A Coal Bump Risk Assessment and Prediction Model Based on Multiparameter Indices by Tao Luo, Gangwei Fan, Shizhong Zhang, Shang Ren, Yibo Fan, Ruiliang Shen

“…This paper presents a model to assess and predict coal bump risk based on multiparameter indices. …”
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EVALUATION OF MACHINE LEARNING MODELS FOR BORON PREDICTION IN ANDISOL SOILS OF NARIÑO-COLOMBIA by David Álvarez Sánchez, Xilena López Estrella, Eduar Manso Ordoñez, Laura López Rivera, Jeison Rodriguez Valenzuela

“…That is why this research uses the predictive capacity of the machine learning (ML) approach. …”
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Regression-Based Networked Virtual Buoy Model for Offshore Wave Height Prediction by Eleonora M. Tronci, Matteo Vitale, Therese Patrosio, Thomas Søndergaard, Babak Moaveni, Usman Khan

“…While numerical wave models and machine learning techniques have been explored for wave height prediction, most approaches rely heavily on historical data from the same buoy, limiting their applicability when the target sensor is offline. …”
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Regional Tropospheric Delay Prediction Model Based on LSTM-Enhanced Encoder Network by Yuanfang Peng, Chenglin Cai, Zexian Li, Kaihui Lv, Xue Zhang, Yihao Cai

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Development and validation of a predictive model for suicidal thoughts and behaviors among freshmen by Yan Qin, Sifang Niu, Xingmeng Niu, Yangziye Guo, Yu Sun, Shuzhang Hu, Fuqin Mu, Ying Zhang, Min Liu, Jianli Wang, Yan Liu

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Between Domestic and Commonly Known Bankruptcy Prediction Models, How Differ It Can Be? by Muhamad Fiqri Aripin

“…As such the needs of research and improvement of Bankruptcy Prediction Models as risk assessment tool is a must. …”
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Study on Prediction of Sluice Settlement Based on Improved GM (1,1) Model by LI Xuede, ZHOU Mingming, ZHAO Jinlei, LIU Yang, JIANG Wenzhi, WANG Guizhi

“…In the settlement monitoring,the amount of initial monitoring data is little with great changes.It can effectively enhance the correlation of the data series and improve the accuracy of the model through pre-processing the data and modeling with GM prediction model.In view of the single value of weight coefficient in the traditional GM prediction model,this paper selects the optimal weight coefficient for the establishment of the GM prediction model by introducing superimposed weight coefficients and changing the initial value.The results show that the improved GM prediction model with high accuracy can accurately predict the actual measured value.…”
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Efficient productivity prediction model based on edge data compression in smart farms by Peng Jin, Wenshuang Du, Wenquan Jin

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Hybridized Deep Learning Model for Perfobond Rib Shear Strength Connector Prediction by Jamal Abdulrazzaq Khalaf, Abeer A. Majeed, Mohammed Suleman Aldlemy, Zainab Hasan Ali, Ahmed W. Al Zand, S. Adarsh, Aissa Bouaissi, Mohammed Majeed Hameed, Zaher Mundher Yaseen

“…Besides, selecting the most significant variables that have a major influence on PRSC in every important step for attaining economic and more accurate predictive models, this study investigates the capacity of deep learning neural network (DLNN) for shear strength prediction of PRSC. …”
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Vehicle Trajectory Prediction Using Residual Diffusion Model Based on Image Information by Wei He, Haoxuan Li, Tao Wang, Nan Wang

Subjects: “…trajectory prediction…”
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Predictive Modeling for Diabetes Subtype Classification in India: A Machine Learning Approach by Ulagamadesan Venkatesan, Anandakumar Amutha, Ranjit Mohan Anjana, Ranjit Unnikrishnan, Bagavandas Mappillairaju, Viswanathan Mohan

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Measuring and modeling waterlogging tolerance to predict the future for threatened lowland ash forests by E. J. Gustafson, D. R. Bronson, M. A. Windmuller-Campione, R. A. Slesak, D. M. Donner

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A New Ground-Motion Prediction Model for Shallow Crustal Earthquakes in Türkiye by Ulubey Çeken, Fadime Sertçelik, Abdullah İçen

