Streamflow routing at high temporal resolution: A distributed hydrological model with dam and weir impacts by Yonggwan Lee, Jeehun Chung, Jiwan Lee, Wonjin Jang, Seongjoon Kim

“…Streamflow modeling results at 10 gauging stations, including dam and weir locations, yielded coefficients of determination (R²) ranging from 0.56 to 0.94, Nash-Sutcliffe efficiency from 0.44 to 0.91, Root Mean Square Error from 1.13 to 3.61 mm/day, and percent bias from −13.94–42.50. …”
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Chemometric and meta-heuristic algorithms to find optimal wavelengths and predict ‘Red Delicious’ apples traits using Vis-NIR by Mahsa S. Razavi, Vali Rasouli Sharabiani, Mohammad Tahmasebi, Silvia Grassi, Mariusz Szymanek

“…SVM-R demonstrated slightly higher performance in predicting apples traits in validation: pH (R2 0.935, RMSEP 0.019, and RPD 3.636), TA (R2 0.932, RMSEP 0.026, and RPD 3.447), SSC (R2 0.913, RMSEP 0.174, and RPD 3.168), ascorbic acid (R2 0.938, RMSEP 0.154, and RPD 3.725), firmness (R2 0.932, RMSEP 0.311, and RPD 3.522), and anthocyanin (R2 0.921, RMSEP 0.007, and RPD 3.171).Thus, different metaheuristic variable selection techniques (including ACO, LA, GA, PSO, LCA, FOA, WCC, CUK, DSOS, ICA, and HTS) were combined with SVM to identify the most important wavelengths for practical industry applications. SVM-PSO and SVM-FOA were identified as the most effective wavelength selection methods based on average coefficient of correlation, average convergence of error, execution time, and the number of selected wavelengths.…”
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High-isolation dual-band MIMO antenna for next-generation 5G wireless networks at 28/38 GHz with machine learning-based gain prediction by Md Ashraful Haque, Redwan A. Ananta, Md. Sharif Ahammed, Jamal Hossain Nirob, Narinderjit Singh Sawaran Singh, Liton Chandra Paul, Reem Ibrahim Alkanhel, Ahmed A. Abd El-Latif, May Almousa, Abdelhamied A. Ateya

“…Among the five different regression machine learning models considered, it was discovered that the Random Forest Regression (RFR) model performed the best in accuracy and achieved the lowest error when predicting gain. This article explores many approaches, including simulation, integration of an RLC-equivalent circuit model, and multiple regression models, to evaluate the suitability of an antenna for its 5G applications.…”
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Kolmogorov–Arnold Networks for Automated Diagnosis of Urinary Tract Infections by Anurag Dutta, A. Ramamoorthy, M. Gayathri Lakshmi, Pijush Kanti Kumar

“…By rapid UTI detection, the proposed methodology reduces diagnostic delays, minimizes human error, and streamlines laboratory workflows. Further, preliminary results can complement (expert-supervised) molecular testing by enabling them to focus only on clinically important cases, reducing stress on traditional approaches.…”
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StarNet: Indian star gooseberries dataset for quality and maturity assessment(Mendeley Data). by Pushpa B․ R․, Manohar N․, N. Shobha Rani

“…The post-harvest process of fruit typically performs the quality assessment by segregating fruits based on visual characteristics, which is tedious and prone to human error. Hence, there is a need to develop an automated computer vision model to assess the fruit quality more accurately. …”
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Unveiling construction accident causation: a scientometric analysis and qualitative review of research trends by Haoyu Zang, Ming Li, Zhiyao Jin, Jingfei Huang

“…These incidents arise from interlinked causal factors, including human error, management shortcomings, technical failures, and environmental conditions. …”
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An Analysis of WiFi Coverage Modeling for a Hotspot in the Parish of Checa Employing Deterministic and Empirical Propagation Models by Iván Sánchez, Fabricio Vallejo, Pablo Palacios Játiva, Ali Dehghan Firoozabadi

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A new 3D plastoelastohydrodynamic lubrication model for rough surfaces by Shengyu You, Jinyuan Tang, Qiang Wang

“…The new model eliminates an original error introduced by the assumption of semi-infinite space in contact calculation, providing wide applicability and high accuracy. …”
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Dynamic Modeling and Disturbance-Observer-Enhanced Control for Mecanum-Wheeled Vehicles Under Load and Noise Disturbance by Chensheng Li, Zhi Li

