Hubungan Pacaran Terhadap Perilaku Seks Pranikah Pada Remaja Di Kecamatan Tanjung Sakti Pumi Kabupaten Lahat by Dia Islami Putri

“…Data analysis used quantitative analysis using validity test, reliability test, normality test, linearity test and hypothesis testing. …”
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Water saturation modeling in carbonate reservoirs using the bulk volume water approach by Ali Behdad, Steve Cuddy

“…A MATLAB Graphical User Interface (GUI) was designed to facilitate computations, including back-calculating capillary pressure (Pc) curves for comparison with input data and conducting error analysis. BVW is determined as the product of porosity and saturation at each Pc curve pressure step across a porosity range of 0.04 to 0.35. …”
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SPATIAL INTERPOLATION OF RAINFALL INTENSITY IN JAVA ISLAND USING ORDINARY KRIGING by Shabira A. Auliyazhafira, Fariza A. Putri, Theresia S. Nauli, Aulia R. Al Madani, I Gede Nyoman Mindra Jaya, Annisa N. Falah, Budi Nurani Ruchjana

“…The Kriging equation obtained can provide highly accurate prediction results on the test data with a MAPE (Mean Absolute Percentage Error) error measure of 4.85% and RMSE (Root Mean Square Error) of 18.17, which indicates that the prediction results obtained are highly accurate predictions.…”
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Comparative study of quality estimation of binary classification by V. V. Starovoitov, Yu. I. Golub

“…The paper describes results of analytical and experimental analysis of seventeen functions used for evaluation of binary classification results of arbitrary data. …”
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The Role of Organisational Culture and Situational Factors in Predicting Workplace Deviation Among Public Employees by Benjamin Adegboyega OLABIMITAN, Sunday Samson BABALOLA

“…Design/methodology/approach – The study employed a quantitative approach using a cross-sectional survey design to collect data from 430 participants; the analysis included regression analysis and structural equation modelling to examine the mediating effect of organisational culture. …”
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Mortality Prediction in COVID-19 Using Time Series and Machine Learning Techniques by Tanzina Akter, Md. Farhad Hossain, Mohammad Safi Ullah, Rabeya Akter

“…To predict the death rate in the seven countries that were chosen, the data were analyzed using time series analysis and machine learning techniques. …”
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Novel cost-effective method for forecasting COVID-19 and hospital occupancy using deep learning by Nabil I. Ajali-Hernández, Carlos M. Travieso-González

“…This results in a long-term prediction where each day we can query the cases for the next three days with very little data. The data utilized in this analysis were obtained from the “Hospital Insular” in Gran Canaria, Spain. …”
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Prediction of Poisson's ratio for a petroleum engineering application: Machine learning methods. by Fahd Saeed Alakbari, Syed Mohammad Mahmood, Mohammed Abdalla Ayoub, Muhammad Jawad Khan, Funsho Afolabi, Mysara Eissa Mohyaldinn, Ali Samer Muhsan

“…The proposed models were created based on a large data of 1691 datasets from different countries. The best-performing model of the nineteen models was selected and further enhanced using various approaches such as trend analysis to improve the model's performance and robustness as some models show high accuracy but show incorrect relationships between the inputs and output because the machine learning model only built based on the data and do not consider the physical behavior of the model. …”
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A novel ensemble ARIMA‐LSTM approach for evaluating COVID‐19 cases and future outbreak preparedness by Somit Jain, Shobhit Agrawal, Eshaan Mohapatra, Kathiravan Srinivasan

“…This research article conducts a time series analysis of COVID‐19 data across various countries, including India, Brazil, Russia, and the United States, with a particular emphasis on total confirmed cases. …”
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Accuracy fluctuations of ICESat-2 height measurements in time series by Xu Wang, Xinlian Liang, Weishu Gong, Pasi Häkli, Yunsheng Wang

“…Its key product, Land and Vegetation Height (ATL08), offers global land and vegetation height data for carbon budget and cycle modeling. Consistent measurement accuracy of ATL08 is crucial for reliable time series analysis. …”
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Iron Ore Information Extraction Based on CNN-LSTM Composite Deep Learning Model by Haili Chen, Mengxiang Xia, Yaping Zhang, Ruonan Zhao, Bingran Song, Yang Bai

“…Magnetite collected from an iron ore mine in the Tangshan area is used as a pilot study, and its spectral data are used as the data source. The raw spectra are preprocessed Savitzky-Golay smoothing, jump point correction, and envelope removal. …”
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Thermal Runaway Warning of Lithium Battery Based on Electronic Nose and Machine Learning Algorithms by Zilong Pu, Miaomiao Yang, Mingzhi Jiao, Duan Zhao, Yu Huo, Zhi Wang

“…Initially, principal component analysis (PCA) was used to visualise the clustering of the three target gas samples at room temperature, providing a preliminary data analysis. …”
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Inference for the treatment effect in staircase designs with continuous outcomes: a simulation study by Ehsan Rezaei-Darzi, Kelsey L. Grantham, Andrew B. Forbes, Jessica Kasza

