Specifics of predicting the profitability of individual bank products based on machine learning by Inna Strelchenko, Dmytro Stognii, Anatolii Strelchenko

“…It is shown that neural networks have the highest level of predictive accuracy, but their implementation requires significant computational resources. …”
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INFORMATION PREDICTABILITY IN THE PROBLEM OF PARAMETER ESTIMATION ON THE BACKGROUND OF NON-STATIONARY PROCESSES by A. V. Ausiannikau, V. M. Kozel

“…The relationship of information predictability stochastic process and evaluation is shown.…”
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A machine learning-powered energy consumption prediction system with API by Toyeeb Adekunle Abd’Azeez, Lanre Olatomiwa

“…The lower MAPE and the higher R2 score indicate the superiority of the ExtraTreeRegressor over other algorithms. While energy consumption is characterised by high variance, our optimised model effectively interprets interactions between input features and predicts the equivalent energy consumed with a lower RMSE of 11.75. …”
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Machine Learning for Prediction of Relapses in Multiple Drug Resistant Tuberculosis Patients by A. S. Аlliluev, O. V. Filinyuk, E. E. Shnаyder, S. V. Аksenov

“…The objective of the study: to evaluate the possibility of using machine learning algorithms for prediction of relapses in multiple drug resistant tuberculosis (MDR TB) patients.Subjects and Methods. …”
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Ensemble Machine Learning for the Prediction and Understanding of the Refractive Index in Chalcogenide Glasses by Miruna-Ioana Belciu, Alin Velea

“…This study employs various machine learning models to reliably predict the refractive index at 20 °C using a small dataset of 541 samples extracted from the SciGlass database. …”
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Feasibility of Conflict Prediction of Drone Trajectories by Means of Machine Learning Techniques by Victor Gordo, Javier A. Perez-Castan, Luis Perez Sanz, Lidia Serrano-Mira, Yan Xu

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Bioinformatics prediction of function of T-cell exhaustion related genes in ischemic stroke by Yajun Gao, Ruyu Bai, Bo Gao, Ma Li

“…Potential drugs or molecular compounds that interact with key genes were predicted by searching DGIdb, and the drug-gene interaction network was visualized by Cytoscape software. …”
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Machine Learning Approaches to Predict Patient’s Length of Stay in Emergency Department by Mohammad A. Shbool, Omar S. Arabeyyat, Ammar Al-Bazi, Abeer Al-Hyari, Arwa Salem, Thana’ Abu-Hmaid, Malak Ali

“…This research aims to determine the critical factors that predict the outcome: the length of stay, i.e., the predictor variables. …”
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Machine learning and company failure prediction: Evidence from South Africa by Nicolene Wesson, Dewald Mienie, Anthea Myatt

“…Research purpose: The accuracy of company failure prediction was assessed when applying an array of fundamental machine learning algorithms in South Africa. …”
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Aircraft Multi-stage Altitude Prediction Under Satellite Signal Loss by Mengchan HUANG, Qiang MIAO

“…Compared to RNNs and their variants, the LTCA–TCN algorithm yields superior prediction results while maintaining a simpler structure and requiring fewer computational resources. …”
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Leveraging machine learning for data-driven building energy rate prediction by Nasim Eslamirad, Mehdi Golamnia, Payam Sajadi, Francesco Pilla

“…This paper presents a novel, data-driven approach for predicting Building Energy Ratings (BER) in urban environments, using advanced Machine Learning (ML) algorithms. …”
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Predicting the Acceptance of Informal Learning Technologies: A Case of the TikTok Application by Ahmed Al-Azawei, Ali Alowayr

“…Moreover, previous literature focused on the use of structural equation modeling (SEM) to predict technology acceptance, whereas the application of data mining algorithms is rare in this direction of research. …”
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Device-Driven Service Allocation in Mobile Edge Computing with Location Prediction by Qian Zeng, Xiaobo Li, Yixuan Chen, Minghao Yang, Xingbang Liu, Yuetian Liu, Shiwei Xiu

“…To validate the effectiveness of the proposed methods, we conduct multiple controlled experiments focusing on both location prediction models and service allocation algorithms. …”
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Prediction of Transformer Residual Flux Based on J-A Hysteresis Theory by Qi Long, Xu Yang, Keru Jiang, Changhong Zhang, Mingchun Hou, Yu Xin, Dehua Xiong, Xiongying Duan

“…Then, based on the J-A model, residual flux prediction of the transformer is carried out, and a transformer no-load energization experimental platform is built. …”
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Prediction of Work-relatedness of Shoulder Musculoskeletal Disorders as by Using Machine Learning by Saemi Jung, Bogeum Kim, Yoon-Ji Kim, Eun-Soo Lee, Dongmug Kang, Youngki Kim

“…Background: This study aimed to develop prediction models for the work-relatedness of shoulder diseases through machine learning algorithms. …”
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Risk prediction and effect evaluation of complicated appendicitis based on XGBoost modeling by Sunmeng Chen, Jianfu Xia, Beibei Xu, Yi Huang, Miaomiao Teng, Juyi Pan

“…An integrated learning algorithm, Extreme Gradient Boosting (XGBoost), was introduced to predict the risk of CAP and compared with Support Vector Machine (SVM), Random Forest (RF), and Decision Tree (CART) algorithms. …”
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Predicting Hospitalization Length in Geriatric Patients Using Artificial Intelligence and Radiomics by Lorenzo Fantechi, Federico Barbarossa, Sara Cecchini, Lorenzo Zoppi, Giulio Amabili, Mirko Di Rosa, Enrico Paci, Daniela Fornarelli, Anna Rita Bonfigli, Fabrizia Lattanzio, Elvira Maranesi, Roberta Bevilacqua

“…The aim of the present study is to use and adapt machine learning (ML) architectures, exploiting CT radiomics information, and analyze algorithms’ capability to predict hospitalization at the time of patient admission. (2) Methods: The original CT lung images of 168 COVID-19 patients underwent two segmentations, isolating the ground glass area of the lung parenchyma. …”
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Application of Artificial Intelligent Approach to Predict the Normal Boiling Point of Refrigerants by Bo Liu, Maryam Karimi Nouroddin

“…To this end, a total of 334 data points of Tb are gathered to prepare and test ELM and EDT boosted algorithms. The visual and mathematical comparisons of model outputs and real Tb express that proposed models have great potential to predict Tb of refrigerant. …”
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A Local–Global Graph KAN for Multi‐Class Prediction of PPI by Minghui Liu, Ying Qu

“…Therefore, using machine learning to treat multiple PPI predictions as binary classifications has become an alternative, but there is a problem of data imbalance. …”
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Machine Learning Techniques to Model and Predict Airflow Requirements in Underground Mining by Maria Karagianni, Andreas Benardos

“…With this twin model, several scenarios are developed and evaluated and more importantly data are gathered, allowing for the training of the ML algorithms used to assess and predict the required ventilation airflow, taking into account air quality data, the number of workers, and machine fleet.…”
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