“…Open-loop experiments validate the model’s accuracy, showing a Dynamic Time Warping (DTW) error of 0.2662 m, significantly lower than the 0.3198 m observed in traditional models. …”
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Classification of forest development stages from national low-density lidar datasets: a comparison of machine learning methods by R. Valbuena, M. Maltamo, P. Packalen

“…We observed that RF and NN had the most balanced error matrices, with cross-validated predictions which were mainly unbiased for all DCs. …”
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SICNN: Soft Interference Cancellation Inspired Neural Network Equalizers by Stefan Baumgartner, Oliver Lang, Mario Huemer

“…SICNNv2 is more universal and is applicable as an equalizer in any communication system with a block-based data transmission scheme. …”
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Mathematical approach for rapid determination of pull-in displacement in MEMS devices by Yongcun Shao, Yutong Cui

“…Compared to traditional methods, this approach yields exact values rather than approximations, showcasing superior precision and efficiency.DiscussionThe proposed method offers significant advantages, including enhanced accuracy, reduced computational time, and minimized error accumulation by solving algebraic equations instead of iterating differential equations. …”
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Optimizing Photovoltaic Panel Performance: A Comparative Study of Meta-Heuristic Algorithms by M. Sundar Rajan

“…Our findings indicate that the HPSGWO algorithm achieves the lowest error rates and the highest efficiency, accuracy, and convergence speed across all tested PV models. …”
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Forecasting of Islamic Stock Index in Turkey with Deep Learning Using Index-Based Features by Dilşad Tülgen Çetin, Sedat Metlek

“…As a consequence of developments in artificial intelligence applications, deep learning methods show superior success compared to other methods in predicting financial data. …”
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Federated learning with LSTM for intrusion detection in IoT-based wireless sensor networks: a multi-dataset analysis by Raja Waseem Anwar, Mohammad Abrar, Abdu Salam, Faizan Ullah

“…The evaluation metrics for its performance included accuracy, F1 score, FPR, and root mean square error (RMSE). We evaluated the performance of the FL-based LSTM model against traditional centralized models, finding significant improvements in intrusion detection. …”
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Fabrication of PLA bio-composite reinforced with jute fiber and ESP fillers and optimization of mechanical properties via fuzzy logic approach by Efty Mahmud, Alberuni Aziz, Farjana Parvin

“…., minimizing the trial-and-error approach often seen in the industry Additionally, the fuzzy logic model enhances the ability to predict composite behavior. …”
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Multi-objective optimization of wear parameters of hybrid composites (LM6/B4C/fly ash) using grey relational analysis. by Charles Sarala Rubi, Jayavelu Udaya Prakash, Sunder Jebarose Juliyana, Sachin Salunkhe, Robert Cep, Emad Abouel Nasr

“…The responses have a narrow margin of error, according to confirmation studies. There exists a good agreement between them.…”
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Using a Bodily Weight-Fat Scale for Cuffless Blood Pressure Measurement Based on the Edge Computing System by Shing-Hong Liu, Bo-Yan Wu, Xin Zhu, Chiun-Li Chin

“…Results show that the error of systolic blood pressure (SBP) and diastolic blood pressure (DBP) in server-based computing are 2.64 ± 9.71 mmHg and 1.52 ± 6.32 mmHg, and in edge computing are 2.2 ± 10.9 mmHg and 1.87 ± 6.79 mmHg. …”
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Improving High-Precision BDS-3 Satellite Orbit Prediction Using a Self-Attention-Enhanced Deep Learning Model by Shengda Xie, Jianwen Li, Jiawei Cai

“…Specifically, SCINet-SA achieved the highest average relative improvement (IMP) in 3D Root Mean Square (RMS) error across 1 d, 7 d, and 15 d prediction horizons, yielding improvements of 21.69%, 18.66%, and 15.42%, respectively. …”
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Enhanced Joint Heart and Respiratory Rates Extraction from Functional Near-infrared Spectroscopy Signals Using Cumulative Curve Fitting Approximation by Navid Adib, Seyed Kamaledin Setarehdan, Shirin Ashtari Tondashti, Mahdis Yaghoubi

“…Moreover, the low mean absolute error (0.18 s) in estimating the respiration period emphasizes the feasibility of the proposed method for RR estimation from fNIRS data. …”
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