Addressing the training gaps for ASD specialists in Kazakhstan: A forecast-based approach by Ainagul Rymkhanova, Saltanat Mulikova, Alfina Sakayeva, Zhanar Akhmetzhanova, Sara Zhanibekova, Assem Bekmaganbetova

“…Additionally, mathematical modeling and forecasting methods were employed to predict the increase in the number of children with ASD, facilitating the development of targeted educational programs for training specialists at undergraduate and graduate levels and improving the qualifications of practicing professionals. …”
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An explainable Machine Learning model for Large-Scale Travelling Ionospheric Disturbances forecasting by Ventriglia Vincenzo, Guerra Marco, Cesaroni Claudio, Spogli Luca, Altadill David, Segarra Antoni, Galkin Ivan, Barta Veronika, Verhulst Tobias G.W., de Paula Víctor, Navas-Portella Víctor, Berényi Kitti A., Belehaki Anna

“…The validation procedure consists of a global-level evaluation and interpretation step, firstly, followed by an event-level validation against independent detection methods, which highlights the model’s predictive robustness and suggests its potential for real-time space weather forecasting. …”
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Probabilistic seasonal dengue forecasting in Vietnam: A modelling study using superensembles. by Felipe J Colón-González, Leonardo Soares Bastos, Barbara Hofmann, Alison Hopkin, Quillon Harpham, Tom Crocker, Rosanna Amato, Iacopo Ferrario, Francesca Moschini, Samuel James, Sajni Malde, Eleanor Ainscoe, Vu Sinh Nam, Dang Quang Tan, Nguyen Duc Khoa, Mark Harrison, Gina Tsarouchi, Darren Lumbroso, Oliver J Brady, Rachel Lowe

“…Moreover, the transition from theoretical to operational systems integrated with disease control activities is rare.<h4>Methods and findings</h4>We introduce an operational seasonal dengue forecasting system for Vietnam where Earth observations, seasonal climate forecasts, and lagged dengue cases are used to drive a superensemble of probabilistic dengue models to predict dengue risk up to 6 months ahead. …”
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Forecasting the number of identified information security vulnerabilities based on the theory of “Gray Systems” by A. O. Efimov, S. A. Mishin, E. A. Rogozin

“…The results of the study indicate the possibility of applying the theory of “gray systems” for short-term forecasting of the number of detected vulnerabilities. …”
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Empirical prediction intervals applied to short term mortality forecasts and excess deaths by Ricarda Duerst, Jonas Schöley

“…Methods Using weekly death data from the Short-term Mortality Database (STMF) for 23 countries, we propose empirical prediction intervals based on the distribution of past out-of-sample forecasting errors for the study of weekly expected and excess deaths. …”
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A Hybrid ARIMA-LSTM-XGBoost Model with Linear Regression Stacking for Transformer Oil Temperature Prediction by Xuemin Huang, Xiaoliang Zhuang, Fangyuan Tian, Zheng Niu, Yujie Chen, Qian Zhou, Chao Yuan

“…The predictions of these three models are combined through a linear-regression stacking approach, improving accuracy and simplifying the model structure. This hybrid method outperforms traditional models, offering superior performance in predicting transformer oil temperature, which enhances fault detection and transformer reliability. …”
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On the Prediction and Forecasting of PMs and Air Pollution: An Application of Deep Hybrid AI-Based Models by Youness El Mghouchi, Mihaela Tinca Udristioiu

“…The GEO-based feature selection method effectively identified the most relevant predictors, while the Deep-NARMAX model captured temporal dynamics for accurate forecasting. …”
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ANNUAL FORECAST IN PATIENTS WITH ACUTE ISCHEMIC STROKE: ROLE OF PATHOLOGICAL ANKLE-BRACHIAL INDEX by A. N. Sumin, J. A. Kolmykova, I. N. Kukhareva, M. V. Ott, N. I. Vodopyanova, A. A. Morkvenas, O. A. Trubnikova, A. V. Kovalenko

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Multimodal Computational Approach for Forecasting Cardiovascular Aging Based on Immune and Clinical–Biochemical Parameters by Madina Suleimenova, Kuat Abzaliyev, Ainur Manapova, Madina Mansurova, Symbat Abzaliyeva, Saule Doskozhayeva, Akbota Bugibayeva, Almagul Kurmanova, Diana Sundetova, Merey Abdykassymova, Ulzhas Sagalbayeva

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Forecasting CO2 emissions in BRICS countries using the grey breakpoint prediction models by Huiping Wang, Xinge Guo

