Performance of a new stabilized structure-preserving finite element method for the Allen–Cahn equation by Panason Manorot, Ben Wongsaijai, Kanyuta Poochinapan

“…Additionally, the [Formula: see text] error estimate for the fully discretized scheme is carried out in a rigorous way with the optimal error bound [Formula: see text]. …”
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Problems in measurement of integrated sensitivity of photodetectors by I. V. Doktorovich, V. N. Hodovaniouk, V. G. Yuryev, V. G. Zhytaryuk

“…Also, metrological characteristics of the methods which are used, the reasons of increasing errors and possible ways of their decreasing are provided. …”
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Minor variant detection in amplicons using 454 massive parallel pyrosequencing: experiences and considerations for successful applications by Ina Vandenbroucke, Herwig Van Marck, Peter Verhasselt, Kim Thys, Wendy Mostmans, Stéphanie Dumont, Veerle Van Eygen, Katrien Coen, Marianne Tuefferd, Jeroen Aerssens

“…Especially for this application, errors that might be introduced during any of the sample processing or data analysis steps should be avoided or at least recognized, as they might lead to aberrant sequence variant calling. …”
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Beyond Handcrafted Features: A Deep Learning Framework for Optical Flow and SLAM by Kamran Kazi, Arbab Nighat Kalhoro, Farida Memon, Azam Rafique Memon, Muddesar Iqbal

“…We conduct an extensive search for optimal features by analyzing the offset error across thousands of combinations of layers and filters within the CNN. …”
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Investigation of cadmium removal using tin oxide nanoflowers through process optimization, isotherms and kinetics by Selim Gürsoy, Miray Bombom, Buse Tuğba Zaman, Fatma Turak, Sezgin Bakırdere, Elif Öztürk Er

“…The adsorption equilibrium process was elucidated by Langmuir, Freundlich, Sips and Toth isotherm models using nonlinear regression. In addition, error functions such as Chi-square (X 2, Average Relative Error (ARE), Root Mean Squared Error (RMSE) and HYBRID were used to test the validity of the nonlinear models. …”
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Optimization Design of the Two-Stage Reduction Micro-Drive Mechanism Based on Particle Swarm Algorithm by Na Zhang, Dongmei Wang, Kai Li, Kaiyang Wei, Hongyu Ge, Manzhi Yang

“…In order to obtain smaller displacements with higher accuracy, this paper focused on the design, optimization, and performance analysis of a two-stage reduction micro-drive mechanism. …”
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Optimized visual front-end navigation technology based on INS SLAM in smart tourism systems by Cheng Pan, Yuqing Liu, Meijiao Sun

“…In the experimental analysis, the results showed that the absolute trajectory error and relative pose error accuracy of the research model reached 0.81 m and 0.012 m/s, respectively. …”
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Non-Contact Oxygen Saturation Estimation Using Deep Learning Ensemble Models and Bayesian Optimization by Andrés Escobedo-Gordillo, Jorge Brieva, Ernesto Moya-Albor

“…As performance metrics for the SpO₂-estimation proposal, we calculated the Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), and other parameters from the Bland–Altman (BA) analysis with respect to the reference. …”
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Independent Component Analysis-Based Composite Drought Index Development for Hydrometeorological Analysis by Yejin Kong, Joo-Heon Lee, Taesam Lee

“…The ICDI was derived by extracting optimal weights for each drought index through ICA, leveraging the optimization of non-Gaussianity. …”
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Comparison of Electric Field Calculation Methods for Optimization Routines to Design Medium-Frequency Transformer Insulation by Bastian Korthauer, Jurgen Biela

“…This paper compares suitable methods, including the Schwarz-Christoffel transformation (SCT), the charge simulation method (CSM), and commonly used analytical approaches, by benchmarking them against nearly 4000 finite element analysis (FEA) simulations. Each method's error is analyzed, and a sensitivity study is performed to define the parameter ranges where each method yields accurate results. …”
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Evaluation of Contemporary Computational Techniques to Optimize Adsorption Process for Simultaneous Removal of COD and TOC in Wastewater by Areej Alhothali, Hifsa Khurshid, Muhammad Raza Ul Mustafa, Kawthar Mostafa Moria, Umer Rashid, Omaimah Omar Bamasag

