Comparative study on RF-BP model prediction of mining water-conducting fracture zone height in Binchang Coal Mine by Yadong JI, Xuan LIU, Kaipeng ZHU, Chunhu ZHAO, Kai LI, Chenhan YUAN, Panpan LI, Pengzhen YAN

“…The research results can provide some references for predicting the development height of the water-conducting fracture zone in Binchang Coal Mine.…”
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Model predictive control for energy efficient AC motor drives: An overview by Muhammad Bilal Shahid, Weidong Jin, Muhammad Abbas Abbasi, Abdul Rashid Bin Husain, Hafiz Mudassir Munir, Mannan Hassan, Aymen Flah, Ahmed Saad Eddine Souissi, Thamer A. H. Alghamdi

“…Then, the important challenges in MPC implementation, such as computational complexity reduction and delay compensation, weighting factor selection for multi‐objective cost functions, steady state performance and ripple reduction, parameter variations/model mismatching and achieving extended prediction horizons, are surveyed and most relevant solutions are reviewed. …”
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Predictive Modeling of Surface Subsidence Considering Different Environmental Risk Zones by Yunsong Li, Yongjun Qin, Liangfu Xie, Yangchun Yuan, Jie Ran

“…Adopt four different noise reduction algorithms for data noise reduction on the raw data of the monitoring points at the intervals of different risk zones, and combine the time series prediction as well as the deep learning prediction method to get the prediction model for environmental risk zoning based on the environmental risk zoning. …”
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Efficacy of two radiographic algorithms for detection of peri-implant bone defects on cone-beam computed tomography scans by Faezeh Yousefi, Ali Heidari, Azita Ehsani, Maryam Farhadian, Marzieh Ehsani

“…This study aimed to assess the efficacy of metal artifact reduction (MAR) and advanced noise reduction (ANR) algorithms for detection of peri-implant bone defects. …”
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Data-Driven Pavement Performance: Machine Learning-Based Predictive Models by Mohammad Fahad, Nurullah Bektas

“…However, machine learning models offer a time-efficient solution for predicting pavement performance. This study utilizes a range of machine learning algorithms, including linear regression, decision tree, random forest, gradient boosting, K-nearest neighbour, Support Vector Regression, LightGBM and CatBoost, to analyse their effectiveness in predicting pavement performance. …”
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The role of artificial intelligence in vascular care by Nehaar Nimmagadda, BS, Edouard Aboian, MD, Sharon Kiang, MD, Uwe Fischer, MD

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Non – Invasive, smartphone image-based screening for sickle cell disease at the point-of-need by Eudorah F. Vital, Meredith Haak LiCalzi, Robert G. Mannino, Patrick T. McGann, Wilbur A. Lam

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Development and validation of a probability-assessment nomogram for non-suicidal self-injury in hospitalized adolescents and young adults with mental disorders by Qi Liu, Yanjuan Ren, Yalin Huang, Ruyi Xie, Yinyuan Li, Zaiquan Dong, Xiaoxia Zhang

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Prediction model for the selection of patients with glioma to proton therapy by Jesper Folsted Kallehauge, Siri Grondahl, Camilla Skinnerup Byskov, Morten Høyer, Slavka Lukacova

“…The dataset was split into training (n = 37, period 2019–2022) and test (n = 12, period 2023) cohorts. Prediction models were built using logistic regression algorithms and support vector machines (SVMs) and evaluated using the area under the precision-recall curve (AUC-PR). …”
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Efficient Fault Diagnosis of Elevator Cabin Door Drives Using Machine Learning with Data Reduction for Reliable Transmission by Jakub Gęca, Dariusz Czerwiński, Bartosz Drzymała, Krzysztof Kolano

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A Hybrid Algorithm for Contour Thinning in Image Processing by Mamatov Narzullo, Niyozmatova Nilufar, Jalelova Malika, Samijonov Abdurashid, Samijonov Boymirzo

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Housing Price Prediction - Machine Learning and Geostatistical Methods by Cellmer Radosław, Kobylińska Katarzyna

“…Machine learning algorithms are increasingly often used to predict real estate prices because they generate more accurate results than conventional statistical or geostatistical methods. …”
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Conformal prediction for uncertainty quantification in dynamic biological systems. by Alberto Portela, Julio R Banga, Marcos Matabuena

“…As an alternative, we propose using conformal predictions methods and introduce two novel algorithms designed for dynamic biological systems. …”
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Prediction Approaches for Smart Cultivation: A Comparative Study by Amitabha Chakrabarty, Nafees Mansoor, Muhammad Irfan Uddin, Mosleh Hmoud Al-adaileh, Nizar Alsharif, Fawaz Waselallah Alsaade

“…Other contemporary machine learning algorithms, namely, support vector machine, random forest, and logistic regression, have average prediction accuracy of around 68.9%, 91.2%, and 62.39%, respectively.…”
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Hybrid CNN-Transformer-WOA model with XGBoost-SHAP feature selection for arrhythmia risk prediction in acute myocardial infarction patients by Li Li, Wenjun Ren, Yuying Lei, Lixia Xu, Xiaohui Ning

Subjects: “…Arrhythmia prediction…”
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Breaks in the Arctic ice cover: from observations to predictions by A. A. Ershova, L. N. Dyment, T. A. Alekseeva

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Causal network inference based on cross-validation predictability by Yuelei Zhang, Qingcui Li, Jiachen Wang, Xiao Chang, Luonan Chen, Xiaoping Liu

“…The causality was extensively validated by combining a large variety of statistical simulation experiments and available benchmark data (simulated data and various real data). Combining the predicted causal network and the real benchmark network, the CVP algorithm demonstrates high accuracy and strong robustness in comparison with the mainstream algorithms.…”
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Predictive analysis of heart disease using quantum-assisted machine learning by Mehroush Banday, Sherin Zafar, Parul Agarwal, M. Afshar Alam, Siddhartha Sankar Biswas, Imran Hussain, K. M. Abubeker

“…Techniques for QML have the potential to forecast cardiac disease and help in early detection. To predict the risk of coronary heart disease, a hybrid approach utilising an ensemble machine learning model based on QML classifiers is presented in this paper. …”
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HAMF: A Novel Hierarchical Attention-Based Multi-Modal Fusion Model for Parkinson’s Disease Classification and Severity Prediction by Anitha Rani Palakayala, P. Kuppusamy, D. Kothandaraman, Gunakala Archana, Jaideep Gera

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Evidential Reasoning Approach for Predicting Popularity of Instagram Posts by L. Rivadeneira, I. Loor

“…Machine learning predictive models are increasingly used to analyse social media data. …”
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