Research on the deformation prediction model of surrounding rock based on SSA-VMD-GRU by Xiao Jiming, Guo Hongyan, Guo Huajun, Hu Juyi, Zhang Zhongzhe

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Short-term Power Prediction of Photovoltaic Power Generation Based on LSTM and Error Correction by ZHU Tao, LI Junwei, ZHU Yuanfu, YE Zhiming, TANG Yi

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Evaluation of Eight Decomposition-Hybrid Models for Short-Term Daily Reference Evapotranspiration Prediction by Yunfei Chen, Zuyu Liu, Ting Long, Xiuhua Liu, Yaowei Gao, Sibo Wang

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

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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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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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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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Using a seasonal and trend decomposition algorithm to improve machine learning prediction of inflow from the Yellow River, China, into the sea by Shuo Wang, Shuo Wang, Ke Yang, Ke Yang, Hui Peng, Hui Peng

“…Time decomposition algorithms, combined with machine learning, are effective tools to enhance the capabilities of inflow prediction models. …”
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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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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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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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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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Spatial-temporal evolution characteristics and driving factors of carbon emission prediction in China-research on ARIMA-BP neural network algorithm by Sanglin Zhao, Zhetong Li, Hao Deng, Xing You, Jiaang Tong, Bingkun Yuan, Zihao Zeng

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Exploring explainable machine learning algorithms to model predictors of tobacco use among men in Sub Sahara Africa between 2018 and 2023 by Mequannent Sharew Melaku, Nebebe Demis Baykemagn, Lamrot Yohannes, Adem Tsegaw Zegeye

“…STATA version 17 was used for data cleaning and descriptive statistics, while Python 3.9 was employed for machine learning predictions. The study utilized several machine learning models, including Decision Tree, Logistic Regression, Random Forest, KNN, eXtreme Gradient Boosting (XGBoost), and AdaBoost, to identify the key predictors of tobacco use among men. …”
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