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Three-State Hidden Markov Model for Spectrum Prediction in Cognitive Radio Networks by Emmanuel Oluwatosin Rabiu, Damilare Oluwole Akande, Zachaeus Kayode Adeyemo, Isaac Akinwale Akanbi, Oluwole Oladele Obanisola

“…However, these resources have grossly been under-utilized due to the inaccurate spectrum predictions. Existing spectrum occupancy and prediction techniques which rely on 2-state hidden Markov model (HMM) results in false alarm or missed detection caused by noisy or incomplete observable effects. …”
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Prediction of the volume of shallow landslides due to rainfall using data-driven models by J. Tuganishuri, C.-Y. Yune, G. Kim, S. W. Lee, M. D. Adhikari, S.-G. Yum

“…The objectives of this research are to construct a model using advanced data-driven algorithms (i.e., ordinary least squares or linear regression (OLS), random forest (RF), support vector machine (SVM), extreme gradient boosting (EGB), generalized linear model (GLM), decision tree (DT), deep neural network (DNN), <span class="inline-formula"><i>k</i></span>-nearest-neighbor (KNN), and ridge regression (RR) algorithms) for the prediction of the volume of landslides due to rainfall, considering geological, geomorphological, and environmental conditions. …”
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A high‐resolution model of the grapevine leaf morphospace predicts synthetic leaves by Daniel H. Chitwood, Efrain Torres‐Lomas, Ebi S. Hadi, Wolfgang L. G. Peterson, Mirjam F. Fischer, Sydney E. Rogers, Chuan He, Michael G. F. Acierno, Shintaro Azumaya, Seth Wayne Benjamin, Devendra Prasad Chalise, Ellice E. Chess, Alex J. Engelsma, Qiuyi Fu, Jirapa Jaikham, Bridget M. Knight, Nikita S. Kodjak, Adazsofia Lengyel, Brenda L. Muñoz, Justin T. Patterson, Sundara I. Rincon, Francis L. Schumann, Yujie Shi, Charlie C. Smith, Mallory K. St. Clair, Carly S. Sweeney, Patrick Whitaker, James Wu, Luis Diaz‐Garcia

“…Summary Grapevine leaves are a model morphometric system. Sampling over 10,000 leaves using dozens of landmarks, the genetic, developmental, and environmental basis of leaf shape has been studied and a morphospace for the genus Vitis predicted. …”
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Auditing the fairness of the US COVID-19 forecast hub's case prediction models. by Saad Mohammad Abrar, Naman Awasthi, Daniel Smolyak, Nekabari Sigalo, Vanessa Frias Martinez

“…In this paper, we carry out a comprehensive fairness analysis of the Forecast Hub model predictions and we show statistically significant diverse predictive performance across social determinants, with minority racial and ethnic groups as well as less urbanized areas often associated with higher prediction errors. …”
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Predictive nomogram integrating radiomics and multi‐omics for improved prognosis‐model in cholangiocarcinoma by Yunlu Jia, Mingyu Wan, Yifei Shen, Junli Wang, Xiao Luo, Mengye He, Ruiliang Bai, Wenbo Xiao, Xiaochen Zhang, Jian Ruan

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Evaluating the Performance and Potential Bias of Predictive Models for Detection of Transthyretin Cardiac Amyloidosis by Jonathan Hourmozdi, MD, MSAI, MA, Nicholas Easton, MSAI, Simon Benigeri, MSAI, James D. Thomas, MD, Akhil Narang, MD, David Ouyang, MD, Grant Duffy, BS, Ross Upton, PhD, Will Hawkes, PhD, Ashley Akerman, PhD, Ike Okwuosa, MD, Adrienne Kline, MD, PhD, Abel N. Kho, MD, Yuan Luo, PhD, Sanjiv J. Shah, MD, Faraz S. Ahmad, MD, MS

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A model based LSTM and graph convolutional network for stock trend prediction by Xiangdong Ran, Zhiguang Shan, Yukang Fan, Lei Gao

“…It is widely believed that modeling these dependencies can improve the accuracy of stock trend prediction and enable investors to earn more stable profits. …”
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