Predicting the Permeability of Pervious Concrete Based on the Beetle Antennae Search Algorithm and Random Forest Model by Jiandong Huang, Tianhong Duan, Yi Zhang, Jiandong Liu, Jia Zhang, Yawei Lei

“…This study proposed a method to combine the beetle antennae search (BAS) and random forest (RF) algorithm to predict the permeability of pervious concrete. …”
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XGBoost algorithm optimized by simulated annealing genetic algrithm for permeability prediction modeling of carbonate reservoirs by Changbing Huang, Xinyu Zhu, Mingyu Lu, Yuling Zhang, Shengbo Yang

“…The results show that the prediction results of SA-GA-XGBoost algorithm are more consistent with the core data. …”
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A Novel Model for Accurate Daily Urban Gas Load Prediction Using Genetic Algorithms by Xi Chen, Feng Wang, Li Xu, Taiwu Xia, Minhao Wang, Gangping Chen, Longyu Chen, Jun Zhou

“…A multiple weather parameter–daily load prediction (MWP-DLP) model based on System Thermal Days (STD) was established, and the genetic algorithm was used to solve the model. …”
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Distributed Photovoltaic Power Energy Generation Prediction Based on Improved Multi-objective Particle Algorithm by Yuanzheng Xiao, Huawei Hong, Feifei Chen, Xiaorui Qian, Ming Xu, Hanbin Ma

Subjects: “…Particle Algorithm…”
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Exploring machine learning algorithms for predicting fertility preferences among reproductive age women in Nigeria by Zinabu Bekele Tadese, Teshome Demis Nimani, Kusse Urmale Mare, Fetlework Gubena, Ismail Garba Wali, Jamilu Sani

“…Six machine learning algorithms, namely, Logistic Regression, Support Vector Machine, K-Nearest Neighbors, Decision Tree, Random Forest, and eXtreme Gradient Boosting, were employed on a total sample size of 37,581 in Python 3.9 version. …”
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Development of a Student Depression Prediction Model Based on Machine Learning with Algorithm Performance Evaluation by Penni Wintasari Simarmata, Putri Taqwa Prasetyaningrum

Subjects: “…classification algorithm, depression prediction, machine learning, model development, model evaluation…”
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Application of bioinspired global optimization algorithms to the improvement of the prediction accuracy of compact extreme learning machines by L. A. Demidova, A. V. Gorchakov

“…The obtained results showed that the prediction accuracy of ELMs can be improved by using bioinspired algorithms for the intelligent adjustment of input weights. …”
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Online Prediction and Correction of Static Voltage Stability Index Based on Extreme Gradient Boosting Algorithm by Huiling Qin, Shuang Li, Juncheng Zhang, Zhi Rao, Chengyu He, Zhijun Chen, Bo Li

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A comprehensive review of predictive analytics models for mental illness using machine learning algorithms by Md. Monirul Islam, Shahriar Hassan, Sharmin Akter, Ferdaus Anam Jibon, Md. Sahidullah

“…This study reviews the machine learning models, algorithms, and applications for the early detection of mental disease, particularly emphasizing the data modalities. …”
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Prediction method of soil water content based on SVM optimized by improved salp swarm algorithm by Xiaoqiang ZHAO, Fan YANG, Zhufeng YAN

Subjects: “…soil water content prediction;support vector machine;salp swarm algorithm;opposition-based learning;chaotic optimization…”
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Optimized machine learning algorithms with SHAP analysis for predicting compressive strength in high-performance concrete by Samuel Olaoluwa Abioye, Yusuf Olawale Babatunde, Oluwafikejimi Abigail Abikoye, Aisha Nene Shaibu, Bailey Jonathan Bankole

“…Abstract This research examines the application of eight different machine learning (ML) algorithms for predicting the compressive strength of high-performance concrete (HPC). …”
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Predicting anti-cancer drug sensitivity through WRE-XGBoost algorithm with weighted feature selection by Yiyao Jiang, Ming Chen, Zhongmin Xiong, Yufang Qin

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Prediction of Acute Kidney Injury for Critically Ill Cardiogenic Shock Patients with Machine Learning Algorithms by Zhang X, Xiong Y, Liu H, Liu Q, Chen S

“…Five machine learning algorithms (LightGBM, decision tree, XGBoost, random forest, and ensemble model) and one conventional logistic regression were applied for the prediction of AKI in critically ill individuals with CS. …”
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Predictive machine learning algorithm for COPD exacerbations using a digital inhaler with integrated sensors by Michael Reich, Njira Lugogo, Laurie D Snyder, Megan L Neely, Guilherme Safioti, Randall Brown, Michael DePietro, Roy Pleasants, Thomas Li, Lena Granovsky

“…This analysis aimed to determine if a machine learning algorithm capable of predicting impending exacerbations could be developed using data from an integrated digital inhaler.Patients and methods A 12-week, open-label clinical study enrolled patients (≥40 years old) with COPD to use ProAir Digihaler, a digital dry powder inhaler with integrated sensors, to deliver their reliever medication (albuterol, 90 µg/dose; 1–2 inhalations every 4 hours, as needed). …”
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Predicting transmembrane helix packing arrangements using residue contacts and a force-directed algorithm. by Timothy Nugent, David T Jones

“…Finally, we employ a force-directed algorithm to construct the optimal helical packing arrangement which demonstrates success for proteins containing up to 13 transmembrane helices. …”
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Safety-critical nonlinear optimal predictive control with adaptive error elimination algorithm for robotic system by Wang Helin

Subjects: “…nonlinear optimal predictive control…”
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PREDICTION OF TBM OIL TEMPERATURE BY IMPROVED CAMEL ALGORITHM ASSISTED RANDOM FOREST MODEL (MT) by REN JianJi, ZHAO RunQiu, WANG ZhenXi, LIU YuMing, YUAN YongLiang

Subjects: “…Improved camel algorithm…”
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A Surrogate-Assisted Gray Prediction Evolution Algorithm for High-Dimensional Expensive Optimization Problems by Xiaoliang Huang, Hongbing Liu, Quan Zhou, Qinghua Su

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Predicting stunting status among under five children in ethiopia using ensemblemachine learning algorithms by Misganaw Ketema Ayele, Getachew Alemu Baye, Seid Hassen Yesuf, Abebaw Agegne Engda, Eshetie Teka Mitiku

“…This study overcame a key limitation in previous stunting prediction models by developing a multi-class classification model that predicts stunting severity (severe, moderate, normal) using Ethiopia’s nationally representative EDHS data from 2011 to 2016. …”
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Research and Application of Denitrification Optimal Control Based on Multi-Variable Generalized Predictive Control Algorithms by Xiaodong ZHANG, Pengfei WANG, Le LIU

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