Machine learning and Fuzzy logic fusion approach for osteoporosis risk prediction by Rabia Khushal, Dr. Ubaida Fatima

Subjects: “…Fuzzy data transformation technique using three variables, fuzzy machine learning logic model for crisp output…”
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Combining Machine Learning Models to Improve Estimated Time of Arrival Predictions by Ramon Dalmau, Aymeric Trzmiel, Stephen Kirby

Subjects: “…machine learning…”
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Binary Classification of Customer’s Online Purchasing Behavior Using Machine Learning by Ahmad Aldelemy, Raed A. Abd-Alhameed

Subjects: “…Machine Learning…”
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The Navigation of Home Service Robot Based on Deep Learning and Machine Learning by Yupei Yan, Weimin Ma, Sengfat Wong, Xuemei Yin, Qiang Pan, Zhiwen Liao, Xiaoxin Lin

“…This paper discusses how to improve the accuracy of navigation for home service robot based on the deep learning and machine learning. First, the crawling programing is applied to collect enough images of fridge and washing machine on the web; a deep learning framework is proposed that can distinguish fridge and washing machine more accurately. …”
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Machine Learning–Enhanced Microseismic Analysis for Evaluating Rock Crack Trajectory by Xinglong Feng, Zeng Chen, Zhengrong Li, Qingtian Zeng, Jing Wang, Ping Wang

“…In this study, the evolution characteristics of MS parameters during the rock fracture process were investigated using MS localization techniques and spatial clustering methods. Machine learning methods were applied to cluster acoustic emission events, enabling the automatic identification of hazardous regions and the construction of crack propagation trajectories. …”
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SVM directed machine learning classifier for human action recognition network by Dharmanna Lamani, Pramod Kumar, A Bhagyalakshmi, J. Maria Shanthi, Lakshmana Phaneendra Maguluri, Mohammad Arif, C Dhanamjayulu, Sathish Kumar. K, Baseem Khan

“…The use of traditional machine learning classifiers is done in order to further improve the discriminative capacity of the features that have been learned. …”
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Clinical validation and optimization of machine learning models for early prediction of sepsis by Xi Liu, Meiyi Li, Xu Liu, Yuting Luo, Dong Yang, Hui Ouyang, Jiaoling He, Jinyu Xia, Fei Xiao, Fei Xiao, Fei Xiao

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Fund Performance Evaluation Based on Bayesian Model and Machine Learning Algorithm by Shuanbao Li, Shenming Qu

“…Based on Bayesian method, this paper constructs a model for estimating fund performance evaluation, and uses machine learning algorithm to construct a sampler that can sample on the basis of conditional distribution. …”
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Machine learning for predicting strength properties of waste iron slag concrete by Matiur Rahman Raju, Syed Ishtiaq Ahmad, Md Mehedi Hasan, Noor Md. Sadiqul Hasan, Md Monirul Islam, Md. Abdul Basit, Ishraq Tasnim Hossain, Saif Ahmed Santo, Md Shahrior Alam, Mahfuzur Rahman

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Predicting early cessation of exclusive breastfeeding using machine learning techniques. by Freja Marie Nejsum, Rikke Wiingreen, Andreas Kryger Jensen, Ellen Christine Leth Løkkegaard, Bo Mølholm Hansen

“…We aimed to develop and validate two models to predict cessation of exclusive breastfeeding within one month among infants born after 35 weeks gestation using machine learning techniques.<h4>Methods</h4>Utilizing a nationwide dataset from Statistics Denmark, including infants born between the 1st of January 2014 and the 31st of December 2015, we employed random forest machine learning to develop two predictive models. …”
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Coronary Heart Disease Risk Prediction Model Based on Machine Learning by YUE Haitao, HE Chanchan, CHENG Yuyou, ZHANG Sencheng, WU You, MA Jing

Subjects: “…coronary disease|machine learning|risk prediction model|logistic regression|k-nearest neighbor|support vector machine|decision tree|xgboost…”
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Cheating Detection in Online Exams Using Deep Learning and Machine Learning by Bahaddin Erdem, Murat Karabatak

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Predicting noncontact injuries of professional football players using machine learning. by Diogo Nuno Freitas, Sheikh Shanawaz Mostafa, Romualdo Caldeira, Francisco Santos, Eduardo Fermé, Élvio R Gouveia, Fernando Morgado-Dias

“…This study introduces an automated injury identification and prediction approach using machine learning, leveraging GPS data and player-specific parameters. …”
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Prediction of Coal Mining Subsidence Based on Machine Learning Probability Theory by Xiaohong Tian, Xinyuan Jin, Xinwei He

“…This paper mainly studies the prediction process of mining subsidence based on machine learning probability theory. In this paper, the mining subsidence problem is studied. …”
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Unlocking biological complexity: the role of machine learning in integrative multi-omics by Ravindra Kumar, Rajrani Ruhel, Andre J. van Wijnen

“…Machine learning and ensemble methods allow researchers to model nonlinear relationships and manage high-dimensional data, improving the precision of predictions. …”
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Evaluation of machine learning models for the prediction of Alzheimer's: In search of the best performance by Michael Cabanillas-Carbonell, Joselyn Zapata-Paulini

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The application of machine learning approaches to classify and predict fertility rate in Ethiopia  by Ewunate Assaye Kassaw, Biruk Beletew Abate, Bekele Mulat Enyew, Ashenafi Kibret Sendekie

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Interpretable Machine Learning to Forecast SEP Events for Solar Cycle 23 by Spiridon Kasapis, Lulu Zhao, Yang Chen, Xiantong Wang, Monica Bobra, Tamas Gombosi

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Machine learning-enhanced high-resolution exposure assessment of ultrafine particles by Yudie Jianyao, Hongyong Yuan, Guofeng Su, Jing Wang, Wenguo Weng, Xiaole Zhang

“…In this study, we developed a stacking-based machine learning framework integrating data-driven and physical-chemical models for a national-scale UFP exposure assessment at 1 km spatial and 1-hour temporal resolutions, leveraging long-term standardized PNC measurements in Switzerland. …”
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Investigating the effects of hyperparameter sensitivity on machine learning algorithms for PV forecasting by Ehtsham Muhammad, Rotilio Marianna, Cucchiella Federica, Di Giovanni Gianni, Schettini Domenico

“…Machine Learning (ML) models have been introduced in the past, and users have debated whether to tune the hyperparameters of the models. …”
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