Peramalan Beban Jangka Panjang pada Gardu Induk Bangil dengan Metode Generalized Regression Neural Network by Ali Rizal Chaidir

“…The forecasting models' accuracy was gauged using Mean Absolute Percentage Error (MAPE) and Mean Absolute Error (MAE). The analysis indicates that Transformer 3 is projected to reach overload by August 2038, with a forecasted peak load of 1407.7465 A. …”
Get full text

A neural network approach to carbon emission prediction in industrial and power sectors by Syed Azeem Inam, Syed Muhammad Hassan Zaidi, Abdullah Ayub Khan, Sajid Ullah

“…A feedforward neural network (FFNN) model predicts pollution levels over the next 3 years, revealing the most affected countries and allowing proactive policy interventions. The model proposed in the present study achieves a Mean Squared Error (MSE) of 79.6%, a Root Mean Squared Error (RMSE) of 89.2%, and a Mean Absolute Error (MAE) of 75.8%, ensuring a reliable prognosis accuracy. …”
Get full text

An AI Approach to Markerless Augmented Reality in Surgical Robots by Abhishek Shankar, Luay Jawad, Abhilash Pandya

“…The results show a median error of 7 pixels (1.4 mm) when using a neural network, as compared to an error of 50 pixels (10 mm) when using a more traditional approach involving camera calibration and robot kinematics. …”
Get full text

Implementation of a therapeutic reconciliation procedure at admission by the emergency department by Elena Urbieta Sanz, Abel Trujilano Ruiz, Celia García-Molina Sáez, Sonia Galicia Puyol, Carmen Caballero Requejo, Pascual Piñera Salmerón

“…Greater compliance with risk criteria, polypharmacy and pluripathology were associated with present RE and prescription of high-risk medications with the need for intervention Conclusions: The application of TRP avoided any error in most of the patients. …”

Validity and reliability of the XSENSOR in-shoe pressure measurement system. by Daniel Parker, Jennifer Andrews, Carina Price

“…<h4>Significance</h4>Errors associated with the quantification of pressure are low enough that they are unlikely to influence the assessments of interventions or screening of the at-risk-foot considering clinically relevant thresholds. …”
Get full text

A novel ensemble ARIMA‐LSTM approach for evaluating COVID‐19 cases and future outbreak preparedness by Somit Jain, Shobhit Agrawal, Eshaan Mohapatra, Kathiravan Srinivasan

“…Conclusions The proposed ARIMA‐LSTM hybrid model outperforms ARIMA, GRU, LSTM, Prophet, and the ARIMA‐ANN hybrid model when evaluating using metrics like MAPE, symmetric mean absolute percentage error, and median absolute percentage error across all countries analyzed. …”
Get full text

Long short-term memory-based forecasting of influenza epidemics using surveillance and meteorological data in Tokyo, Japan by Daiki Koge, Daiki Koge, Keita Wagatsuma, Keita Wagatsuma

“…After model training, we assessed the predictive performance on an independent test dataset, using mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE), and Pearson’s correlation coefficient.ResultsDuring the study period, 1,445,944 influenza cases were analyzed. …”
Get full text

TBESO-BP: an improved regression model for predicting subclinical mastitis by Kexin Han, Yongqiang Dai, Huan Liu, Junjie Hu, Leilei Liu, Zhihui Wang, Liping Wei

“…The primary objective is to discern models by exhibiting higher predictive accuracy and lower error values.ResultsThe evaluation of the TBESO-BP model in the test phase reveals a coefficient of determination R2 = 0.94, a Mean Absolute Error (MAE) of 2.07, and a Root Mean Square Error (RMSE) of 5.33. …”
Get full text

The Neural Correlates and Behavioral Impact of Peripheral Noise Electrical Stimulation on Motor Learning by Li-Wei Chou, Man-Wai Kou, Hui-Min Lee, Felipe Fregni, Vincent Chen, Chung-Lan Kao

“…The differences (force error) between the actual and the targeted force were calculated, and motor learning was achieved by reducing the force error to a plateau. …”
Get full text

Neural Correlates of Growth Mindset: A Scoping Review of Brain-Based Evidence by Hang Zeng

