Empowering data-driven load forecasting by leveraging long short-term memory recurrent neural networks by Waqar Waheed, Qingshan Xu, Muhammad Aurangzeb, Sheeraz Iqbal, Saadat Hanif Dar, Z.M.S. Elbarbary

“…The LSTM-RNN model has outstanding accuracy, with a Mean Absolute Percentage Error (MAPE) of 1.5% and a Root Mean Squared Error (RMSE) of 26.5 for hourly forecasts. …”
Get full text

Underground Personnel Positioning Method Based on Self-training and NLOS Suppression by SHAO Xiaoqiang, HAN Zehui, MA Bo, YANG Yongde, YUAN Zewen, LI Xin

“…[Purposes] The research of precise location of underground personnel in coal mine is of great significance to protect their life safety. …”
Get full text

A Novel Closed-Loop Deep Learning-Based Smart Infusion Rate Monitoring Technique for Safe Intravenous Medication Administration by Subrata Bhattacharjee, Gun Ho Kim, Hongje Lee, Kyoung Won Nam

Get full text

Short-Term Daily Univariate Streamflow Forecasting Using Deep Learning Models by Eyob Betru Wegayehu, Fiseha Behulu Muluneh

“…Hydrological forecasting is one of the key research areas in hydrology. Innovative forecasting tools will reform water resources management systems, flood early warning mechanisms, and agricultural and hydropower management schemes. …”
Get full text

Inversion Method for Permitting Loadings of Pollutant from Lateral Effluents Based on Adjoint Equations by SHI Xiaoyan, ZHANG Hong, TAO Chunhua, LU Lingjiang, WAN Xin, LIU Zhaowei

“…The simulation of the forward problem establishes the foundation for solving the inverse problem. This research focuses on an outlet from a sewage treatment facility located in the upper reaches of the Yangtze River to evaluate the hydrodynamic and water quality model. …”
Get full text

Forecasting cryptocurrency returns using classical statistical and deep learning techniques by Nehal N. AlMadany, Omar Hujran, Ghazi Al Naymat, Aktham Maghyereh

“…The results indicate that all models exhibit high accuracy, as evidenced by their low root mean square error (RMSE), mean absolute error (MAE), and mean squared error (MSE) values. …”
Get full text

Spatial distribution and reserve estimation of sand and gravel deposits using geostatistical methods in west Basrah, southern Iraq by Safaa Al-Ali, Sattar Al-Khafaji

“…Data validation using the mean error (ME) and root-mean-square error (RMSE) were applied. …”
Get full text

Positioning with Chinese DTMB Signal under Complex Urban Environments by T. Zhou, L. Chen

“…The pedestrian experiment results show that the 1 − σ ranging error from the carrier phase is about 0.94m. The on-vehicle experiment results show that the 1 − σ positioning error in the eastward is about 9.07m, and the 1 − σ positioning error in the northward is about 7.74m. …”
Get full text

Predicting patient visits at the psychiatric polyclinic of a public hospital in Bali, Indonesia: A forecasting approach using single exponential smoothing by Ni Made Ratih Comala Dewi Dewi, Putu Cintariasih, Ni Wayan Suryani, Luh Gde Nita Sri Wahyuningsih

“…Forecasting accuracy was assessed using Root Mean Squared Error (RMSE) and Mean Absolute Percentage Error (MAPE), with forecasts for 2024–2026 generated for monthly patient visits. …”
Get full text

An Auto-Adjusting Algorithm to Enhance Indoor Localization Accuracy: A Real-Time Experimental Analysis by Othman A. Alfahad, Husham Saied, Emad Malaekah, Ahmed Al Rashdi, Mohammed Emam, Mohsen Bakouri

Get full text

Estimation of Evaporation Rate Using Advanced Methods by Mohammed Falah Allawi, Uday Hatem Abdulhameed, Mohammed Freeh Sahab, Sadeq Oleiwi Sulaiman

“…Several statistical indicators have been used to evaluate the prediction results which are root mean square error (RMSE), Nash-Sutcliffe efficiency (NSE), mean absolute error (MAE), and correlation (R2) the prediction accuracy. …”
Get full text

PERFORMANCE PREDICTION OF ROADHEADERS USING SUPPORT VECTOR MACHINE (SVM), FIREFLY ALGORITHM (FA) AND BAT ALGORITHM (BA) by Arash Ebrahimabadi, Alireza Afradi

“…Additionally, this study employed Firefly Algorithm (FA), Bat Algorithm (BA) and Support Vector Machine (SVM), which were assessed using coefficient of determination (R²), root mean square error (RMSE), mean squared error (MSE) and mean absolute error (MAE).The obtained results for Firefly Algorithm (FA) are found to be as R2 = 0.9104, RMSE = 0.0658, MSE= 0.0043 and MAE= 0.0039, for Bat Algorithm (BA) are found to be as R2 = 0.9421, RMSE = 0.0528, MSE= 0.0027 and MAE= 0.0024, and for Support Vector Machine (SVM) are found to be as R2 = 0.8795, RMSE = 0.0762, MSE= 0.0058 and MAE= 0.0052, respectively. …”
Get full text

Enhancing AI-driven forecasting of diabetes burden: a comparative analysis of deep learning and statistical models by Rasool Esmaeilyfard, Mohsen Bayati

Get full text

Prediction of mechanical characteristics of shearer intelligent cables under bending conditions. by Lijuan Zhao, Dongyang Wang, Guocong Lin, Shuo Tian, Hongqiang Zhang, Yadong Wang

“…The results show that, compared to other predictive models, the proposed model achieves reductions in Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Mean Absolute Error (MAE) to 0.0002, 0.0159, and 0.0126, respectively, with the coefficient of determination (R2) increasing to 0.981. …”
Get full text

Performance Evaluation of CMIP6-GCMs Using Three Spatial Interpolation Methods Over Catchment Area of Koyna Reservoir, India by Sucheta Dumbre, Pradnya Dixit, Shreenivas Londhe

Get full text

Inversion Method for Permitting Loadings of Pollutant from Lateral Effluents Based on Adjoint Equations by SHI Xiaoyan, ZHANG Hong, TAO Chunhua, LU Lingjiang, WAN Xin, LIU Zhaowei

“…The simulation of the forward problem lays the groundwork for the inverse problem. This research focuses on an outlet from a sewage treatment facility in the upper reaches of the Yangtze River to assess the hydrodynamic and water quality model. …”
Get full text

Optimized control techniques for enhancing the buck converter performance in lithium-ion battery charging by Anitha K, Balamurugan Parandhaman

Get full text

NeuMoDx random access molecular diagnostic system for detection and quantification of hepatitis B virus in clinical samples by Ayse Arikan, Murat Sayan, Osman Doluca

Get full text

Automatic assessment of lower limb deformities using high-resolution X-ray images by Reyhaneh Rostamian, Masoud Shariat Panahi, Morad Karimpour, Alireza Almasi Nokiani, Ramin Jafarzadeh Khaledi, Hadi Ghattan Kashani

Get full text

Intra‐ and inter‐session reliability and repeatability of 1H magnetic resonance spectroscopy for determining total creatine concentrations in multiple brain regions by Jedd Pratt, James McStravick, Aneurin J. Kennerley, Craig Sale

“…We provide new minimum detectable change data for tCr concentrations, a detailed discussion of the inherent error sources in repeated 1H MRS, including the substantial effect of the analysis package on tCr quantification, and suggestions for how these should be managed to improve the interpretability and clinical value of future research. …”
Get full text