Trajectory Tracking Control of Robot based on Improved Genetic Algorithm by Liu Yiyang, Liu Mingming

“…The motion track of the robot in the process of motion is influenced by small disturbance linear error,the robot system is a multi variable nonlinear control system,and in the traditional genetic algorithm for trajectory tracking control,the steady- state tracking error appearances in the boundary layer. …”
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Design a PID Controller for Suspension System by Back Propagation Neural Network by M. Heidari, H. Homaei

“…Training was continued until the mean squared error is less than . Desired error value was achieved in the BPN, and the BPN was tested with both data used and not used for training. …”
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X‐ray Spectroscopic Determination of Electrostatic Potential and Material Composition for Spacecraft: Experimental Results by K. T. Wilson, M. T. Bengtson, H. Schaub

“…The mean error in landing energy is found to be approximately 1%, and the mean error in estimated plate voltage is found to be within the uncertainty of the high voltage power supply. …”
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Quantitative Assessment of Brix in Grafted Melon Cultivars: A Machine Learning and Regression-Based Approach by Uğur Ercan, Ilker Sonmez, Aylin Kabaş, Onder Kabas, Buşra Calık Zyambo, Muharrem Gölükcü, Gigel Paraschiv

“…Established models were evaluated with Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Mean Square Error (MSE), Root Mean Square Error (RMSE), and Coefficient of Determination (R²) metrics. …”
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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. …”
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Enhancing DC Motor Speed Control Performance Using Heuristic Optimization and Comparative Analysis of Control Methods by Ali Öztürk, Nasser Bandar Nasser Al Saremi, Beytullah Bozali

“…The performances of the controllers were determined using criteria such as Integral of Absolute Error (IAE), Integral Squared Error (ISE), and Integral of Time multiplied by Absolute Error (ITAE). …”
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CYCLOTOMIC CLASSES IN THE NORMING DECODING BCH-CODES by D. N. Hoang, V. K. Konopelko

“…Norming decoding based on cyclotomic classes with main and subordinate norms is exanimated. It was found that all the norms of BCH codes and their error vector generators are the parts of complete cyclotomic classes. …”
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Predictability in process-based ensemble forecast of influenza. by Sen Pei, Mark A Cane, Jeffrey Shaman

“…These two types of errors are found to have qualitatively similar growth patterns during model integration, indicating that dynamic error growth, regardless of source, is a dominant component of forecast inaccuracy. …”
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Solar PV focused LFC studies utilizing an SFS-optimized PID with fractional derivative (PIDDμ), and incorporating BESS and FESS applications by S.B. Masikana, Gulshan Sharma, Sachin Sharma, Pitshou N. Bokoro, Emre Çelik

“…The results are compared with recent optimization-based LFC techniques across various scenarios. It is found that the SFS-PIDDμ achieves IAE=0.006786, ITSE=1.07e-05, and ITAE=0.01853, which are significantly lower than the error values produced by other LFC techniques. …”
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Advanced Machine Learning Approaches for Predicting Machining Performance in Orthogonal Cutting Process by Sabrina Al Bukhari, Salman Pervaiz

“…The performance of each model was evaluated based on error metrics such as the mean squared error (MSE) and R-squared values. …”
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Extending the forecasting horizon of daily new COVID-19 cases using non-pharmaceutical measures and the effective reproduction number (Rt): A deep learning-based framework by Tuga Mauritsius

“…The effectiveness of the predictive model was assessed using various metrics, such as Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), Mean Squared Error (MSE), Root Mean Square Error (RMSE), and Mean Absolute Scaled Error (MASE), which evaluates MAE relative to a baseline model. …”
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Efficacy of physically pretreated Mangifera indica biomass for Cu2+ and Zn2+ sequestration by Raziya Nadeem, Maida Ali Naqvi, Mubashir Hussain Nasir, Rashid Saeed, Tahira Iqbal, Muhammad Ashraf, Tariq Mehmood Ansari

“…To measure the goodness-of-fit error functions as sum of square error (SSE), chi-square (χ2) and residual root mean square error (RMSE) were used. …”
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Comparison of changes in corneal volume and corneal thickness after myopia correction between LASIK and SMILE. by Anna Schuh, Carolin M Kolb, Wolfgang J Mayer, Efstathios Vounotrypidis, Thomas Kreutzer, Thomas Kohnen, Siegfried Priglinger, Mehdi Shajari, Daniel Kook

“…Myopia is the most common refractive error. Surgical correction with laser is possible. …”
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Prediction of splitting tensile strength of fiber-reinforced recycled aggregate concrete utilizing machine learning models with SHAP analysis by Md Al Adnan, Muhammad Babur, Faisal Farooq, Mursaleen Shahid, Zamiul Ahmed, Pobithra Das

“…The machine learning models demonstrated high reliability in predicting splitting tensile strength, including robust values for R-squared (R2), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE) and Mean Absolute Error (MAE). …”
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The Reliability and Influence of Body Position on Acoustic Pharyngometry and Rhinometry Outcomes by Sofie Wilkens Knappe, Liselotte Sonnesen

“…Objectives: The aim of this cross sectional study was to analyze the method error and reliability in acoustic pharyngometry and rhinometry and to analyze the difference between standing and sitting position in acoustic pharyngometry and rhinometry. …”
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Location estimation of UWB-based wireless capsule endoscopy using TDoA in various gastrointestinal simulation models. by Sruthi Krishnan, Mohammed Abdel-Hafez, Matti Hämäläinen

“…The RMSE in WCE location estimation is found for individual voxel models, and the error is observed to reduce approximately from 4 mm to 1 mm, with variations in individual models, when the number of receivers are increased from 9 to 33.…”
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Practical analysis of using PPPH and raPPPid for Precise Point Positioning in Europe by Saber Mohamed, El-Mewafi Mahmoud, Awad Ahmed

“…RMSE in Up direction estimated by raPPPid varied from 0.8 cm to 5.2 cm, while RMSE in Up direction estimated by PPPH varied from 0.9 cm to 5.5 cm. 3D Positioning error was also estimated by both software and it was found that the 3D positioning error estimated by raPPPid varied from 0.2 cm to 2.2 cm, whereas the 3D positioning error estimated by PPPH varied from 0.9 cm to 4.1 cm. …”
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Association of Disability Quotient with Ocular and Systemic Manifestations in Children with Developmental Delay by Meenakshi Wadhwani, Sehzadi Malhotra, Dhulika Dhingra, Manika Manika, Shubhangi Kursange, Rahul Singh, Sneha Kumari, Amit Kumar

“…Delayed cry at birth was found to have a significant association with lower Developmental Quotient (DQ) (P = 0.021) and higher incidence of refractive error (P = 0.036). …”
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Finding Reliability of Slopes by Optimization of ANFIS with GA, FFA and PSO by Jayanti Bharti, Pijush Samui

“…Again the Root Mean Square Error (RMSE) values were found to be 0.1216, 0.1349, 0.1263 in training and 0.1256, 0.1664 and 0.1590 in testing. …”
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Deep neural network application in real-time economic dispatch and frequency control of microgrids by Liu Jun

“…The research results showed that the IRPGC algorithm had an average error of less than 10−5 after 5,000 iterations. Compared with mainstream algorithms, this algorithm achieved favorable results in frequency deviation evaluation indicators, with a frequency deviation fluctuation range of −0.073 to 0.013 Hz, an average error integral of 51.45, an absolute error integral of 0.54, and a time-weighted absolute error integral of 1.58 × 105. …”
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