Frequency regulation of two-area thermal and photovoltaic power system via flood algorithm by Serdar Ekinci, Davut Izci, Cebrail Turkeri, Aseel Smerat, Absalom E. Ezugwu, Laith Abualigah

“…The proposed FLA-based PI controller achieved a reduction in maximum overshoot by 28.3 %, a decrease in settling time by 23.4 %, and an improvement in steady-state error by 15.7 % compared to the next best-performing optimization method. …”
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Accurate sub-seasonal root-zone soil moisture prediction using attention-based autoregressive transfer learning and SMAP data by Lei Xu, Xihao Zhang, Xi Zhang, Tingtao Wu, Hongchu Yu, Wenying Du, Zeqiang Chen, Nengcheng Chen

“…The results showed that compared with LSTM, the skills of the MAATL model were significantly improved, with an average correlation coefficient increase of 18.26% and a root mean square error (RMSE) reduction of 42.55%. Furthermore, 118 in-situ soil moisture stations are used for predictive validation and the proposed MAATL model demonstrates higher accuracy compared to the Global Forecast System (GFS) and the LSTM model, with an average correlation skill improvement of 16.02% and 15.08% for MAATL over GFS and LSTM, respectively. …”
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Digital biomarkers for interstitial glucose prediction in healthy individuals using wearables and machine learning by Xinyu Huang, Franziska Schmelter, Christian Seitzer, Lars Martensen, Hans Otzen, Artur Piet, Oliver Witt, Torsten Schröder, Ulrich L. Günther, Lisa Marshall, Marcin Grzegorzek, Christian Sina

“…Abstract A personalized low-glycemic diet, maintaining stable blood glucose levels, aids in weight reduction and managing (pre-)diabetes and migraines in individuals. …”
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Diagnosis of a Severe Dust Storm Event over Iraq by Sama K. Al-Dabbagh

“…The model overestimates temperature and wind direction, while underestimating humidity and wind speed. Errors are low for most variables but notably higher for wind direction. …”
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Prevalence and predictors of statin therapy in the general working-age population by V. S. Kaveshnikov, V. N. Serebryakova, I. A. Trubacheva

“…We used methods of univariate and multivariate statistics. Error probability < 5% was considered significant.Results. …”
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Physics-informed deep learning model for line-integral diagnostics across fusion devices by Cong Wang, Weizhe Yang, Haiping Wang, Renjie Yang, Jing Li, Zhijun Wang, Yixiong Wei, Xianli Huang, Chenshu Hu, Zhaoyang Liu, Xinyao Yu, Changqing Zou, Zhifeng Zhao

“…This study achieves reductions in reconstruction errors, and accelerates the development of surrogate models in fusion research.…”
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Coffee and tea consumption and glioma risk: a meta-analysis of cohort studies by Jinyu Pan, Chuan Shao, Hui Tang, Nan Wu

“…The analysis explored glioma risk concerning the highest versus lowest levels of coffee and tea intake, supplemented by a dose–response evaluation using a one-stage robust error meta-regression model.ResultsA total of nine studies, published between 2004 and 2020, were included. …”
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Design and Analysis of Modular Neural Network-Based PI-Controller Ensemble With Karush-Kuhn-Tucker Conditions for Grid-Connected Photovoltaic Systems Under Ground Fault Conditions by Burla Sridhar, Soorya Prakash Shukla, Ritesh Dash, Arpan Dwivedi, G. C. Biswal, Nivedita Singh, Mukesh Kumar Chandrakar, Kalvakurthi Jyotheeswara Reddy, Bhabasis Mohapatra, Binod Kumar Sahu

“…Experimental validation through hardware implementation demonstrates a 45% reduction in steady-state error, a 30% reduction in THD, and improved reactive power compensation and grid synchronization. …”
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Carbon Quota Allocation Prediction for Power Grids Using PSO-Optimized Neural Networks by Yixin Xu, Yanli Sun, Yina Teng, Shanglai Liu, Shiyu Ji, Zhen Zou, Yang Yu

“…The power sector can refer to this carbon allowance allocation standard to control carbon emissions in order to meet the industry’s emission reduction standards.…”
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The effect of resizing on the natural appearance of scintigraphic images: an image similarity analysis by Siraj Ghassel, Amir Jabbarpour, Jochen Lang, Eric Moulton, Eric Moulton, Ran Klein, Ran Klein, Ran Klein, Ran Klein

