Machine learning algorithms to predict feeding practices during diarrheal disease and its determinants among under-five children in East Africa by Tirualem Zeleke Yehuala, Nebebe Demis Baykemagn, Bewuketu Terefe

“…In this work, we evaluated the predictive models' performance using performance assessment criteria such as accuracy, precision, recall, and the AUC curve.ResultsIn this study, 20,059 children aged 5 years were used in the final analysis. …”
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Application Of ArtifiCial Intelligence in E-Governance: A Comparative Study of Supervised Machine Learning and Ensemble Learning Algorithms on Crime Prediction. by Niyonzima, Ivan, Muhaise, Hussein, Akankwasa, Aureri

“…Experimental results revealed that KNN generally performed better when compared to the rest of the algorithms. we then developed a crime prediction model based on KNN and its prediction accuracy was 66% on our test dataset. …”
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A rules extraction algorithm for IPTV customers forecasting based on the forecasting entropy measurement by Minjuan WANG, Zhengpeng JI, Chao LV

“…An algorithm model conformed to the user behavior,based on the massive IPTV user characteristic data which extract rules and classify IPTV users was proposed.First,IPTV user group description dimension in accordance with the user on demand was put forward.Namely,the user group could be described by basic property and trend of user behavior could be described by users' demand behavior.Then the concept of prediction measurement was put forward,the stability of user group was described,and an algorithm which extracted demand behavior probability on stable user group was proposed.At last,the algorithm model was verified and analyzed by massive IPTV operation data.…”
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Optimal machine learning algorithms and UAV multispectral imagery for crop phenotypic trait estimation: a comprehensive review and meta-analysis by Adama Ndour, Gerald Blasch, João Valente, Bisrat Haile Gebrekidan, Tesfaye Shiferaw Sida

“…In this study, we conducted a comprehensive meta-analysis to analyze the relationship between the machine learning model performance and variables such crop type, the type of aerial phenotyping platform, the phenological stage, etc A trait-based comparison of the efficiency and popularity of machine learning algorithms was conducted. Our findings showed that the multiple linear regression is the most effective model in predicting biomass while artificial neural networks showed up as the top performing algorithm in determining nitrogen content. …”
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Air quality prediction method based on improved BCCSA and deep LSTM by Wei Shiyue, Xu Hongzhen

“…Therefore, an air quality prediction method based on improved binary chaotic crow search algorithm(BCCSA) and deep long short term memory neural network(LSTM) is proposed. …”
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Machine learning-based prediction of CO2 solubility in methyldiethanolamine solutions: A comparative study by Sajjad Fazeli, Mohammad Amin Moradkhani, Behrouz Bayati

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HSoMLSDP: A Hybrid Swarm-Optimized Machine Learning Framework for Software Defect Prediction by Madhusmita Das, Biju R. Mohan, Ram Mohana Reddy Guddeti

Subjects: “…Swarm-optimization algorithm…”
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An ensemble machine learning-based performance evaluation identifies top In-Silico pathogenicity prediction methods that best classify driver mutations in cancer by Subrata Das, Vatsal Patel, Shouvik Chakravarty, Arnab Ghosh, Anirban Mukhopadhyay, Nidhan K. Biswas

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Optimization of Graphene Oxide’s Characteristics with TOPSIS Using an Automated Decision-Making Process by Javanbakht T.

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Novel concept for the healthy population influencing factors by Yuhao Shen, Jichao Wang, Lihua Ma, Huizhe Yan

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Enhancing patient rehabilitation outcomes: artificial intelligence-driven predictive modeling for home discharge in neurological and orthopedic conditions by Leonardo Buscarini, Paola Romano, Elena Sofia Cocco, Carlo Damiani, Sanaz Pournajaf, Marco Franceschini, Francesco Infarinato

“…Progress in both fields has enabled the generation of a vast amount of data used for making predictions and identifying interesting clusters and pathways. …”
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Explainable Model Prediction of Memristor by Sruthi Pallathuvalappil, Rahul Kottappuzhackal, Alex James

“…This article proposes predicting the memristor device under test by automatically evaluating the <italic>I&#x2013;V</italic> behavior using random forest and extreme gradient boosting algorithms. …”
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The machine learning in the prediction of elections by M.S.C. José A. León-Borges, M.A. Roger-Ismael-Noh-Balam, Lic. Lino Rangel Gómez, Br. Michael Philip Strand

“…This research article, presents an analysis and a comparison of three different algorithms: A.- Grouping method K-means, B.-Expectation a convergence criteria, EM and C.- Methodology for classification LAMDA, using two software of classification Weka and SALSA, as an aid for the prediction of future elections in the state of Quintana Roo. …”
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Research on POI quality prediction based on KPCA-GA-BP neural network by Lu LIU, Dan YANG, Ruijie CHEN, Jia LI, Xi ZHOU

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Evaluation of Thermal Damage Effect of Forest Fire Based on Multispectral Camera Combined with Dual Annealing Algorithm by Pan Pei, Xiaojian Hao, Ziqi Wu, Rui Jia, Shenxiang Feng, Tong Wei, Wenxiang You, Chenyang Xu, Xining Wang, Yuqian Dong

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Mopidip: a modular real-time pipeline for machinery diagnosis and prognosis based on deep learning algorithms by Mattia Pujatti, Davide Calzà, Andrea Gobbi, Piergiorgio Svaizer, Marco Cristoforetti

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Prediction of Scale Synchronization Instability by V. E. Lankin, A. K. Schaschkin

“…Based on the models of long-term care scales algorithms to estimate parameters of these processes and their prediction are created. …”
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LSTM-ANN-GA A HYBRID DEEP LEARNING MODEL FOR PREDICTIVE MAINTENANCE OF INDUSTRIAL EQUIPEMENT by Farouk Noumich, Abouchabaka Jaafar, Amrani Ayoub

Subjects: “…predictive maintenance…”
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Operational Performance Assessment of PV-Powered Street Lighting: A Comparative Study of Different Machine Learning Prediction Models by Safwan Nadweh, Nabil Mohammed, Charalambos Konstantinou, Shehab Ahmed

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Prediction Model For Students' On-Time Graduation Using Algorithm Support Vector Machine (SVM) Based  Particle Swarm Optimization (PSO) by Syarif Hidayatulloh, Gandung Triyono, Kiki Ari Suwandi kosasih

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