An improved calibration method for magnetic sensor of multipoint inclinometer by Yi ZHANG

“…In order to improve the calibration accuracy of the inclinometer and its adaptability to random errors, aiming at the problems that the current multi-position calibration method of the inclinometer does not consider the effect of symmetry on error reduction, the measurement error is introduced in angle rotation correction, and the calibration time is reduced, a multi-point calibration and error simulation method is first established. …”
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NUMERICAL METHOD FOR ESTIMATION OF TENSILE LOAD IN TIE-RODS by Kseniia Riabova, Luca Collini, Rinaldo Garziera

“…Qualitative analysis of the results showed a significant reduction of the error compared to models with different boundary conditions. …”
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High-Precision Control of Control Moment Gyroscope Gimbal Servo Systems via a Proportional–Integral–Resonant Controller and Noise Reduction Extended Disturbance Observer by Zhihao Lu, Zhong Wu

“…To suppress the effects of these complex disturbances on speed control accuracy, a control method based on a proportional–integral–resonant (PIR) controller and a noise reduction extended disturbance observer (NREDO) is proposed in this paper. …”
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A Self-Evaluated Bilingual Automatic Speech Recognition System for Mandarin–English Mixed Conversations by Xinhe Hai, Kaviya Aranganadin, Cheng-Cheng Yeh, Zhengmao Hua, Chen-Yun Huang, Hua-Yi Hsu, Ming-Chieh Lin

“…These findings highlight the importance of a well-designed system to manage the complexities of mixed-language speech recognition, offering a promising method for building a bilingual ASR system using existing monolingual models. …”
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A speech recognition method with enhanced transformer decoder by Hengbo Hu, Tong Niu, Zhenhua He

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Improvement of methodical tools of the seasonal transportation irregularity assessment by D. A. Macheret, A. Yu. Ledney

“…This issue negatively affects operation of the railway transport as higher irregularity of transportation means limitation of the overall volume that can be realized within a year, which results in reduction of effectiveness of the industry resources use.When assessing the seasonal irregularity of transportation by means of the method, significant error takes place due to different number of days in the months. …”
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NORMALISATION OF THE DRIVE PRECISION OF METAL-CUTTING MACHINES by Irina A. Klenova, Dmitry A. Rudikov, Svetlana N. Kholodova

“…The presented complex helps to reveal the role of the rounding error of the output criteria in the formation of the general relative error and provides a basis for its possible reduction. …”
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Optimizing Models and Data Denoising Algorithms for Power Load Forecasting by Yanxia Li, Ilyosbek Numonov Rakhimjon Ugli, Yuldashev Izzatillo Hakimjon Ugli, Taeo Lee, Tae-Kook Kim

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Generative autoencoder to prevent overregularization of variational autoencoder by YoungMin Ko, SunWoo Ko, YoungSoo Kim

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Groundwater Pollution Concentration Estimation with Modified Kalman Filter Method by Nenik Estuningsih, Fatmawati Fatmawati

“…The model order reduction method used in this research is the LMI (Linear Matrix Inequality) method because the model reduction error using the LMI method is the smallest error compared to the reduction error using the Balanced Truncation method or the Singular Pertrubation Approximation method. …”
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Micro-parameter Optimization of Helical Cylindrical Gear based on Romax by Hongfu Xing, Chaohui Yang, Nan Yu, Chao Xu, Jingliang Jiang

“…In the gearbox of main reduction helical cylindrical gear as the research object，by using Romax software，the gearbox model is established，combining the theory of microscopic parameters optimization of cylindrical bevel wheel，the transmission error，distribution of load per unit length of gear tooth surface and the contact spot are taken as the optimization objectives for microscopic gear modification，an omnidirectional modification method combining helical modification and tooth profile modification is proposed. …”
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Introducing an Evolutionary Method to Create the Bounds of Artificial Neural Networks by Ioannis G. Tsoulos, Vasileios Charilogis, Dimitrios Tsalikakis

“…This text proposes the incorporation of a three-stage evolutionary technique, which has roots in the differential evolution technique, for the effective training of the parameters of artificial neural networks and the avoidance of the problem of overfitting. The new method effectively constructs the parameter value range of the artificial neural network with one processing level and sigmoid outputs, both achieving a reduction in training error and preventing the network from experiencing overfitting phenomena. …”
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A Hybrid GARCH and Deep Learning Method for Volatility Prediction by Hailabe T. Araya, Jane Aduda, Tesfahun Berhane

“…The model’s forecasting performance was assessed using key evaluation metrics, including mean absolute error (MAE) and root mean squared error (RMSE). Compared to other hybrid models, our new proposed hybrid model demonstrates an average reduction in MAE and RMSE of 60.35% and 60.61%, respectively. …”
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Battery Life Evaluation Method Based on Temporal Convolution Network by SUN Yushu, AN Juan, HUANG Cunqiang, ZHANG Shunzhen, DANG Yanyang, PEI Wei, TANG Xisheng

“…Due to the different principles of these methods, their outcomes often diverge significantly. …”
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Establishing a generalized model for accurate prediction of higher heating values of substances with large ash fractions by Peng Jiang, Lin Li, Han Lin, Tuo Ji, Liwen Mu, Yuanhui Ji, Xiaohua Lu, Jiahua Zhu

“…This work proposed a novel HHV prediction model based on its reduction degree (DR) and ash content (Cash). First, ultimate analysis of biomass was applied to establish the calculation method of DR; then, the correlation between DR, Cash, and HHV was analyzed using the Pearson Correlation Coefficient; subsequently, the HHV = f (DR, Cash) model was developed using regression analysis. …”
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Adaptive neuro-fuzzy inference systems for improved mastitis classification and diagnosis by Javad Shirani Shamsabadi, Saeid Ansari Mahyari, Mostafa Ghaderi-Zefrehei

“…The results showed that the GD-ANFIS model integrated with the Pearson method demonstrated superior performance compared to PSO-ANFIS and GA-ANFIS across key evaluation metrics such as accuracy and error rates. …”
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Automatic target spraying and field evaluation of unstructured orchard based on millimeter-wave radar by Xing Xu, Jianying Li, Dongying Shen, Jieli Duan, Zhou Yang, Yinlong Jiang

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3D-CNN detection of systemic symptoms induced by different Potexvirus infections in four Nicotiana benthamiana genotypes using leaf hyperspectral imaging by Rizos-Theodoros Chadoulis, Ioannis Livieratos, Ioannis Manakos, Theodore Spanos, Zeinab Marouni, Christos Kalogeropoulos, Constantine Kotropoulos

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A Study on Improving of Adaptive Sensorless Control Performance via Funnel Control by Jun-Seo Han, Gyung-Jae Cho, Hyeon-Ji Jin, Geun-Ho Lee

“…This method is more accurate and stable than the existing methods when parameter errors exist. …”
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Tether Force Estimation Airborne Kite Using Machine Learning Methods by Akarsh Gupta, Yashwant Kashyap, Panagiotis Kosmopoulos

“…Our XGBoost model, for example, demonstrated a notable reduction in error in predicting the tether force that can be extracted at a particular location, with a root mean square error of 52.3 Newtons and a mean absolute error of 32.1 Newtons, coupled with a <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mi>R</mi><mn>2</mn></msup></semantics></math></inline-formula> error, which measures the proportion of variance explained by the model, achieved an impressive value of 0.93. …”
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