Capturing spatiotemporal variation in salt marsh belowground biomass, a key resilience metric, through geoinformatics by Kyle D. Runion, Deepak R. Mishra, Merryl Alber, Mark A. Lever, Jessica L. O'Connell

“…When we used this expanded calibration dataset and associated predictors to advance BERM, model error was reduced from a normalized root‐mean‐square error of 13.0%–9.4% in comparison with the original BERM formulation. …”
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Machine Learning Approach for Assessment of Compressive Strength of Soil for Use as Construction Materials by Yassir M. H. Mustafa, Yakubu Sani Wudil, Mohammad Sharif Zami, Mohammed A. Al-Osta

“…Validation was conducted using data from four types of locally available soils in the Najd region of Saudi Arabia, although some disparities were noted between actual and predicted results due to limitations in the training data. …”
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A Structured Cleaving Mesh for Bioheat Transfer Application by Rohan Amare, Amir A. Bahadori, Steven Eckels

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A Short-Term Prediction Method for Tropospheric Delay Products in PPP-RTK Based on Multi-Scale Sliding Window LSTM by Linyu He, Xingyu Zhou, Hua Chen, Jie He, Runhua Chen, Jie Ding

“…The integration of these two methods significantly enhances the precision of short-term tropospheric delay predictions. Experimental analysis utilizing one week of data from the Hong Kong Continuously Operating Reference Stations (CORS) network demonstrates that the proposed method achieves a maximum prediction error of less than 1.5 cm. …”
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Short-Term Electricity Price Forecasting Using the Empirical Mode Decomposed Hilbert-LSTM and Wavelet-LSTM Models by Kunal Shejul, R. Harikrishnan, Amit Kukker

“…In this approach, the 8-year dataset is used for training the models, and based on this the day-ahead price is calculated and compared with the testing data. The proposed techniques show better performance in terms of rank correlation, mean square error, and root mean square error compared to the existing algorithms of LSTM and CNN-LSTM. …”
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Enhanced Collaborative Filtering: Combining Autoencoder and Opposite User Inference to Solve Sparsity and Gray Sheep Issues by Lamyae El Youbi El Idrissi, Ismail Akharraz, Aziza El Ouaazizi, Abdelaziz Ahaitouf

“…Through experimental analysis of the MovieLens 100K dataset, we observe that our method achieves notable reductions in both RMSE (Root Mean Squared Error) and MAE (Mean Absolute Error), underscoring its superiority over the state-of-the-art collaborative filtering models.…”
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The Research on Path Planning Method for Detecting Automotive Steering Knuckles Based on Phased Array Ultrasound Point Cloud by Yihao Mao, Jun Tu, Huizhen Wang, Yangfan Zhou, Qiao Wu, Xu Zhang, Xiaochun Song

“…The results show that the point cloud data of the steering knuckle specimen, obtained using phased array ultrasound, had a relative measurement error controlled within 1.4%, and the error between the calculated probe angle and the theoretical angle did not exceed 0.5°. …”
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Leveraging machine learning techniques to analyze nutritional content in processed foods by K. A. Muthukumar, Soumya Gupta, Doli Saikia

“…Model performance was evaluated using Normalized Mean Squared Error (NMSE) as the evaluation metric. The results indicated that the RF model achieved an NMSE of approximately 0.35, reflecting a moderate level of prediction error relative to data variance. …”
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Predicting Knee Cartilage Degradation and Osteoarthritis Onset Using a Hybrid Mathematical Modeling and Machine Learning Framework by F. Mekrane, R. Ouladsine, A. Barkaoui, R. Ghandour

“…Knee osteoarthritis (KOA), in particular, represents a big data challenge due to the complexity, heterogeneity, and large volume of data required for its analysis and prediction. …”
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Novel magnetometer-free inertial-measurement-unit-based orientation estimation approach for measuring upper limb kinematics by Souha Baklouti, Taysir Rezgui, Abdelbadia Chaker, Anis Sahbani, Sami Bennour