“…The impact on inference for the treatment effect when misspecifying the intracluster correlation structure is assessed through considering performance metrics including bias and 95% confidence interval coverage. Results Data analysis assuming an exchangeable correlation structure and application of the Satterthwaite correction controls Type I error well when the correlation structure is correctly specified, and there are a sufficient number of clusters. …”
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Evaluating the performance of artificial intelligence models for temperature downscaling (Study area: Ardabil province) by Mohammad Hossein Jahangir, Seyed Mohammad Ehsan Azimi

“…These tools downscale forecasting scenarios by creating relationship between parameters of synoptic stations and Large-scale data of general circulation models.Material and methods: In this study large-scale predictor parameters from 1961 to 2003 from the database of National Centers for Environmental Prediction (NCEP), large-scale data for the A1B and A2 forecast scenarios of the HadCM3 model from 2001 to 2100 from the Canadian Centre for Climate Modelling and Analysis (CCCMA), and the meteorological synoptic data of Ardabil stations from the Meteorological Organization were gathered. …”
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Crude Oil and Hot-Rolled Coil Futures Price Prediction Based on Multi-Dimensional Fusion Feature Enhancement by Yongli Tang, Zhenlun Gao, Ya Li, Zhongqi Cai, Jinxia Yu, Panke Qin

“…Experimental results demonstrate that the MDFFE model excels in various metrics, including mean absolute error, root mean square error, mean absolute percentage error, coefficient of determination, and sum of squared errors. …”
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Research on subway settlement prediction based on the WTD-PSR combination and GSM-SVR model by Miren Rong, Chao Feng, Yinping Pang, Hailong Wang, Ying Yuan, Wensong Zhang, Lanxin Luo

“…By upgrading the one-dimensional settlement data sequence to a multi-dimensional data sequence, and utilizing the Grid Search Method Optimized Support Vector Regression (GSM-SVR) regression model to predict subway settlement with small sample data, the aim is to offer a more precise and reliable data analysis method and theoretical approach for small sample subway settlement prediction. …”
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Adaptive zero velocity correction method for fiber optic inertial navigation system in coal mining roadheader by Qinghua MAO, Qing ZHOU, Jianquan CHAI, Yanzhang CHEN, Wenjuan YANG, Xusheng XUE

“…Secondly, the time-frequency domain features of IMF components are extracted, and the principal component analysis method is used to reduce the dimension to reduce the complexity of the diagnostic model and the difficulty of data analysis. …”
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Research on the Nowcasting Method of Solar Energy Resources Base on FY-4A Ground Radiation Products by Dong YE, Jinqiu LIANG, Yanbo SHEN, Chuanhui WANG, Rui CHANG

“…Based on the ground incident radiation data of FY-4A and the radiation data of ground weather station， the nowcasting method based on mean generation function is used to obtain the forecast radiation， as well as its rolling correction.Taking Taiyuan station in Shanxi Province as an example， the experiment in 2019 shows that the high spatial-temporal resolution radiation related products provided by the new generation geostationary meteorological satellite FY-4A can provide relatively reliable initial conditions for nowcasting prediction； The nowcasting forecast based on satellite radiation products captures the impact of weather changes， and the revised nowcasting forecast radiation has been effectively improved； In sunny days， the maximum deviation of nowcasting forecast global radiation is improved from about 120 W·m-2 before correction to about 40 W·m-2 after correction.In cloudy days， the average absolute error decreases to 14 W·m-2.In cloudy days， the average absolute error decreases to 56 W·m-2.According to the comprehensive statistical analysis of 16 prediction time steps without considering temporal variation， the corrected nowcasting global radiation and observed global radiation are coincided very well at each prediction time step， the relative error decreased from 44.7%~66.4% to 21.3%~54.3%， and the RMSE decreased from 166.4~198.8 W·m-2 to 132.2~189.9 W·m-2； From the comprehensive statistical analysis of the whole year， the revised correlation coefficient is generally higher than that before the revision， increased from 0.77~0.84 to 0.79~0.88， only slightly decreased at 15 hour， the RMSE decreased from 162.7~197.1 W·m-2 to 129.3~180.9 W·m-2， and the average absolute relative error decreased from 46.0%~76.8% to 24.0%~46.5%.This method can be used for nowcasting prediction of the whole disk at any time.…”
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Prognostic machine learning models for thermophysical characteristics of nanodiamond-based nanolubricants for heat pump systems by Ammar M. Bahman, Emil Pradeep, Zafar Said, Prabhakar Sharma

“…Furthermore, in the extrapolation analysis, despite changes in oil grade and nanolubricant concentrations, the GPR-based model showed a maximum absolute error (AE) of 19% compared to non-trained experimental data. …”
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Development of an upper limb muscle strength rehabilitation assessment system using particle swarm optimisation by Chuangan Zhou, Siqi Wang, Meiyi Wu, Wei Lai, Junyu Yao, Xingyue Gou, Hui Ye, Jun Yi, Dong Cao

“…Machine learning models, including Backpropagation Neural Network (BPNN), Support Vector Machines (SVM), and particle swarm optimization algorithms (PSO-BPNN, PSO-SVR), were applied for regression analysis. Model performance was evaluated using R-squared (R2), Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Mean Bias Error (MBE).ResultsThe system successfully collected electromyographic and kinematic data. …”
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