Predictive modelling of aquaculture water quality using IoT and advanced machine learning algorithms by Md. Abdullah Al Mamun Hridoy, Chiara Bordin, Andleeb Masood, Khalid Masood

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A Method for Predicting Trajectories of Concealed Targets via a Hybrid Decomposition and State Prediction Framework by Zhengpeng Yang, Jiyan Yu, Miao Liu, Tongxing Peng, Huaiyan Wang

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Wind power generation prediction using LSTM model optimized by sparrow search algorithm and firefly algorithm by Wenjing Zhang, Hongjing Yan, Lili Xiang, Linling Shao

“…To raise the accuracy of wind power generation prediction, a bidirectional long short-term memory network combination model based on sparrow search algorithm and firefly algorithm optimization is designed. …”
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A novel interval prediction method in wind speed based on deep learning and combination prediction by XueJun Chen, Tao Han, Peng Cheng, Xuanfang Da

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Research on E-Commerce Inventory Sales Forecasting Model Based on ARIMA and LSTM Algorithm by Chenyang Wang, Junsheng Wang

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Machine learning algorithms can predict emotional valence across ungulate vocalizations by Romain A. Lefèvre, Ciara C.R. Sypherd, Élodie F. Briefer

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Applications of Machine Learning Algorithms in Geriatrics by Adrian Stancu, Cosmina-Mihaela Rosca, Emilian Marian Iovanovici

“…The integration of machine learning (ML)-type algorithms in geriatrics represents a direction for optimizing prevention, diagnosis, prediction, monitoring, and treatment. …”
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Model-Free Predictive Control Based on RLS Algorithm for Grid-Forming Inverters With Virtual Synchronous Generator by Min Huang, Huiying Zhang, Kangan Wang, Zhilei Yao, Weimin Wu

“…In the role of the inner loop control, the traditional model predictive control (MPC) is widely employed in converters, but it is heavily dependent on model parameters. …”
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Predicting student self-efficacy in Muslim societies using machine learning algorithms by Mohammed Ba-Aoum, Mohammed Ba-Aoum, Mohammed Alrezq, Jyotishka Datta, Konstantinos P. Triantis

“…Four machine learning algorithms-Decision Tree, Random Forest, XGBoost, and Neural Network-were employed to predict self-efficacy using two demographic variables and 10 socio-emotional, cognitive, and regulatory factors. …”
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Prediction and Optimization of Civil Aviation Flight Delays Based on Machine Learning Algorithms by Qingwei Zhong, Yingxue Yu, Yiru Huang, Tianhang Zhang

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Predicting diabetic retinopathy based on routine laboratory tests by machine learning algorithms by Xiaohua Wan, Ruihuan Zhang, Yanan Wang, Wei Wei, Biao Song, Lin Zhang, Yanwei Hu

“…Using 39 optimal variables, a prediction model was constructed using the eXtreme Gradient Boosting (XGBoost) algorithm and compared with four other algorithms: support vector machine (SVM), gradient boosting decision tree (GBDT), neural network (NN), and logistic regression (LR). …”
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Predicting the risk of pulmonary embolism in patients with tuberculosis using machine learning algorithms by Haobo Kong, Yong Li, Ya Shen, Jingjing Pan, Min Liang, Zhi Geng, Yanbei Zhang

“…Abstract Background This study aimed to develop predictive models with robust generalization capabilities for assessing the risk of pulmonary embolism in patients with tuberculosis using machine learning algorithms. …”
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Machine learning algorithms for predicting PTSD: a systematic review and meta-analysis by Masoumeh Vali, Hossein Motahari Nezhad, Levente Kovacs, Amir H Gandomi

“…Tree-based models were the primarily used algorithms and showed promising results in predicting PTSD outcomes for various groups, as indicated by their pooled AUCs: military incidents (0.745), sexual or physical trauma (0.861), natural disasters (0.771), medical trauma (0.808), firefighters (0.96), and alcohol-related stress (0.935). …”
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On the Training Algorithms for Artificial Neural Network in Predicting the Shear Strength of Deep Beams by Thuy-Anh Nguyen, Hai-Bang Ly, Hai-Van Thi Mai, Van Quan Tran

“…This study aims to predict the shear strength of reinforced concrete (RC) deep beams based on artificial neural network (ANN) using four training algorithms, namely, Levenberg–Marquardt (ANN-LM), quasi-Newton method (ANN-QN), conjugate gradient (ANN-CG), and gradient descent (ANN-GD). …”
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Predicting the shield effectiveness of carbon fiber reinforced mortars utilizing metaheuristic algorithms by Mana Alyami, Irfan Ullah, Furqan Ahmad, Hisham Alabduljabbar

“…A user-friendly interface was developed for instant SE prediction of carbon fiber reinforced mortar, requiring only essential input parameters.…”
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Comparative analysis of regression algorithms for drug response prediction using GDSC dataset by Soojung Ha, Juho Park, Kyuri Jo

“…In addition, it is difficult for researchers to know which algorithm is appropriate for prediction as various regression and feature selection algorithms exist. …”
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Predicting diabetes using supervised machine learning algorithms on E-health records by Sulaiman Afolabi, Nurudeen Ajadi, Afeez Jimoh, Ibrahim Adenekan

“…The research explores the effectiveness of three supervised machine learning algorithms: logistic regression, Random Forest, and k-nearest neighbors (KNN), in developing predictive models for diabetes. …”
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Hydropower Station Status Prediction Using RNN and LSTM Algorithms for Fault Detection by Omar Farhan Al-Hardanee, Hüseyin Demirel

“…In this study, artificial neural network algorithms (RNN and LSTM) are used to predict the condition of the hydropower station, identify the fault before it occurs, and avoid it. …”
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Predicting the Classification of Heart Failure Patients Using Optimized Machine Learning Algorithms by Marzia Ahmed, Mohd Herwan Sulaiman, Md Maruf Hassan, Touhid Bhuiyan

Subjects: “…Heart failure survival prediction…”
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Experiments on software error prediction using Decision Tree and Random Forest algorithms by Ilona Bluemke, Paweł Borsukiewicz

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