“…Finally, the novel grey breakpoint prediction models are used to simulate and forecast the CO2 emissions in BRICS countries. We can see that by setting time breakpoints and fuzzy breakpoint intervals, the novel methods successfully detect abrupt changes in the system and achieve accurate predictions, thus improving the accuracy and applicability of the grey model. …”
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Tools for forecasting regional economic growth using big data and business intelligence technologies by Afanasev Kirill, Kalinin Aleksandr

“…The significance of the study is due to the increasing complexity of regional economic growth forecasting in the context of digital transformation and the limitations of traditional analysis methods. …”
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CO-MORBIDITY AND FORECASTING THE RISK OF POST-OPERATIVE INFECTIOUS COMPLICATIONS IN TUBERCULOUS SPONDYLITIS PATIENTS by S. V. Burlakov, A. A. Vishnevskiy

“…Goal of the study: to study co-morbidity and risk of post-operative infectious complications in tuberculous spondylitis patients with concurrent non-specific spinal osteomyelitis as per ASA, PITSS scales and Charlson score.Materials and methods. Surgical treatment of 41 patients with infectious spondylitis was retrospectively analyzed. …”
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Lessons learned from the co-development of operational climate forecast services for vineyards management by N. Pérez-Zanón, V. Agudetse, E. Baulenas, P.A. Bretonnière, C. Delgado-Torres, N. González-Reviriego, A. Manrique-Suñén, A. Nicodemou, M. Olid, Ll. Palma, M. Terrado, B. Basile, F. Carteni, A. Dente, C. Ezquerra, F. Oldani, M. Otero, F. Santos-Alves, M. Torres, J. Valente, A. Soret

“…In the co-design phase, more intense engagement methods were implemented to communicate the capabilities of climate forecasts and design the product’s visualisation. …”
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Linking Critical Heights in Solar Active Regions with 3D Coronal Mass Ejection Speeds: Insights from Automated and Manual Polarity Inversion Line Detection Methods by Harshita Gandhi, Alexander W James, Huw Morgan, Lucie Green

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Ultra-Short-Term Wind Power Forecasting in Complex Terrain: A Physics-Based Approach by Dimitrios Michos, Francky Catthoor, Dimitris Foussekis, Andreas Kazantzidis

“…This paper proposes a method based on Computational Fluid Dynamics (CFD) and the detection of Wind Energy Extraction Latency for a given wind turbine (WT) designed for ultra-short-term (UST) wind energy forecasting over complex terrain. …”
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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

“…CMA-MESO model is utilized to investigate the impact of assimilating multi-source polar-orbiting satellite microwave radiance data on forecast of "23.7" severe rainstorm event in North China. …”
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Structural time series modelling for weekly forecasting of enterovirus outpatient, inpatient, and emergency department visits. by Cathy W S Chen, Leon L Hsieh, Betty X Y Chu

“…The study evaluates forecast accuracy using five key metrics and identifies significant surges in cases by detecting values that exceed the 95% prediction intervals, enhancing anomaly detection.…”
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Power distribution and forecasting using a probabilistic and systematic data processing model for renewable resources by Hammad Alnuman, Ghulam Abbas, Amr Yousef

“…Comparing PSPM to current methods, empirical data show that it improves forecast success rate by 20%, increases distribution efficiency by 25%, and reduces analytical latency by 35%. …”
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Scientific geovisualization of the dynamics of Sargassum dispersion and landfall in the Caribbean, based on satellite imagery and numerical forecasts. by Francisco Javier Osorno-Covarrubias, Jorge Prado Molina, Gabriela Gómez-Rodríguez, Uriel Mendoza, Stéphane Couturier

“…An automated prototype is developed incorporating the following components: 1) Detection of Sargassum Rafts: Individual sargassum rafts are identified using Sentinel-2 images with a revisiting period of five days. 2) Forecasting/Hindcasting Vector Fields: One-week forecasts (or hindcasts) are obtained at hourly intervals for the primary forces affecting raft movement—currents, tides, waves, and wind—using supercomputing services (Copernicus Marine Service) 3) Lagrangian Simulation: The movement of detected rafts in step 1 is simulated using the vector fields obtained in step 2. …”
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Enhanced Wind Power Forecasting Using Graph Convolutional Networks with Ramp Characterization and Error Correction by Xin He, Yichen Ma, Jiancang Xie, Gang Zhang, Tuo Xie

“…Experiments conducted on wind power data from a Belgian wind farm show that the proposed method significantly improves prediction stability and accuracy during ramp events, achieving an approximate 28% improvement compared to conventional models, and demonstrates strong multi-step forecasting capability.…”
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