“…First, a comparative analysis was conducted on the double-stage Kalman filter (DSKF) and complementary filter using the collected robot motion encoder data. …”
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MATHEMATICAL MODELING IN THE CONTENT OF STUDENTS-ECOLOGISTS’ TRAINING OF MATHEMATICS by S. I. Toropova

“…The process of sequential selection of the best model of multiple regressions is presented, taking into account such criteria as determination coefficient, Zarembka test, standard regression error and approximation error.Conclusion. The listed criteria are satisfied by linear, inverse, power and exponential models. …”
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High-Resolution Spatiotemporal Forecasting with Missing Observations Including an Application to Daily Particulate Matter 2.5 Concentrations in Jakarta Province, Indonesia by I Gede Nyoman Mindra Jaya, Henk Folmer

“…The validation of out-of-sample forecasts indicates a strong model fit with low mean squared error (0.001), mean absolute error (0.037), and mean absolute percentage error (0.041), and a high R² value (0.855). …”
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Adaptive Hosting Capacity Forecasting in Distribution Networks with Distributed Energy Resources by Md Tariqul Islam, M. Jahangir Hossain, Md. Ahasan Habib, Muhammad Ahsan Zamee

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An Unscented Kalman Filter-Based Method for Reconstructing Vehicle Trajectories at Signalized Intersections by Jiantao Mu, Yin Han, Cheng Zhang, Jiao Yao, Jing Zhao

“…Finally, the method is applied to the actual scenario provided by the NGSIM data and compared with the real trajectory. The mean absolute error (MAE) is adopted to evaluate the accuracy of the proposed trajectory reconstruction. …”
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Quantifying Upper-Arm Rehabilitation Metrics for Children through Interaction with a Humanoid Robot by Douglas A. Brooks, Ayanna M. Howard

“…The specific exercises involved adduction and abduction and lateral and medial movements. The analysis shows that our algorithmic results compare closely to the results obtain from the ground truth data, with an average algorithmic error is less than 9% for the range of motion and less than 8% for the peak angular velocity of each subject.…”
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Pengaruh Volume Pembiayaan Bagi Hasil Dan Pembiayaan Murabahah Terhadap Kinerja Keuangan Bank Umum Syariah Periode 2015-2020 by Celine Quatro, Asnaini Asnaini, Aminah Oktarina

“…This research uses ECM (Error Correction Model) analysis with Eviews 8 software. …”
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Research on automatic processing system of financial information in colleges and universities based on NLP-KG fusion algorithm by Jin Lei, Mengke Wei, Yiwen She, Weixia Wang

“…Traditional financial information processing in colleges and universities relies on manual entry and review, which is inefficient, error-prone and scattered, and early automation tools have problems such as insufficient semantic understanding and correlation analysis, and data silos. …”
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Crystal Structure and Cyclic Voltammetric Studies on the Metal Complexes of N-(Dimethylcarbamothioyl)-4-fluorobenzamide by Gun Binzet, Ersan Turunc, Ulrich Flörke, Nevzat Külcü, Hakan Arslan

“…All bond lengths and angles obtained as a result of the analyses are found to be within experimental error limits. The obtained crystal analysis data shows that the structure of complex compounds is compatible with similar compounds in literature. …”
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Study on Noise Reduction of Hydrostatic Leveling Signals for Wind Turbine Foundations Based on CEEMDAN-SG Algorithm by Renjie Li, Xiangxing Lu, Zhixin Song, Huanwei Wei, Fang Tan, Zhonghua Liu

“…The denoising performance of each algorithm was evaluated through quantitative analysis, which included calculating the signal-to-noise ratio, mean square error, and coefficient of determination derived from the simulated signal data. …”
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Equilibrium Solubility of Ammonium Nitrate and Potassium Nitrate in (NH₄NO₃-KNO₃-H₂O-C₂H₅OH) Mixed System by Xian Wu, Ganbing Yao, Hao Feng

“…Error analysis demonstrates that the calculated values exhibit satisfactory agreement with the experimental data.…”
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