Comparative analysis of empirical and deep learning models for ionospheric sporadic E layer prediction by BingKun Yu, PengHao Tian, XiangHui Xue, Christopher J. Scott, HaiLun Ye, JianFei Wu, Wen Yi, TingDi Chen, XianKang Dou

“…In this study, we present Es predictions made by an empirical model and by a deep learning model, and analyze their differences comprehensively by comparing the model predictions to satellite RO measurements and ground-based ionosonde observations. …”
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Predictive interpretable analytics models for forecasting healthcare costs using open healthcare data by A. Ravishankar Rao, Raunak Jain, Mrityunjai Singh, Rahul Garg

“…We demonstrate our approach by creating predictive models using recent machine learning techniques. …”
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The Use of Momentum-Inspired Features in Pre-Game Prediction Models for the Sport of Ice Hockey by Noel Jordan T.P., Fonseca Vinicius Prado da, Soares Amilcar

“…We show that with the use of SVM and logistic regression these momentum- based features have more predictive power than traditional frequency-based features in a pre-game prediction model which only uses each team’s three most recent games to assess team quality. …”
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Performance Evaluation of Numerical Weather Prediction Models in Forecasting Rainfall Events in Kerala, India by V. Nitha, S. K. Pramada, N. S. Praseed, Venkataramana Sridhar

Subjects: “…Numerical Weather Prediction (NWP) models…”
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A comparative study of explainable machine learning models with Shapley values for diabetes prediction by Keona Pang

“…Over the years, numerous machine learning models have been developed, leading to successful applications across various fields. …”
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Predictive models for the surface roughness and subsurface damage depth of semiconductor materials in precision grinding by Shang Gao, Haoxiang Wang, Han Huang, Zhigang Dong, Renke Kang

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Establishment of interpretable cytotoxicity prediction models using machine learning analysis of transcriptome features by You Wu, Ke Tang, Chunzheng Wang, Hao Song, Fanfan Zhou, Ying Guo

“…In summary, the models established in this research exhibit superior capacity to those of previous studies; these models enable accurate high-safety substance screening via cytotoxicity prediction across cell lines. …”
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Correction: Time series models for prediction of leptospirosis in different climate zones in Sri Lanka. by PLOS ONE Staff

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Systematic review of risk prediction models for arteriovenous fistula dysfunction in maintenance hemodialysis patients by Shiyan Yao, Guannan Ma, Yongze Dong, Mengjiao Zhao, Luchen Chen, Wenhao Qi, Huajuan Shen

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Optimized machine learning based comparative analysis of predictive models for classification of kidney tumors by Vatsala Anand, Ajay Khajuria, Rupendra Kumar Pachauri, Vinay Gupta

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Construction of mathematical models to predict M25 and M10 coke quality indices by E. N. Stepanov, A. N. Smirnov, D. I. Alekseev

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Development and validation of prediction models for death within 6 months after cardiac arrest by Jianping Lu, Jianping Lu, Yuqi Zeng, Yuqi Zeng, Nan Lin, Qinyong Ye, Qinyong Ye

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Comparative analysis of supervised learning models for effluent quality prediction in wastewater treatment plants. by Liu Bo-Qi, Zhou Ding-Jie, Zhao Yang, Shi Long-Yu

“…Nevertheless, the findings provide valuable insights into selecting effective machine learning models for effluent quality prediction, supporting data-driven decision-making in wastewater management and advancing intelligent process optimization in WWTP.…”
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Assessment of spatial autocorrelation and scalability in fine-scale wildfire random forest prediction models by Madeleine Pascolini-Campbell, Joshua B. Fisher, Kerry Cawse-Nicholson, Christine M. Lee, Natasha Stavros

“…Abstract Wildfire prediction models that can be applied across diverse regions at fine scales (< 100 m) are critical for wildfire management. …”
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Comparative Study of OLGA and LedaFlow Models for Mechanistic Predictions of Hydrate Transport Dynamics by Anqi Qu, Luiz F. R. Dalla, Luis E. Zerpa, Thierry Palermo, Khalid Mateen, Annie Fidel-Dufour, Carolyn A. Koh

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Predictive Performance Evaluation of ARIMA and Hybrid ARIMA-LSTM Models for Particulate Matter Concentration by Johanes Dian Kurniawan, Hanna Arini Parhusip, Suryasatria Trihandaru

“…This study provides an objective evaluation of prediction performance models for particulate matter policy for industrial stakeholders by comparing the ARIMA and Hybrid ARIMA-LSTM models for predicting air quality data from the industrial environment. …”
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Advanced machine learning models for the prediction of ceramic tiles’ properties during the firing stage by V. Vasic, Milica, Awoyera, Paul O., Fadugba, Oladlu George, Barisic, Ivana, Nettinger Grubeša, Ivanka

“…Among the four ensemble ML models evaluated, CatBoost demonstrated the highest predictive performance. …”
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AI-based nanotoxicity data extraction and prediction of nanotoxicity by Eunyong Ha, Seung Min Ha, Zayakhuu Gerelkhuu, Hyun-Yi Kim, Tae Hyun Yoon

“…Among toxicity assessment methods, computational models for predicting nanotoxicity are emerging as alternatives to traditional in vitro and in vivo assays, which involve high costs and ethical concerns. …”
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Predicting snow structures relevant to reindeer husbandry by Emma T. D. Perkins, Amanda H. Lynch, Vera Solovyeva, David A. Bailey

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Development and application of the 3-PGCj model for predicting stand growth of Japanese cedar (Cryptomeria japonica) plantations by Hung-En Li, Ching-Chu Tsai, Kai-Chih Yin, Yen-Jen Lai, Su-Ting Cheng

Subjects: “…Stand growth modeling…”
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