral blood mononuclear cells by Huimin Zhang, Jiahui Yang, Xiaobo Zhang, Chaoyi Wu, Zhen Zhao, Ming Yang, Zhaoping Wu

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Assessing and forecasting the efficiency of Russian banks (2000–2026): A DEA, panel data, and Monte Carlo simulation approach by Jalal Abu-Alrop

“…This study aims to evaluate the efficiency of Russian banks, identify the factors influencing it based on their size and ownership type, and forecast future trends in the banking sector. The analysis utilized data from 680 Russian banks over the period 2000–2023, employing Data Envelopment Analysis (DEA) to measure technical efficiency, panel data analysis to determine efficiency-related variables, and Monte Carlo simulation to predict future performance for the years 2024–2026. …”
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Extreme forecasting for universal control fuel pump and gas turbine engine in service obtaining for a long time trials by Elena V. Shendaleva

“…The subject matter of this article is the analysis of extreme forecasting method application for providing the assured forecasting of fuel pump technical state. …”
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An Ensemble Learning Method for the Kernel-Based Nonlinear Multivariate Grey Model and its Application in Forecasting Greenhouse Gas Emissions by Lan Wang, Nan Li, Ming Xie

“…In boosting scheme, the KGM (1, N) is used as a base learner, and the use of early stopping method avoids overfitting the training dataset. The empirical analysis of forecasting GHG emissions in 27 European countries for the period 2015–2019 is carried out. …”
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Machine-learning derived identification of prognostic signature to forecast head and neck squamous cell carcinoma prognosis and drug response by Sha-Zhou Li, Hai-Ying Sun, Yuan Tian, Liu-Qing Zhou, Tao Zhou

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THE USE OF FORECASTING METHODS FOR DETERMINING THE MAIN TRENDS IN THE DEVELOPMENT OF PROFESSIONAL TRAINING SYSTEMS FOR SECOND LANGUAGE TEACHERS OF ROMANIA AND UKRAINE by Korolova Larysa

“…The article claims that thanks to the use of a comparative analysis, a systematic approach, the methodology of scenario forecasting and conducting an expert assessment during the research, three ways of developing the trends of higher education in Romania and Ukraine in the field of professional training of foreign language teachers were determined and they were formed in three scenarios: optimistic, neutral and pessimistic. …”
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Big data-driven corporate financial forecasting and decision support: a study of CNN-LSTM machine learning models by Aixiang Yang

“…A practical enterprise case analysis further confirms the model’s effectiveness in improving financial forecasting accuracy, optimizing decision-making, and mitigating financial risks. …”
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Migrative armadillo optimization enabled a one-dimensional quantum convolutional neural network for supply chain demand forecasting. by Mohamed Irhuma, Ahmad Alzubi, Tolga Öz, Kolawole Iyiola

“…Demand forecasting is a quite challenging task, which is sensitive to several factors such as endogenous and exogenous parameters. …”
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Optimized Demand Forecasting for Bike-Sharing Stations Through Multi-Method Fusion and Gated Graph Convolutional Neural Networks by Hebin Guo, Kexin Li, Yutong Rou

“…This study presents an innovative approach to hourly demand forecasting for bike-sharing systems using a multi-attribute, edge-weighted, Gated Graph Convolutional Network (GGCN). …”
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Development and validation of nomograms to forecast overall survival and cancer-specific survival in Asian patients diagnosed with epithelial ovarian cancer by Hao He, Xin Cheng, Mengna Zhao, Shimeng Wan, Shijie Yao, Hongbing Cai

“…The calibration plots showed that the nomogram forecasts and actual survival results agreed. Additionally, the decision curve analysis curves indicated that the nomogram outperformed the American Joint Commission on Cancer staging system in terms of predictive accuracy.ConclusionNomograms and a risk classification system were created to forecast the overall survival and cancer-specific survival of Asian females with ovarian cancer. …”
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NOSOLOGICAL STRUCTURE OF ACUTE CORONARY EVENTS AT ADMISSION AND AT DISCHARGE, PATIENT COMPLIANCE AND NEAREST FORECAST (DATA OF THE RACSMI-UZ REGISTER) by G. A. Nagaeva

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Exploring current trends in agricultural commodities forecasting methods through text mining: Developments in statistical and artificial intelligence methods by Luana Gonçalves Guindani, Gilson Adamczuk Oliveirai, Matheus Henrique Dal Molin Ribeiro, Gabriel Villarrubia Gonzalez, José Donizetti de Lima

“…To address these challenges, mathematical models have been developed for forecasting crucial variables in managing agribusiness activities. …”
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Forecasting the daily evaporation by coupling the ensemble deep learning models with meta-heuristic algorithms and data pre-processing in dryland by Tonglin Fu, Dong Wang, Jing Jin

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Technical and Economic Forecast in Selection of Optimum Biomass and Local Fossil Fuel Application Technology for Thermal Electric Energy Generation by I. A. Bokun, S. S. Severina

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