“…For downsampling, both linear interpolation and sliding window summation yielded similar outcomes for a reduction factor of 2. However, for a reduction factor of 4, only sliding window summation resulted in image similarity metrics in agreement with those at the target grid size.ConclusionsThe study underlines the importance of applying appropriate resizing techniques in nuclear medical imaging to produce realistic images at the target grid size.…”
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HTSA-LSTM: Leveraging Driving Habits for Enhanced Long-Term Urban Traffic Trajectory Prediction by Yiying Wei, Xiangyu Zeng, Xirui Chen, Hui Zhang, Zhengan Yang, Zhicheng Li

“…In comparison to benchmark models, HTSA-LSTM achieved a 20.72% reduction in the root mean square error (RMSE) and a 24.98% reduction in the negative log likelihood (NLL) for 5 s predictions of long-term trajectories. …”
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RESEARCH INTO SPEECH-TO-TEXT TRANFROMATION MODULE IN THE PROPOSED MODEL OF A SPEAKER’S AUTOMATIC SPEECH ANNOTATION by Olesia Barkovska

“…The following results were obtained: demonstrates the reduction of the word error level descriptor by almost 1.5 times, which influences the quality of word recognition from the audio and may potentially lead to obtaining higher-quality output text data. …”
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A multi-dimensional data-driven ship roll prediction model based on VMD-PCA and IDBO-TCN-BiGRU-Attention by Huifeng Wang, Jianchuan Yin, Jianchuan Yin, Nini Wang, Lijun Wang, Lijun Wang

“…The results show that the proposed prediction model has a root mean square error reduction of about 78.25% and an increase of about 65.63% reliability compared with TCN.DiscussionThe model outperforms traditional methods in terms of accuracy and stability. …”
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A novel multiscale feature enhancement network using learnable density map for red clustered pepper yield estimation by Chenming Cheng, Chenming Cheng, Jin Lei, Jin Lei, Zicui Zhu, Lijian Lu, Lijian Lu, Zhi Wang, Zhi Wang, Jiali Tao, Jiali Tao, Xinyan Qin, Xinyan Qin

“…Compared to other feature extraction networks, MFEN had the lowest mean absolute error (MAE) of 5.42, root mean square error (RMSE) of 10.37 and symmetric mean absolute percentage error (SMAPE) of 11.64%. …”
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Political risk and macroeconomic effect of housing prices in South Africa by Thomas Habanabakize, Zandri Dickason

“…Additionally, interest rate reduction can generate growth in housing demand resulting in the country’s economic improvement.…”
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Low-Complexity Architecture of Orthogonal <italic>N</italic>-Continuous Precoding for Sidelobe Suppression of OFDM Signals and Its Analysis by Hikaru Kawasaki, Fumihide Kojima, Takeshi Matsumura

“…In conclusion, the proposed scheme drastically reduces the conventional precoding&#x2019;s complexity to a level matching that of a fast Fourier transform for OFDM and provides 99 % storage overhead reduction. All its inherent advantages are maintained such as fast, smooth, and symmetrical spectral decay of band-edges, and ideal characteristics of error rate and peak power.…”
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A study on monthly sales forecasting of new energy vehicles in urban areas using the WOA-BiGRU model. by Xiangtu Li

“…The WOA-BiGRU model outperforms both the standalone BiGRU and PSO models, achieving a Mean Absolute Error (MAE) of 3051.89, which is 526.18 lower than the BiGRU model and 104.72 lower than that of the PSO model. …”
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The Algorithm for Recognizing Superposition of Wave Aberrations from Focal Pattern Based on Partial Sums by Sergey G. Volotovsky, Pavel A. Khorin, Aleksey P. Dzyuba, Svetlana N. Khonina

“…Due to the peculiarities of the focal pattern, some types of the considered superpositions are recognized ambiguously from the intensity pattern in the focal plane by standard error-reduction algorithms. It is numerically shown that when recognizing superpositions of Zernike functions from the intensity pattern in the focal plane, the use of step-by-step optimization in combination with the Levenberg–Marquardt algorithm yields good results only with an initial approximation close to the solution. …”
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Continuous respiratory rate monitoring through temporal fusion of ECG and PPG signals. by Yuxuan Lin, Xinyue Song, Yan Zhao, Chunlin Zhang, Xiaorong Ding

“…Validation on two public datasets - the Capnobase dataset (42 subjects) and the BIDMC dataset (53 subjects) - showed that the proposed method attained a mean absolute error (MAE) of 1.39 breaths/min and 3.29 breaths/min for RR estimation, respectively, achieving an average 11.61% reduction in MAE compared to existing state-of-the-art approaches. …”
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Semi-Supervised Learning of Statistical Models for Natural Language Understanding by Deyu Zhou, Yulan He

“…In addition, the proposed framework shows superior performance than two other baseline approaches, a hybrid framework combining HVS and HM-SVMs and discriminative training of HVS, with a relative error reduction rate of about 25% and 15% being achieved in F-measure.…”
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