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121
Enterprise power emission reduction technology based on the LSTM–SVM model
Published 2025-08-01“…The machine learning-based power data warning method proposed in this study has important practical application value and can effectively help enterprises achieve emission reduction and cost control goals.…”
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122
Accelerating Energy Forecasting with Data Dimensionality Reduction in a Residential Environment
Published 2025-03-01“…Our results demonstrate that by selecting the optimal dimensionality reduction method and model architecture, it is possible to decrease the mean squared error (MSE) by up to 63% and accelerate training by up to 80%.…”
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123
Method for limiting the peak factor using an additional compensation signal in a system with orthogonal frequency division multiplexing for a Gaussian channel
Published 2024-10-01“…The effect of the OFDM signal limitation level and the number of additional signals when using the limitation method with an additional compensation signal on the quality (reduction of transmission losses) of the OFDM signal is analyzed. …”
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124
Improving Climate Bias and Variability via CNN‐Based State‐Dependent Model‐Error Corrections
Published 2025-03-01“…Abstract We develop an approach to correct biases in the atmospheric component of the Community Earth System Model using convolutional neural networks (CNNs) to create a corrective model parameterization for online bias reduction. By predicting systematic nudging increments derived from nudging toward the ERA5‐reanalysis, our method dynamically adjusts the model state, outperforming traditional corrections based on climatological increments alone. …”
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125
Dimensionality Reduction Optimization of High Subsonic Unmanned Aerial Vehicles Intake
Published 2025-05-01“…The results show that after dimensionality reduction through sensitivity analysis and PCA, the average error and coefficient of determination of the surrogate model were improved. …”
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126
Fully-Gated Denoising Auto-Encoder for Artifact Reduction in ECG Signals
Published 2025-01-01“…None of the present denoising methods preserve the morphology of ECG signals adequately for all noise types, especially at high noise levels. …”
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127
MIMO System Reduction Using Modified Pole Clustering and Genetic Algorithm
Published 2009-01-01“…The algorithm of the proposed method is illustrated with the help of an example and the results are compared with the other well-known reduction techniques.…”
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128
Insights into geometric deviations of medical 3d-printing: a phantom study utilizing error propagation analysis
Published 2024-11-01“…Methods The partial errors were analyzed employing surface deviation analyses. …”
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129
Analytical Reduction of Nonlinear Metabolic Networks Accounting for Dynamics in Enzymatic Reactions
Published 2018-01-01“…Here, we propose a rigorous approach to reduce metabolic models using quasi-steady-state reduction based on Tikhonov’s theorem, with a characterized and bounded reduction error. …”
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130
Dimensionality Reduction using Hybrid Algorithms and Their Application to Remote Sensing Data
Published 2013-03-01Get full text
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131
Study of the Noise Reduction of DF9S1600 Gearbox Reverse Gear
Published 2017-01-01“…And according to the test,the effects of reverse gear noise is analyzed respectively from the speed,load and gear manufacturing errors,the structure is improved to achieve the purpose of the reverse gear damping noise reduction.…”
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132
Correcting errors in PCR-derived libraries for rare allele detection by reconstructing parental and daughter strand information
Published 2025-07-01“…Here, we present a sensitive genotyping method based on a peer-to-peer network-derived identifier for error reduction in amplicon sequencing (SPIDER-seq) and enable molecular identity tracking with PCR-derived libraries using overwritten barcodes. …”
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133
Uncertainty evaluation of surface profile measurement error based on adaptive sparse grid polynomial chaos expansion
Published 2025-06-01“…Numerical and experimental validations based on the car door outer surface demonstrate that compared to the ISO standard method, this method achieves a mean prediction error of less than 0.3% and a standard deviation relative error of less than 0.5% with a reduction of 99.6% in the number of sample calculation points. …”
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134
An Enhanced Error-Adaptive Extended-State Kalman Filter Model Predictive Controller for Supercritical Power Plants
Published 2025-06-01“…This study introduces an Enhanced Error-Adaptive Extended-State Kalman Filter Model Predictive Control (EEA-ESKF-MPC) method to tackle strong coupling and inertia in supercritical power plants. …”
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135
Improving Voice Spoofing Detection Through Extensive Analysis of Multicepstral Feature Reduction
Published 2025-08-01“…Our comparative analysis demonstrates significant performance gains when dimensionality reduction methods are applied, underscoring their value in enhancing the security and effectiveness of voice biometric verification systems against emerging spoofing threats.…”
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136
Multi-stage deep learning artifact reduction for parallel-beam computed tomography
Published 2025-03-01Get full text
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137
Optimizing Concrete Mix Design for Cost and Carbon Reduction Using Machine Learning
Published 2025-06-01“…The research findings indicate that the ML model provides satisfactory prediction values with an R2 value of 0.9043, root mean square error of 48.5147 and mean absolute percentage error of 0.0484. …”
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138
Analyzing the impact of curved tracks on wheel flange thickness reduction in railway systems
Published 2024-12-01“…The results of wear indices obtained using SIMPACK and VAMPIR closely matched with a small percentage error difference of 1.94%. The matching of these results validated the effectiveness of the methods used in this research to calculate wear. …”
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139
A Polar-Coded PAPR Reduction Scheme Based On Hybrid Index Modulation
Published 2025-01-01“…Therefore, the need for transmitting side information, which is a necessary process in probabilistic PAPR reduction schemes, can be eliminated. Further, to enhance detection accuracy, a construction method for frozen bit sets based on Hadamard matrix is proposed. …”
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140
A Bi-Objective Optimal Scheduling Method for the Charging and Discharging of EVs Considering the Uncertainty of Wind and Photovoltaic Output in the Context of Time-of-Use Electrici...
Published 2024-09-01“…Then, the Monte Carlo method was employed to simulate electric vehicle loads and to facilitate the generation of and reduction in scenario scenes. …”
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