Gross primary productivity and the predictability of CO₂: more uncertainty in what we predict than how well we predict it by I. Dunkl, I. Dunkl, N. Lovenduski, N. Lovenduski, A. Collalti, V. K. Arora, T. Ilyina, V. Brovkin, V. Brovkin

“…Up to 32 % of the GPP IAV induced by soil moisture is predictable, whereas only 7 % to 13 % of the GPP IAV induced by radiation is predictable. …”
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the function of prediction of recidivism methods in parole by mehri barzegar, Hossein gholami

Subjects: “…prediction of crime…”
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Development and internal validation of a prediction model for the presence of tinnitus in a Dutch population-based cohort by Maaike M. Rademaker, Maaike M. Rademaker, Adriana L. Smit, Adriana L. Smit, Robert J. Stokroos, Robert J. Stokroos, Maarten van Smeden, Inge Stegeman, Inge Stegeman

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Predicted and measured behavior of five spread footings on sand : proceedings of a prediction symposium / by Briaud, Jean-Louis, Gibbens, Robert, American Society of Civil Engineers

Short‐term prediction of photovoltaic power generation based on neural network prediction model by Mu Chai, Zhenan Liu, Kuanfang He, Mian Jiang

“…Abstract Real‐time monitoring and accurate prediction of photovoltaic (PV) power generation operation parameters are essential to ensure stable operation. …”
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A Comparative Analysis of the ARIMA and LSTM Predictive Models and Their Effectiveness for Predicting Wind Speed by Meftah Elsaraiti, Adel Merabet

“…However, the accuracy and adequacy of long-term wind speed prediction is not yet well resolved. This study aims to find the most effective predictive model for time series, with less errors and higher accuracy in the predictions, using artificial neural networks (ANNs), recurrent neural networks (RNNs), and long short-term memory (LSTM), which is a special type of RNN model, compared to the common autoregressive integrated moving average (ARIMA). …”
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Early prediction of hypothyroidism and multiclass classification using predictive machine learning and deep learning by Kalpna Guleria, Shagun Sharma, Sushil Kumar, Sunita Tiwari

“…However, manual analysis of these parameters on large databases to diagnose and predict hypothyroidism or hyperthyroidism is tedious. …”
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Predictive Control of a Heaving Compensation System Based on Machine Learning Prediction Algorithm by Lifen Hu, Ming Zhang, Zhi-Ming Yuan, Hongxia Zheng, Wenbin Lv

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Temporal phenomic predictions from unoccupied aerial systems can outperform genomic predictions by Alper Adak, Seth C Murray, Steven L Anderson

“…Over the last decade, genomic predictions (GP) based on genome-wide markers have become reliable and routine. …”
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The predictive accuracy of coronary heart disease risk prediction models in rural Northwestern China by Jiangwei Qiu, Zhenqi Chang, Kai Wang, Kexin Chen, Qingan Wang, Jiaxing Zhang, Juan Li, Chan Yang, Yi Zhao, Yuhong Zhang

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On the seasonal prediction and predictability of winter surface Temperature Swing Index over North America by Xiaosong Yang, Thomas L. Delworth, Liwei Jia, Liwei Jia, Nathaniel C. Johnson, Feiyu Lu, Colleen McHugh

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Seasonal predictability of summer north african subtropical high in operational climate prediction models by Fang Zhou, Ali Said Juma, Ran Zi, Jian Shi, Ming-Hong Liu

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Water Requirement in North China from Grey Point Prediction and Grey Interval Prediction by Lifeng Wu, Yuan Meng

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Predictive Performance of Machine Learning-Based Methods for the Prediction of Preeclampsia—A Prospective Study by Alina-Sinziana Melinte-Popescu, Ingrid-Andrada Vasilache, Demetra Socolov, Marian Melinte-Popescu

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Hyper-Local Weather Predictions with the Enhanced General Urban Area Microclimate Predictions Tool by Kevin A. Adkins, William Becker, Sricharan Ayyalasomayajula, Steven Lavenstein, Kleoniki Vlachou, David Miller, Marc Compere, Avinash Muthu Krishnan, Nickolas Macchiarella

“…This paper presents enhancements to, and the demonstration of, the General Urban area Microclimate Predictions tool (GUMP), which is designed to provide hyper-local weather predictions by combining machine-learning (ML) models and computational fluid dynamic (CFD) simulations. …”
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Clinical prediction rules in acute appendicitis: which combination of variables is more effective at predicting? by Juan C. Martín del Olmo, Pilar Concejo-Cutoli, Carlos Vaquero-Puerta, Cristina López-Mestanza, Juan R. Gómez-López

Subjects: “…Laparoscopic appendectomy. Clinical prediction rules.…”
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Evaluation of the predictive value of the bleeding prediction score VTE‐BLEED for recurrent venous thromboembolism by Frederikus A. Klok, Emilie Presles, Cecile Tromeur, Stefano Barco, Stavros V. Konstantinides, Olivier Sanchez, Gilles Pernod, Leela Raj, Philippe Robin, Pierre‐Yves Le Roux, Clément Hoffman, Solen Mélac, Laurent Bertoletti, Philippe Girard, Silvy Laporte, Patrick Mismetti, Guy Meyer, Christophe Leroyer, Francis Couturaud, for the PADIS‐PE Investigators

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Transformer Based Binocular Disparity Prediction with Occlusion Predict and Novel Full Connection Layers by Yi Liu, Xintao Xu, Bajian Xiang, Gang Chen, Guoliang Gong, Huaxiang Lu

“…Aiming at the problems in the matching method of constructing matching cost volume, we propose a disparity prediction algorithm based on Transformer, which specifically comprises the Swin-SPP module for feature extraction based on Swin Transformer, Transformer disparity matching network based on self-attention and cross-attention mechanism, and occlusion prediction sub-network. …”
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Deep Learning Predictive Models for Terminal Call Rate Prediction during the Warranty Period by Ferencek Aljaž, Kofjač Davorin, Škraba Andrej, Sašek Blaž, Borštnar Mirjana Kljajić

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Development and validation of the nomogram to predict the risk of hospital drug shortages: A prediction model. by Jie Dong, Yang Gao, Yi Liu, Xiuling Yang

“…At present, the risk of drug shortages in medical institutions rarely used prediction models. To this end, we attempted to proactively predict the risk of drug shortages in hospital drug procurement to make further decisions or implement interventions.…”
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