Integration of multi agent reinforcement learning with golden jackal optimization for predicting average localization error in wireless sensor networks by K. Lakshmi Prabha, Hanan Abdullah Mengash, Hamed Alqahtani, Randa Allafi

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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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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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Research on Wind Power Grid Integration Power Fluctuation Smoothing Control Strategy Based on Energy Storage Battery Health Prediction by Bin Cheng, Jiahui Wu, Guancheng Lv, Zhongbo Li

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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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Robust Cross-Validation of Predictive Models Used in Credit Default Risk by Jose Vicente Alonso, Lorenzo Escot

“…While many methodologies have been developed, cross-validation is perhaps the most widely accepted, often being part of the model development process by optimizing the hyperparameters of predictive algorithms. This experimental research focuses on evaluating existing robust cross-validation variants to address the issues of validating credit default models. …”
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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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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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