Evaluating the Predictive Power of Software Metrics for Fault Localization by Issar Arab, Kenneth Magel, Mohammed Akour

“…This study investigates the predictive power of various software metrics for fault localization by framing the task as a multi-class classification problem and evaluating it using the Defects4J dataset. …”
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Predictive analysis of doubly Type-Ⅱ censored models by Young Eun Jeon, Yongku Kim, Jung-In Seo

“…Second, it addresses prediction problems in a closed-form manner, ensuring computational efficiency. …”
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Data-driven predictive models for sustainable smart buildings by Prabhu Rajaram, Gnana Swathika O․V․

“…In intelligent buildings, AI enables the analysis of vast amount of data collected from sensors and building systems, facilitating enhanced energy management, predictive maintenance, tailored comfort controls, and operational efficiencies derived from informed decisions based on operational conditions and occupant behavior trends, which aid in maximizing both functionality and sustainability of a building. …”
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Machine learning algorithms to predict khat chewing practice and its predictors among men aged 15 to 59 in Ethiopia: further analysis of the 2011 and 2016 Ethiopian Demographic and Health Survey by Mequannent Sharew Melaku, Lamrot Yohannes, Eliyas Addisu Taye, Nebebe Demis Baykemagn

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Artificial intelligence model for predicting early biochemical recurrence of prostate cancer after robotic-assisted radical prostatectomy by Miguel Angel Bergero, Pablo Martínez, Patricio Modina, Ricardo Hosman, Wenceslao Villamil, Romina Gudiño, Carlos David, Lucas Costa

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Machine learning models for predicting morphological traits and optimizing genotype and planting date in roselle (Hibiscus Sabdariffa L.) by Fazilat Fakhrzad, Warqaa Muhammed ShariffAl-Sheikh, Mohammed M. Mohammed, Heidar Meftahizadeh

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A novel deep learning-based 1D-CNN-optimized GRU approach for heart disease prediction by Jini Mol G., Ajith Bosco Raj T.

“…This research proposes an ensemble classification method leveraging machine learning (ML) to predict cardiac problems, providing physicians with actionable insights for personalized diagnoses and treatments. …”
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Prediction of the Effect of Polymer Membrane Composition in a Dry Air Humidification Process via Neural Network Modeling by M. Fakhroleslam, A. Samimi, S.A. Mousavi, R. Rezaei

“…The results showed that the feed- forward neural network models, especially FFGA, were suitable for prediction of the effect of membrane composition and operating conditions on the performance of this type of membrane humidifiers…”
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A Special Points and Neural Network-Based Dynamic Multi-Objective Optimization Algorithm by Sanyi Li, Wenjie Hou, Peng Liu, Weichao Yue, Qian Wang

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Cybersecure XAI Algorithm for Generating Recommendations Based on Financial Fundamentals Using DeepSeek by Iván García-Magariño, Javier Bravo-Agapito, Raquel Lacuesta

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Pore size classification and prediction based on distribution of reservoir fluid volumes utilizing well logs and deep learning algorithm in a complex lithology by Hassan Bagheri, Reza Mohebian, Ali Moradzadeh, Behnia Azizzadeh Mehmandost Olya

“…Subsequently, the CUDA Deep Neural Network Long Short-Term Memory algorithm(CUDNNLSTM), belonging to the category of DL algorithms and harnessing the computational power of GPUs, is employed for the prediction of CBW, BVI, and FFV logs. …”
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Online Prediction of Concrete Temperature During the Construction of an Arch Dam Based on a Sparrow Search Algorithm–Incremental Support Vector Regression Model by Yihong Zhou, Yu Deng, Fang Wang, Chunju Zhao, Huawei Zhou, Zhipeng Liang, Lei Lei

“…To overcome these limitations, this study constructed a sparrow search algorithm–incremental support vector regression (SSA-ISVR) model for online concrete temperature prediction. …”
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Predicting higher risk factors for COVID-19 short-term reinfection in patients with rheumatic diseases: a modeling study based on XGBoost algorithm by Yao Liang, Siwei Xie, Xuqi Zheng, Xinyu Wu, Sijin Du, Yutong Jiang

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Derivation and validation of an algorithm to predict transitions from community to residential long-term care among persons with dementia-A retrospective cohort study. by Wenshan Li, Luke Turcotte, Amy T Hsu, Robert Talarico, Danial Qureshi, Colleen Webber, Steven Hawken, Peter Tanuseputro, Douglas G Manuel, Greg Huyer

“…<h4>Conclusions and implications</h4>We developed an algorithm to predict time to LTC entry among individuals living with dementia. …”
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Comparison of Support Vector Machine (SVM) and Random Forest (RF) Algorithm Performance with Random Undersampling Technique to Predict Gestational Diabetes Mellitus Risk by Annisa Damayanti, Anna Baita

“…One of the machine learning methods that can be used to predict GDM is the Support Vector Machine (SVM) algorithm and the Random Forest (RF) algorithm. …”
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Research on a hybrid deep learning model based on two-stage decomposition and an improved whale optimization algorithm for air quality index prediction by Hangyu Zhou, Yongquan Yan

Subjects: “…Air quality index prediction…”
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Prediction of China’s Polysilicon Prices: A Combination Model Based on Variational Mode Decomposition, Sparrow Search Algorithm and Long Short-Term Memory by Jining Wang, Lin Jiang, Lei Wang

Subjects: “…polysilicon price prediction…”
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A Novel Back Propagation Neural Network Based on the Harris Hawks Optimization Algorithm for the Remaining Useful Life Prediction of Lithium-Ion Batteries by Yuyang Zhou, Zijian Shao, Huanhuan Li, Jing Chen, Haohan Sun, Yaping Wang, Nan Wang, Lei Pei, Zhen Wang, Houzhong Zhang, Chaochun Yuan

“…In order to achieve accurate and reliable RUL prediction, a novel RUL prediction method which employs a back propagation (BP) neural network based on the Harris Hawks optimization (HHO) algorithm is proposed. …”
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An Algorithm to Analyze Cost Heterogeneity using Counterfactual Scenarios in Endovascular versus Open Repair of Abdominal Aortic Aneurysm: Predicting Costs for Subsequent Patients by Christopher A. Jones, Peter W. Callas, Robert W. Everett, Richard A. Galbraith, Richie Spitsberg, Jeffrey J. Petrozzino, Michael J. DeSarno, Andrew C. Stanley

“… # Conclusions Certain risk factors at the individual patient level are predictive of UQC. Under such circumstances, it is our expectation that such algorithms may be used to select the most cost-efficient treatment.…”
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External validation of a serum tumor marker algorithm for early prediction of no durable benefit to immunotherapy in metastastic non-small cell lung carcinoma by Milou M. F. Schuurbiers, Freek A. van Delft, Hendrik Koffijberg, Maarten J. IJzerman, Kim Monkhorst, Marjolijn J. L. Ligtenberg, Daan van den Broek, Huub H. van Rossum, Michel M. van den Heuvel

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