“…A total of 15 studies were reviewed, revealing six primary research objectives: (1) neural mechanisms of error and feedback processing, (2) domain-specific mindsets, (3) neural changes resulting from mindset interventions, (4) mindsets and grit, (5) the neuroanatomy of mindsets, and (6) neural mechanisms of stereotype violation, with error and feedback processing being the most frequently investigated. …”
Get full text

Funding the future: Nigeria's battle against poverty through government expenditure by Temitope Adebayo

“…This study investigates the effectiveness of government expenditure in combating the incidence of poverty in Nigeria from 1981 to 2022, employing a Vector Error Correction Model (VECM) framework. The research analyzes the relationship between poverty incidence and key variables including government expenditure, GDP per capita, Agricultural Credit Guarantee Scheme Fund (ACGSF), and gross enrollment ratio in secondary education. …”
Get full text

Accurate prediction of college students' information anxiety based on optimized random forest and category boosting fusion model by Bin Wang, Li Shao

“…The results showed that the model integrating random forest and category boosting algorithm had the lowest mean absolute error and root mean squared error, which were 0.125 and 0.142. …”
Get full text

Analyzing and forecasting under-5 mortality trends in Bangladesh using machine learning techniques. by Shayla Naznin, Md Jamal Uddin, Ishmam Ahmad, Ahmad Kabir

“…Key metrics, including Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), R-squared, and Mean Absolute Percentage Error (MAPE), were employed to evaluate model performance. …”
Get full text

Enhancing agricultural commodity price forecasting with deep learning by R. L. Manogna, Vijay Dharmaji, S. Sarang

“…Furthermore, the Mean Absolute Percentage Error (MAPE) for GRU was notably lower, at 14.59% for onions and 10.58% for tomatoes. …”
Get full text

Analysis of the mechanism of physical activity enhancing well-being among college students using artificial neural network by Yuxin Cong, Roxana Dev Omar Dev, Shamsulariffin Bin Samsudin, Kaihao Yu

“…The results show that the proposed LSTM + CNN model has achieved significant improvement on the test set. Its mean absolute error is only 0.072, the mean square error is 0.00596, and the root mean square error is 0.077, which is remarkably superior to traditional machine learning methods such as random forest and support vector regression. …”
Get full text

Effect of artificial insemination, ruminal incubation, and esophageal tubing on cortisol concentration in blood of lactating dairy cows by Victoria Ferreira, Gonzalo Ferreira

“…We hypothesized that human interventions increase cortisol concentrations in dairy cow plasma. …”
Get full text

Criterion and Construct Validity of the Pocket-Worn RISE Device to Assess Movement Behaviour in Community-Dwelling People with Stroke by Camille F. M. Biemans, Laura van der Heiden, Cindy Veenhof, Olaf W. Verschuren, Johanna M. A. Visser-Meily, Martijn F. Pisters, Yvonne A. W. Hartman

“…The mean absolute percentage error and mean percentage error were below the predefined 20% threshold for SB and PA. …”
Get full text

Socio-economic inequalities in malaria prevalence among under-five children in Ghana between 2016 and 2019: a decomposition analysis by Marian Yaa Abrafi Edusei, Olufunke Alaba, Denis Okova, Amarech Obse

“…However, the concentration index for 2016 (Concentration Index = − 0.052; Standard Error = 0.044; p-value = 0.230) was not statistically significant. …”
Get full text

Prevalence and root causes of operating room fires in the United States 2014–2024 by Monica M. Attia

“…Intraoperative fires comprised the majority (35.6%). Operator error accounted for 37.8% of cases, with common errors including device mishandling (35.2%) and failure to detect damage (17.6%). …”
Get full text

The Reliability and Validity of a Clinical Measurement Proposed to Quantify Humeral Torsion by Paul A. Salamh, William J. Hanney, Lauren Champion, Connor Hansen, Kari Cochenour, Celine Siahmakoun, Morey J. Kolber

“… # Purpose The primary aim of this study is to determine the intrarater reliability and standard error of measurement (SEM) of the biceps forearm angle (BFA) measurement. …”
Get full text