Development and validation of a machine learning model for prediction of cephalic dystocia by Yumei Huang, Xuerong Ran, Xueyan Wang, Defang Wu, Zheng Yao, Jinguo Zhai

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Drought prediction based on an improved VMD-OS-QR-ELM model. by Yang Liu, Li Hu Wang, Li Bo Yang, Xue Mei Liu

“…To overcome the low accuracy, poor reliability, and delay in the current drought prediction models, we propose a new extreme learning machine (ELM) based on an improved variational mode decomposition (VMD). …”
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Design and development of an efficient RLNet prediction model for deepfake video detection by Varad Bhandarkawthekar, T. M. Navamani, Rishabh Sharma, K. Shyamala

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The Comparison of Grey System and the Verhulst Model for Rainfall and Water in Dam Prediction by Chalermchai Puripat, Sukuman Sarikavanij

“…A time series of data of rainfall in Thailand between the years 2005 and 2015 was employed to predict possible future rainfall based on Julong Deng’s grey systems theory and the grey Verhulst model to see which model can predict more accurately with uncertain and limited data. …”
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State of Charge Prediction for Electric Vehicles Based on Integrated Model Architecture by Min Wei, Yuhang Liu, Haojie Wang, Siquan Yuan, Jie Hu

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Analysis of Empirical Models for Predicting the Rupture Force in Four-Pile Caps by Raphael Saverio Spozito, André Luis Christoforo, Fernando Menezes de Almeida Filho, Rodrigo Gustavo Delalibera, Elvys Dias Reis, André Luís Lima Velame Branco

“…These experimental records are frequently utilized to evaluate analytical models focusing on less conservative than normative models to predict rupture force. …”
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A model of group mobility management based on user behavior prediction by Xiaoyong LIN, Yang YU, Zhengkun MI

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Data-driven intelligent productivity prediction model for horizontal fracture stimulation by Qian Li, Yiyong Sui, Mengying Luo, Bin Guan, Lu Liu, Yuan Zhao

“…Finally, during fracturing design, the optimal productivity prediction model was matched to each interval based on its characteristics to predict post-fracturing productivity. …”
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Application Of Machine Learning Models To Predict Warping Of Plastic Automotive Parts by Evandro Menezes de Souza Amarante, João Paulo Rios Brandão de Oliveira, Pedro Guilherme Carvalho de Souza Marconi, Armando Sá Ribeiro Júnior

“…The results indicated that the regression models developed for predicting warpage performed better with the ABS data. …”
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A Deep Learning Model for Stroke Patients’ Motor Function Prediction by Abeer Abdulaziz AlArfaj, Hanan A. Hosni Mahmoud, Alaaeldin M. Hafez

“…The experiments depict that the best performance is attained with the incorporation of the proposed EEG-DenseNet and the transfer model. The prediction accuracy of the model reached 96.5% with reduced time computational cost. …”
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Colorectal cancer risk prediction using a simple multivariable model. by Gillian S Dite, Chi Kuen Wong, Aviv Gafni, Erika Spaeth

“…For women and men separately, we developed (i) a multivariable risk prediction model using family history, a polygenic risk score (PRS) and clinical risk factors, and (ii) a simple model comprising family history and a PRS. …”
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Prediction of Gear Life based on Unbiased Grey Markov Combined Model by Duan Mingde, Wei Baolei, You Yanwei

“…For the difficulty of predicting the life of gear,an unbiased Grey GM（1,1）model is established based on the original data,and it is modified by using residual error model.The development trend of gear life is analyzed,the predicting accuracy is improved by introducing Markov optimization based on unbiased Grey GM（1,1）modification model.Comparing with the predicted value and the actual value,the predicting accuracy of gear life is improved from 87.06%to 90.09%.The result shows that the combined model has a better predicting precision and practicality within a period in the case of few data and poor information,it provides an available method for predicting the life of gear.…”
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Modelling and Prediction of Random Delays in NCSs Using Double-Chain HMMs by Yuan Ge, Yan Zhang, Wengen Gao, Fanyong Cheng, Nuo Yu, Jincenzi Wu

“…This paper is concerned with the modelling and prediction of random delays in networked control systems. …”
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Establishment of model predicting early patency rate of forearm arteriovenous fistula by CHEN Yong-ping, LIANG Yu-feng, LIANG Xing-lan, QIU Mei-lan, HUANG Bin-san, LIAO Wei-zeng, ZHANG Gui-rong

“…Using the ROC,the predictive efficacy of the model was evaluated to increase the positive predictive value of the operation. …”
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Predictability of water resources with global climate models. Case of Northern Tunisia by Besbes, Mustapha, Chahed, Jamel

“…The results show that the use of raw GCMs predictions on large basins is possible and provides precisions comparable to what is produced when using Regional Climate Models in medium size basins.…”
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Urinary metabolite model to predict the dying process in lung cancer patients by Séamus Coyle, Elinor Chapman, David M. Hughes, James Baker, Rachael Slater, Andrew S. Davison, Brendan P. Norman, Ivayla Roberts, Amara C. Nwosu, James A. Gallagher, Lakshminarayan R. Ranganath, Mark T. Boyd, Catriona R. Mayland, Douglas B. Kell, Stephen Mason, John Ellershaw, Chris Probert

“…Methods We performed urinary metabolomics analysis on patients with lung cancer to create a metabolite model to predict dying over the last 30 days of life. …”
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Rainfall prediction based on CNN-LSTM model under sliding window by Rui Yuan

“…Due to the new division of data through the sliding window method, the input data dimension to the CNN-LSTM model was relatively small. Therefore, data augmentation was employed to enhance the overall predictive ability of the model. …”
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Performance Comparison of Multiple Discriminant Analysis and Logit Models in Bankruptcy Prediction by Matúš Mihalovič

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Accurate Conditional Variance Models for Predicting Asymmetric Volatility in Cryptocurrency Markets by Onur Çelebi, Erhan Demireli

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A Lightweight Transformer Edge Intelligence Model for RUL Prediction Classification by Lilu Wang, Yongqi Li, Haiyuan Liu, Taihui Liu

“…Currently, gated recurrent networks, hybrid models, and attention-enhanced models used for predictive maintenance face the challenge of balancing prediction accuracy and model lightweighting when extracting complex degradation features. …”
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