Performance evaluation and comparative analysis of different machine learning algorithms in predicting postnatal care utilization: Evidence from the ethiopian demographic and health survey 2016. by Daniel Niguse Mamo, Agmasie Damtew Walle, Eden Ketema Woldekidan, Jibril Bashir Adem, Yosef Haile Gebremariam, Meron Asmamaw Alemayehu, Ermias Bekele Enyew, Shimels Derso Kebede

“…This research aims to evaluate and compare the effectiveness of machine learning algorithms in predicting postnatal care utilization in Ethiopia and to identify the key factors involved. …”
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Predicting the tensile properties of heat treated and non-heat treated LPBFed AlSi10Mg alloy using machine learning regression algorithms by Vijaykumar S. Jatti, A. Saiyathibrahim, Arvind Yadav, Murali Krishnan R., B. Jayaprakash, Sumit Kaushal, Vinaykumar S. Jatti, Ashwini V. Jatti, Savita V. Jatti, Abhinav Kumar, Soumaya Gouadria, Ebenezer Bonyah

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How can we predict transportation stock prices using artificial intelligence? Findings from experiments with Long Short-Term Memory based algorithms by Dinar Ajeng Kristiyanti, Willibrordus Bayu Nova Pramudya, Samuel Ady Sanjaya

“…It employs the Long Short-Term Memory (LSTM) algorithm, assessing different hyperparameter activation functions (linear, ReLU, sigmoid, tanh) and optimizers (ADAM, ADAGRAD, NADAM, RMSPROP, ADADELTA, SGD, ADAMAX) to refine prediction accuracy. …”
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Development and validation of a prediction model for coronary heart disease risk in depressed patients aged 20 years and older using machine learning algorithms by Yicheng Wang, Yicheng Wang, Yicheng Wang, Chuan-Yang Wu, Hui-Xian Fu, Jian-Cheng Zhang, Jian-Cheng Zhang, Jian-Cheng Zhang

“…Several evaluation metrics were employed to assess and compare the performance of eight different machine learning models, aiming to identify the most effective algorithm for predicting coronary heart disease risk in individuals with depression. …”
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Geometric Degree Reduction of Wang–Ball Curves by Yusuf Fatihu Hamza, Mukhtar Fatihu Hamza, Abedallah Rababah, Salisu Ibrahim

“…In this paper, an approximate geometric multidegree reduction algorithm of Wang–Ball curves is proposed. …”
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Reduction to master integrals and transverse integration identities by Vsevolod Chestnov, Gaia Fontana, Tiziano Peraro

“…We describe a proof-of-concept implementation of the application of transverse integration identities in the context of integral reduction. We include some applications to cutting-edge integral families, showing significant improvements over traditional algorithms.…”
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Prediction of old goaf residual subsidence integrating EDS-InSAR with EsLSTM in the Loess Plateau, China by Fei Ma, Fei Ma, Qingbin Zhang, Lichun Sui

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Early Detection of Congenital Heart Diseases among Infants Using Artificial Neural Network Algorithm by Lucy Ifeyinwa Ezigbo, Anthony Kwubeghari, Francis Okoye

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Training and inference Time Efficiency Assessment Framework for machine learning algorithms: A case study for hyperspectral image classification by Xiaorou Zheng, Jianxin Jia, Shoubin Dong, Yawei Wang, Runuo Lu, Yuwei Chen, Yueming Wang

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A Modified Kalman Filter Based on Radial Basis Function Neural Networks for the Improvement of Numerical Weather Prediction Models by Athanasios Donas, George Galanis, Ioannis Pytharoulis, Ioannis Th. Famelis

“…This study introduces a novel enhancement to the Kalman filter algorithm by integrating it with Radial Basis Function neural networks to improve numerical weather prediction models. …”
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Intelligent Photolithography Corrections Using Dimensionality Reductions by Parag Parashar, Chandni Akbar, Tejender S. Rawat, Sparsh Pratik, Rajat Butola, Shih H. Chen, Yung-Sung Chang, Sirapop Nuannimnoi, Albert S. Lin