“…Comparative analysis of RSM, ANN, and ANFIS models showed mean square error (MSE) as 5.29809, 1.49937, and 0.24164 for adsorption of COD and MSE of 0.11726, 0.10241, and 0.08747 for prediction of TOC adsorption, respectively. …”
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Determination of similar material proportions based on orthogonal experiments and neural network optimization in the goaf area by Shengdi Wang, Junzhi Chen, Yonggang Zhang, Xiaowei Qiao, Zhiping Zhang, Xin Wang

“…This paper used orthogonal experiments and multi factor optimization methods to study the optimal mixing ratio of similar materials for limestone surrounding rock in a goaf of a certain iron mine in Yunnan, and introduced a new material combination (quartz, cement, gypsum, barite, and glycerol), and utilized orthogonal experiments alongside machine learning techniques for predictive analysis. …”
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A Hybrid Model Integrating Variational Mode Decomposition and Intelligent Optimization for Vegetable Price Prediction by Gao Wang, Shuang Xu, Zixu Chen, Youzhu Li

“…Experimental results indicate substantial improvements in key metrics including the Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and Coefficient of Determination (R²), with R² values consistently exceeding 99.4% and achieving over 5% enhancement compared to the baseline GRU model. …”
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Model and training method for aerial image object detector with optimization of both robustness and computational efficiency by Alona Moskalenko, Mykola Zaretskyi, Maksym Vynohradov, Vladyslav Babych

“…However, the vulnerability of neural networks to noise, adversarial attacks, and weight error injections significantly diminishes their robustness and overall effectiveness. …”
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Time-dependent robust reliability optimization of structure based on genetic interval affine response surface by GUAN Yi, SHENG GuoJun

“…On the basis of sample boundary and structural performance analysis results of each variable in the design variable database, the genetic algorithm and criteria for error minimization we were used to optimize the initial interval affine response surface. …”
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Performance assessment and optimization of Ti6Al4V helical hole milling process by Gururaj Bolar, Vikas Marakini, Raviraj Shetty, Sawan Shetty, Adithya Hegde

“…Metrics like R ^2 , root mean square error (RMSE), and error percentage were used to assess the predictive models that were developed using Response Surface Methodology (RSM) and Back Propagation Artificial Neural Networks (BPANN). …”
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Control Optimization Design of Radio Frequency Identification Technology in IoT Express Logistics Distribution System by He Liu, Linna Jiao, Fangfang Wang, Xiaoman Zhang

“…The details of the method are RFID positioning technology, laser ranging technology, RFID and laser fusion positioning feasibility analysis, and moving target state estimation. The experimental results show that when the phase shift threshold φ and the included angle of the antenna are 90°, the error can be reduced to 0.36 m, and the recognition rate can be increased to 94.8%. …”
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Optimizing Chlorophyll-a Concentration Inversion in Coastal Waters Using SVD and Deep Learning Approach by Lili Zhan, Yongxin Xu, Jinshan Zhu, Zhangshuo Liu

“…Results show that the developed SVD-DNN model has the best retrieval accuracy [mean R = 0.90, root mean square error (RMSE) = 1.21, mean absolute error (MAE) = 1.05], outperforming the SVD-RF and SVD-SVM models. …”
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A Seismic Demand Model for Bridges Based on IM and EDP Parameter Matching and Bidirectional Optimization by Shuai Wang, Shuai Song, Gang Wu

“…This paper proposes a novel method to obtain the optimal seismic demand model for the seismic vulnerability analysis of bridges. …”
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Automated Machine Learning for Optimized Load Forecasting and Economic Impact in the Greek Wholesale Energy Market by Nikolaos Koutantos, Maria Fotopoulou, Dimitrios Rakopoulos

“…Assuming an always overbought condition in the Day-Ahead as well as in the Futures Market, the excess energy returns without revenue to the market, and the results are compared with a standard contract in Greece, which stands as the lowest as far as the billing price is concerned. The analysis achieved a mean absolute percentage error (MAPE) of 12.89% as the best fitted model and without using any kind of pre-processing methods.…”
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