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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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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From Social to Academic: Associations and Predictions Between Different Types of Peer Relationships and Academic Performance Among College Students by Jiadong Tian, Jiali Lin, Dagang Li

“…Subsequently, we used Random Forests and Neural Networks as baseline methods, and introduced Graph Convolutional Network and Dynamic Graph Convolutional Network algorithms, on top of a graph network model based on social characteristics, to predict students’ academic performances. …”
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Crowd Evacuation in Stadiums Using Fire Alarm Prediction by Afnan A. Alazbah, Osama Rabie, Abdullah Al-Barakati

“…This study introduces an AI-driven predictive fire alarm and evacuation model that leverages machine learning algorithms and real-time environmental sensor data to anticipate fire hazards before ignition, improving emergency response efficiency. …”
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Understanding the flowering process of litchi through machine learning predictive models by SU Zuanxian, NING Zhenchen, WANG Qing, CHEN Houbin

“…The machine learning algorithms can handle high-dimensional nonlinear data with complex interactions, outperform traditional statistical models in ecology, and have been effectively used for plant classification, phenology detection, crop growth detection, and yield prediction. …”
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Artificial Intelligence (AI) and the University. How AI Will Change Our Approach to Education by Jacek Grzybowski

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Prediction of Traffic Accident Severity Based on Random Forest by Jianjun Yang, Siyuan Han, Yimeng Chen

“…Random forest was used to rank the importance of 12 accident features, and 7 important accident features were finally adopted. By comparing the algorithms and optimizing the results, the prediction model of traffic accident degree with higher accuracy is finally obtained.…”
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Electrical Grounding Fault Prediction of EMU Traction Motor by Xuemiao PANG, Chunxing PEI, Chunguang YAN, Dongxing WANG, Jie JIANG

“…It shows that the prediction accuracy of the three algorithms is higher than 84% at all. …”
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Predicting Hit Songs Using Audio and Visual Features by Cheng-Yuan Lee, Yi-Ning Tu

“…However, we combined audio and visual data to make predictions on 1000 YouTube songs. In total, 1000 songs were grouped into two categories based on YouTube view counts: popular and non-popular. …”
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Prediction of Chemical Gas Emissions Based on Ecological Environment by Guobin Chen, Shijin Li

“…Relevant intelligent chemical algorithms control the emission of chemical gases, which can effectively reduce emissions and predict emissions more accurately. …”
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Statistical Prediction of Summer Rainfall and Vegetation in the Ethiopian Highlands by Mark R. Jury

“…After step-wise multivariate regression, the leading predictors are: surface temperature across Europe (cold-favourable), 850 mb zonal winds over the tropical Atlantic (easterly-favourable), and surface temperature in the tropical Indian Ocean (cold-favourable). Predictive algorithms for early and late rainfall exhibit a consistent r2 fit of ~0.50, while those for vegetation reach ~0.65 in late summer, indicating that fluctuations in food resources could be forewarned.…”
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Prediction Models for Diabetes in Children and Adolescents: A Review by Livija Cveticanin, Marko Arsenovic

“…Newly identified factors for differentiating between types of diabetes are discussed, alongside an overview of various machine learning and deep learning algorithms specifically adapted for diabetes prediction in children and adolescents. …”
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Towards Predicting Basketball Player Positions with Transformative Insights by Angelos Tsiannis, Christodoulos Efstathiades

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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

“…Abstract State‐of‐the‐art model‐based predictive control techniques for AC motor drives are reviewed in this paper. …”
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