Evaluation of Lightning Prediction by an Electrification and Discharge Model in Long-Term Forecasting Experiments by Liangtao Xu, Shuang Chen, Wen Yao

“…The predictability of the model was enhanced with increasing thunderstorm scale. …”
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Establishment of Fracture Prediction Model of Muti-point Incremental Forming on Sheet Material by XIAO Hong-li, CAI Gai-pin, QI Bu-chun, ZHOU Xiao-lei

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Solar Irradiance Prediction for Zaria Town Using Different Machine Learning Models by Ibrahim Abdulwahab, Sulaiman Haruna Sulaiman, Umar Musa, Ibrahim Abdullahi Shehu, Abdullahi Kakumi Musa, Ismaila Mahmud, Mohammed Musa, Abdullahi Abubakar, Abdulrahman Olaniyan

“…This is done in order to construct and develop a high-efficiency prediction model that uses actual meteorological data to predict daily solar irradiance for the town of Zaria, Nigeria. …”
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Evaluation of different erosion models for predicting guide vane wear in Francis turbine by Rakish Shrestha, Rakish Shrestha, Kushal Shrestha, Kushal Shrestha, Sailesh Chitrakar, Sailesh Chitrakar, Bhola Thapa, Hari Prasad Neopane, Zhongdong Qian, Zhiwei Guo

“…By dividing the CG into sections and comparing the erosion predictions by different erosion models with the actual erosion, Finnie erosion model is found to be the most suitable model for this application. …”
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Research on Financial Stock Market Prediction Based on the Hidden Quantum Markov Model by Xingyao Song, Wenyu Chen, Junyi Lu

“…The model was used to predict 15 stock indices from the Shanghai and Shenzhen Stock Exchanges between June 2018 and June 2021. …”
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Using the LARS-WG Model to Predict the Maximum Temperature in Zakho City, Iraq by Sura Abdulsahib, Salah Zubaidi, Nadheer Ayoob

“…The daily maximum temperatures are downscaled using the Long Ashton Research Station Weather Generator (LARS-WG) model based on the SSP585 scenario. Five General Circulation Models (GCMs) outputs are used for the selected period (2021-2040). …”
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Advanced air quality prediction using multimodal data and dynamic modeling techniques by Umesh Kumar Lilhore, Sarita Simaiya, Rajesh Kumar Singh, Abdullah M. Baqasah, Roobaea Alroobaea, Majed Alsafyani, Afnan Alhazmi, M. D. Monish Khan

“…The attention mechanism directs the model’s focus to the most informative features, improving predictive accuracy. …”
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Research on Deformation Prediction of Foundation Pit Based on PSO-GM-BP Model by Dongge Cui, Chuanqu Zhu, Qingfeng Li, Qiyun Huang, Qi Luo

“…The results show that both the GM (1, 1) and BP neural network models can predict accurate results. The prediction optimized by the particle swarm algorithm is more accurate and has more substantial applicability. …”
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Predicting oxytocin binding dynamics in receptor genetic variants through computational modeling by Preeti Dubey, Yingye Fang, K. Lionel Tukei, Shobhan Kuila, Xinming Liu, Annika Sahota, Antonina I. Frolova, Erin L. Reinl, Manasi Malik, Sarah K. England, Princess I. Imoukhuede

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An interpretable stacking ensemble model for high-entropy alloy mechanical property prediction by Songpeng Zhao, Zeyuan Li, Changshuai Yin, Zhaofu Zhang, Teng Long, Jingjing Yang, Ruyue Cao, Yuzheng Guo

“…The results demonstrate that the proposed stacking framework outperforms individual models in predicting yield strength and elongation, showing improved generalization ability and predictive accuracy.…”
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Study on factor-state artificial neural network model for water quality prediction by GUO Zong-lou, SHEN Wei

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Risk factors for infections in patients with lupus nephritis and construction of a prediction model by Liu Ding-lin, Zhang Wen-hao, Hu Hao-fei, Li Ai-ting, Chen Zhi-jin, Zheng Cai-yan, Qin Le-le, Zhang Li, Li Rui-zhao, Ye Zhi-ming

“…Cox proportional risk regression model was used to analyze the factors affecting secondary infections.ResultsThe mean age of the included patients was （30 ± 12）years， and 85.3% of them were female. …”
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Advancing Forex prediction through multimodal text-driven model and attention mechanisms by Fatima Dakalbab, Ayush Kumar, Manar Abu Talib, Qassim Nasir

“…This research work introduces a novel multimodal deep learning framework that integrates technical analysis and sentiment analysis through a cross-modal attention mechanism, enabling a comprehensive understanding of market dynamics. The proposed model leverages innovative alignment techniques to synchronize sentiment from news articles with historical price trends, facilitating robust multiclass prediction of Forex price directions. …”
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A Hybrid Prediction Model for Monitoring of River Water Quality in the USN System by Hoontae Kim, Minsoo Kim

“…Since the detection of each day's pattern takes some time, we need to incorporate statistical regression model as an interim prediction method. Through an experiment that compares the hybrid model to previous statistical regression model, we have shown that our hybrid model is more accurate to predict the sensor's movement.…”
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A network security situation prediction method based on hidden Markov model by Xiong ZHAN, Hao GUO, Peng ZHANG, Shu MAO

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Comparison of Machine Learning and Deep Learning Models Performance in predicting wind energy by Saswati Rakshit, Anal Ranjan Sengupta

“…This study leverages advanced machine learning (ML) and some other statistical and deep learning based time series forecasting models to enhance the accuracy of wind energy predictions. …”
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Prediction of Precipitation in the Western Mountainous Regions of China Using a Statistical Model by Yijia Hu, Yuan Sun, Yao Ha, Yimin Zhu, Zhixian Luo

“…It has better skill in the prediction of WMR precipitation than the dynamical model SINTEX-F.…”
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Temperature Prediction for Aerospace Thermal Tests Based on Physical and LSTM Hybrid Model by Xinze Li, Chunjun Chen

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Postoperative hyperglycemia in patients with traumatic brain injury: development of a prediction model by Xiangyi Yin, Yi Xia, Liuyan Shen, Xiaowen Zhu, Lichun Lu, Xianlan Meng

“…For TBI patients with a total score ≥ 6 in the prediction model, early interventions and care are needed to reduce the postoperative hyperglycemia.…”
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Impact of a USMLE Step 2 Prediction Model on Medical Student Motivations by Anthony Shanks, Ben Steckler, Sarah Smith, Debra Rusk, Emily Walvoord, Erin Dafoe, Paul Wallach

“…The standard error of the prediction model was 7.6 with better accuracy for predicted scores greater than 230 (SE 8.1) as compared to less than 230 (SE 12.8). …”
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