A Hybrid Intelligent Model for Olympic Medal Prediction Based on Data-Intelligence Fusion by Ning Li, Junhao Li, Hejia Fang, Jian Wang, Qiao Yu, Yafei Shi

“…The model demonstrates strong accuracy with root mean square errors of 3.21 (gold) and 4.32 (total medals), and mean-relative errors of 17.6% and 8.04%. …”
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Combined Prediction Method of Short-Term Distance Headway Based on EB-GRA-TCN by Chun Wang, Weihua Zhang, Cong Wu, Heng Hu, Wenjia Zhu

“…Compared with the autoregressive integrated moving average (ARIMA), TCN, RNN, and long short-term memory (LSTM) models, the EB-GRA-TCN model achieved the best prediction accuracy. …”
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Applicability of machine learning models for drought prediction using SPI in Kalahandi, Odisha by AMIT PRASAD, R.K. SINGH, K V RAMANA RAO, C. K. SAXENA

“… This study assesses the performance of auto-regressive integrated moving average (ARIMA), artificial neural network (ANN), support vector machine (SVM) and extreme learning machine (ELM), in predicting meteorological drought with Standardized Precipitation Index (SPI-6 and SPI-12) for Kalahandi district, Odisha. …”
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Modeling and forecasting of TEC using subspace-based SSA-LRF-ANN model by J.R.K. Kumar Dabbakuti, Mallika Yarrakula, Dinesh Babu Vunnava, Gopi Krishna Popuri

“…The SSA–LRF–ANN model demonstrates superior accuracy compared with the SSA–LRF, Autoregressive Moving Average (ARMA), and Holt–Winter (HW) models, achieving a correlation of 0.99, a Mean Absolute Error (MAE) of 0.55 TECU, a Mean Absolute Percentage Error (MAPE) of 7.06%, and a Root Mean Square Error (RMSE) of 0.75 TECU. …”
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Multi-feature stock price prediction by LSTM networks based on VMD and TMFG by Zhixin Zhang, Qingyang Liu, Yanrong Hu, Hongjiu Liu

“…(sh600009), the VMD–TMFG–LSTM model achieves a 69.76% reduction in Root Mean Squared Error (RMSE), a 71.41% reduction in Mean Absolute Error (MAE), a 46.28% reduction in runtime, and an improvement of 0.2184 in R-squared (R2), indicating significantly higher prediction accuracy. …”
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Mortality Prediction in COVID-19 Using Time Series and Machine Learning Techniques by Tanzina Akter, Md. Farhad Hossain, Mohammad Safi Ullah, Rabeya Akter

“…The autoregressive integrated moving average (ARIMA) model with the lowest AIC value for each nation is found through time series analysis. …”
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Evaluation of Deformable Image Registration for Three-Dimensional Temporal Subtraction of Chest Computed Tomography Images by Ping Yan, Yoshie Kodera, Kazuhiro Shimamoto

“…When considering 3D landmark distance, the root-mean-square error changed from an average of 20.82 mm for Pfixed to Pmoving to 0.5 mm for Pwarped to Pfixed. …”
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Hybrid SARIMA+BO-LSTM Framework for Forecasting EV Adoption: A Road to Net-Zero in Ireland by Afaq Khattak, Brian Caulfield

“…The SARIMA-BO–LSTM model achieves a Mean Absolute Error (MAE) of 742.99, Root Mean Squared Error (RMSE) of 1200, and R2 of 0.93, outperforming several baseline statistical and machine learning models. …”
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The Practical Wisdom of Aristotle in the Era of Postmodernism (Managing China’s Sports Reform) by S. V. Altukhov

“…The economy is being actively taken root into the culture of consumption in the service industry. …”
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Time-Series analysis of short-term exposure to air pollutants and daily hospital admissions for stroke in Tabriz, Iran. by Shahryar Razzaghi, Saeid Mousavi, Mehran Jaberinezhad, Ali Farshbaf Khalili, Seyed Mahdi Banan Khojasteh

“…Autoregressive integrated moving average (ARIMA-X) model with 3 lag days was developed to assess the correlation.…”
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Optical Design Study with Uniform Field of View Regardless of Sensor Size for Terahertz System Applications by Jungjin Park, Jaemyung Ryu, Hojong Choi

“…A zoom optical system that changed the image height by fixing the angle of view and changed the focal length by moving the internal lens group was designed. THz waves exhibit minimal change in the refractive index depending on the wavelength. …”
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The Realization of a Three-Dimensional Temperature Measurement System with a Two-Dimensional Sensor Array and the Demonstration of the Deformation Effect of Gravity on the Heating... by Dogan Can Samuk, Oguzhan Cakir

“…Then, the fan heater was moved along the <i>y</i>-axis at intervals of 10 cm from 0 to 100 cm, and three-dimensional heating patterns were obtained for different fan voltages. …”
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Ground data analysis for PM2.5 Prediction using predictive modeling techniques by Elham Nourmohammad, Yousef Rashidi

“…The models were evaluated based on performance metrics such as Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and R² scores. …”
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A Spatial Long-Term Load Forecast Using a Multiple Delineated Machine Learning Approach by Terence Kibula Lukong, Derick Nganyu Tanyu, Yannick Nkongtchou, Thomas Tamo Tatietse, Detlef Schulz

“…However, conventional methods like multiple linear regression and autoregressive integrated moving average struggle to capture the complex spatiotemporal patterns in historical data. …”
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PREDIKSI KURS RUPIAH TERHADAP EURO DAN POUND MENGGUNAKAN ARIMA by Alfriando C Vean, Arita Witanti

“…Metode yang digunakan adalah Autoregressive Integrated Moving Average (ARIMA) yang cocok untuk memprediksi data berbentuk deret waktu. …”
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Calcium Route in the Plant and Blossom-End Rot Incidence by Md. Yamin Kabir, Juan Carlos Díaz-Pérez

“…Soil-available Ca²⁺, transported by water flow, enters the root apoplast through membrane channels and moves toward the xylem via apoplastic or symplastic routes. …”
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Bacterial Diversity in the Different Ecological Niches Related to the Yonghwasil Pond (Republic of Korea) by Myung Kyum Kim, Bong-Soon Lim, Chang Seok Lee, Sathiyaraj Srinivasan

“…Six samples from water, mud, and soil niches were assessed, specifically from lake water, bottom mud (sediment), and root-soil samples of Bulrush, wild rice, Reed, and Korean Willow. …”
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Improved forecasting of carbon dioxide emissions using a hybrid SSA ARIMA model based on annual time series data in Bahrain by Zahrah Fayez Althobaiti

“…Accordingly, we proposed a hybrid forecasting model that combines Singular Spectrum Analysis (SSA) and the Auto Regressive Integrated Moving Average (ARIMA) method. This hybrid model decomposes the annual CO₂ emissions time series into trend, periodic, and noise components using SSA, then applies ARIMA individually to each component. …”
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Flax Harvesting Technologies for Flax Harvesting Machines by V. G. Chernikov, R. A. Rostovtsev, V. Yu. Romanenko

“…For this purpose, a mechanism was created for moving the deseeder against the clamping conveyor, depending on the flax stem height l(t), centimeters.…”
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Short-term Power Load Forecasting for a 33/11 KV Sub-Station by Utilizing Attention-Based Hybrid Deep Learning Architectures by Mukkamala R.

“…The performance of these models measured using several key metrics, including Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and R-squared (R²). …”
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