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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Prognostic factors for tuberculosis development in children with latent tuberculous infection by N. V. Korneva, A. A. Starshinova, S. M. Аnaniev, Yu. E. Ovchinnikova, I. F. Dovgalyuk

“…Goal of the study: to detect specific immune response in children with latent tuberculous infection and define factors to forecast the development of the active disease in this group.Materials and methods. …”
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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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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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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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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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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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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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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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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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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

“…Bias correction is implemented using the static bias correction method developed by Harris and Kelly, which addresses both scan-dependent bias and air mass bias. …”
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An adaptive prediction method for ultra-short-term generation power of power system based on the improved long- and short-term memory network of sparrow algorithm by Peipei Yang, Zhidong Chen, Wen Tang, Zongyang Liu, Bingrui He

“…Abstract To achieve adaptive and accurate ultra-short-term power generation forecasting in power systems, this study proposes a novel prediction method combining Sparrow Search Algorithm (SSA) with Long Short-Term Memory (LSTM) networks. …”
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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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A Novel Monitoring Method of Wind-Induced Vibration and Stability of Long-Span Bridges Based on Permanent Scatterer Interferometric Synthetic Aperture Radar Technology by Jiayue Ma, Xiaojun Xue, Guoliang Zhi, Haoyang Zheng, Hanqing Zhu

“…By leveraging the spatial accuracy and long-term monitoring capability of PS-InSAR, along with the time-series forecasting strength of ARMA models, the method enables data-driven analysis of bridge vibrations. …”
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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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Epizootiological and Epidemiological Situation on Leptospirosis in the Russian Federation over the Period of 2013–2022 and the Forecast for 2023 by D. V. Trankvilevsky, E. Yu. Kiseleva, V. M. Korzun, N. V. Breneva, Yu. A. Verzhutskaya, I. D. Zarva, O. N. Skudareva, S. V. Balakhonov

“…When studying the material from small mammals using bacteriological, immunological and molecular-biological methods, Leptospira circulation was detected in 52 entities of the Russian Federation, in all federal districts. …”
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The burden of attention deficit hyperactivity disorder and incidence rate forecast in China from 1990 to 2021 by Ningyu Li, Ningyu Li, Junqiang Zhao, Junqiang Zhao, Junqiang Zhao, Junqiang Zhao, Fujun Zhou

“…ObjectiveTo analyze the temporal trends and future projections of attention-deficit/hyperactivity disorder (ADHD) burden among children and adolescents in China from 1990 to 2021, and to identify age-, period-, and cohort-specific drivers of disease progression.MethodsUsing data from the Global Burden of Disease Study 2021, we conducted joinpoint regression to detect trend transitions in ADHD incidence and age-standardized rates. …”
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A Consistency-Aware Hybrid Static–Dynamic Multivariate Network for Forecasting Industrial Key Performance Indicators by Jiahui Long, Xiang Jia, Bingyi Li, Lin Zhu, Miao Wang

“…Extensive experiments on both synthetic and real-world radar detection datasets demonstrated that CHSDM-Net achieved significant improvements compared with existing methods. …”
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