“…In this work, we use dimensionality reduction (DR) algorithms to reduce the computation time of complex OPC/EPC problems while the prediction accuracy is maintained. …”
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Multiscale Feature Modeling and Interpretability Analysis of the SHAP Method for Predicting the Lifespan of Landslide Dams by Zhengze Huang, Yuqi Bai, Hengyu Liu, Yun Lin

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Optimizing Solar Radiation Prediction Based on The Internet of Things Platform in Photovoltaic Power Plant by Neda Ashrafi Khozani, Maryam Mahmoudi, Shabnam Nasr Esfahani

“…Managers and designers encounter economic and managerial challenges due to the uncertainty and difficulty in predicting solar radiation levels. This research introduces a highly accurate prediction method utilizing tree-based methods, enhanced by meta-heuristic algorithms to boost performance. …”
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GAN data reconstruction based prediction method of telecom subscriber loss by Kehong A, Xiaodong HU

“…Users are the core of operators’ interests.With the introduction of the policy of transferring network with a number, the competition between operators becomes more and more fierce.In order to accurately predict subscriber loss tendency in advance, a prediction method of subscriber loss based on generative adversarial network data reconstruction was proposed.Firstly, the dirty data in the telecom subscriber loss data was used by effective data preprocessing method.Secondly, the GAN was used to reconstruct the telecom subscriber loss data to solve the problem of the imbalance of the telecom subscriber loss data.Finally, extreme gradient boosting algorithm was used to train the telecom subscriber loss prediction model based on GAN reconstruction and the SMOTE sampling model based on synthetic minority oversampling technique sampling method respectively, and compare the prediction accuracy of the two models.The experimental results show that the prediction accuracy of the GAN reconstructed telecom subscriber loss prediction model is increased by 6.75%, the accuracy rate is increased by 25.91%, the recall rate is increased by 30.91%, and the F1-score is increased by 28.73% compared with the unreconstructed prediction model.This method can effectively improve the accuracy of telecom subscriber loss prediction.…”
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An Ensemble Model for Predicting Cardiovascular Disease utilizing Nature Inspired Optimization by Annwesha Banerjee Majumder, Somsubhra Gupta, Sourav Majumder, Dharmpal Singh

“… This paper represents an efficient model for heart disease prediction model utilizing an ensemble mechanism optimized through BAT algorithm. …”
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Dissolved Oxygen Prediction Based on SOA-SVM and SOA-BP Models by ZHANG Xuekun

Subjects: “…dissolved oxygen prediction…”
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Efficient Ensemble Learning-Based Models for Plastic Hinge Length Prediction of Reinforced Concrete Shear Walls by Naser Safaeian Hamzehkolaei, Mohammad Sadegh Barkhordari

“…This study aims to develop practical machine-learning (ML) models for PHL prediction of RCSWs. For this purpose, 721 data of nonplanar and rectangular RCSWs were utilized. …”
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Predicting cardiovascular outcomes in Chinese patients with type 2 diabetes by combining risk factor trajectories and machine learning algorithm: a cohort study by Qi Huang, Xiantong Zou, Zhouhui Lian, Xianghai Zhou, Xueyao Han, Yingying Luo, Shuohua Chen, Yanxiu Wang, Shouling Wu, Linong Ji

“…Conclusions The ML-CVD-C model, incorporating dynamic cardiovascular risk trajectories and a machine learning algorithm, significantly improves risk prediction accuracy for Chinese patients with diabetes. …”
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Methodology of optimal distribution of single-phase electric consumers in power supply systems by the criterion of reduction of additional losses caused by load asymmetry and non-s... by A. A. Pesterev, S. S. Kostinskiy, N. D. Narakidze

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Pressure Control in the Pump-Controlled Hydraulic Die Cushion Pressure-Building Phase Using Enhanced Model Predictive Control with Extended State Observer-Genetic Algorithm Optimization by Zhikui Dong, Song He, Yi Liao, Heng Wang, Mingxing Song, Jinpei Jiang, Gexin Chen

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