Analysis of Static Stability of Earth-Rockfill Dam Slope Based on PSO-PR-IE Method by LIU Qiankun, PAN Shiyang, LI Tongchun, LIU Baoyong

“…In order to fully consider the advantages of the anti-sliding performance of the contact interface using the partitioned rigid body–interface element (PR-IE) method, the static stability analysis method of earth-rockfill dam slope based on the PR-IE method was improved, and the particle swarm optimization (PSO) method was adopted, yielding a static stability analysis method of earth-rockfill dam slope based on PSO-PR-IE method. …”
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Minimum Error Integration Method for Quadrilateral Flat Plate Fitting in Steel Construction by Zhuoju Huang, Jiemin Ding

“…Our results demonstrate at most a 75.5% reduction in fitting errors for analytical curved plates with particularly significant improvements in biconvex curvature scenarios. …”
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Comparison of Spatial Predictability Differences in Truck Activity Patterns: An Empirical Study Based on Truck Tracking Dataset of China by Lianghua Li, Peng Du, Guohua Jiao, Xin Fu

“…This research not only characterizes the freight truck community but also aids algorithm optimization by revealing predictability factors for real-world applications.…”
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Evaluation method of distribution network operation status based on local fuzzy measure in boundary region by Bing Yu, Peng Xie, Zhonglin Ding, Letian Li, Changan Chen, Chunfeng Jing

“…The research results showed that the cluster center update optimization method based on local fuzzy measure in boundary region could effectively reduce the negative impact of the edge region occupied by most clusters on its clustering effect, so that the cluster center was always in an ideal position. …”
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A Rice Leaf Area Index Monitoring Method Based on the Fusion of Data from RGB Camera and Multi-Spectral Camera on an Inspection Robot by Yan Li, Xuerui Qi, Yucheng Cai, Yongchao Tian, Yan Zhu, Weixing Cao, Xiaohu Zhang

“…The model based on the LightGBM regression algorithm has the most improvement in accuracy, with a coefficient of determination (R²) of 0.892, a root mean square error (RMSE) of 0.270, and a mean absolute error (MAE) of 0.160. …”
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Data-driven approach to mid-latitude coherent scatter radar data classification by Berngardt Oleg

“…Based on 2021 data, a solution of the problem of automatic data classification is presented without their labeling by an expert and without postulating the number of classes. The algorithm automatically labels the data, determines the optimal number of signal classes observed by the radars, and trains a two-layer classifying neural network of an extremely simple structure. …”
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Application of GA in Furniture Modeling Style Design by Heng Yu, Chunjing Liu

“…In order to improve the production efficiency of furniture, it is necessary to optimize it. …”
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High-Precision Extraction Method for Blade Tip-Timing Signal with Eddy Current Sensor by Ji-wang Zhang, Ke-qin Ding, Guang Chen

“…A new denoising and shaping algorithm based on ensemble empirical mode decomposition (EEMD) was introduced for the errors caused by background noise. …”
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Vulnerability Assessment in Karst Aquifers with EPIK and COP Indices Calibration by Hamid Kardan Moghadam, Amir Reza Nemati Mansour, Abbas Akbarzadeh, Ali Mirarabi

“…In order to calibrate the GQI qualitative index with the zoning of the springs in the region, whale optimization algorithms were used. In this calibration, the weights and ranks of the two vulnerability indices were determined. …”
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Multiple Interface Parallel Approach of Bioinspired Routing Protocol for Mobile Ad Hoc Networks by L. J. García Villalba, D. Rupérez Cañas, A. L. Sandoval Orozco, T.-H. Kim

“…The simulation results indicate that PAntOR and PAntOR-MI improve performances of AntOR, whilst it is also noticed that PAntOR-MI is the most suitable for highly dynamic environments.…”
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From Tables to Computer Vision: Transforming HPDC Process Data into Images for CNN-Based Deep Learning by A. Burzyńska

“…Utilizing a combination of statistical pre-processing, intelligent generative models, visual data transformations and deep learning, the methodology offers a comprehensive approach to enhancing production efficiency, ensuring superior process control and improving the quality of HPDC products. This development signifies a significant advancement in the field of intelligent systems for manufacturing process optimization, aligning with the principles of Industry 4.0 and Quality 4.0.…”
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An Intelligent Method for C++ Test Case Synthesis Based on a Q-Learning Agent by Serhii Semenov, Oleksii Kolomiitsev, Mykhailo Hulevych, Patryk Mazurek, Olena Chernyk

“…However, test suites in open-source libraries often grow large, redundant, and difficult to maintain. Most traditional test suite optimization methods treat test cases as atomic units, without analyzing the utility of individual instructions. …”
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Multi-Underwater Target Interception Strategy Based on Deep Reinforcement Learning by Wenhao GAN, Yunfei PENG, Lei QIAO

“…Next, the multi-agent proximal policy optimization algorithm was used to construct a scalable state and action space and design a compound reward function, enhancing interception efficiency and cooperation of AUVs. …”
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A Hierarchical Control Framework for Coordinating CAV-Dedicated Lane Allocation and Signal Timing at Isolated Intersections in Mixed Traffic Environments by Feng Chen, Cunbao Zhang, Yu Cao

“…With the rapid development of connected and automated vehicles (CAVs), numerous studies have demonstrated that CAV-dedicated lanes (CAV-DLs) can significantly enhance traffic efficiency. However, most existing studies primarily focus on optimizing either CAV trajectory planning or traffic signal control, and the integration of CAV-DLs and signal control for improved spatiotemporal resource utilization remains underexplored. …”
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Systemic therapy for laryngeal carcinoma by Thorsten Fuereder, Florian Kocher, Jan Baptist Vermorken, Jan Baptist Vermorken

“…Consequently, multiple recent efforts have been made to integrate novel immunotherapies into the current treatment algorithm for LSCC. In particular, perioperative immunotherapy regimens appear to be the most promising approach for preserving laryngeal function and optimizing event-free and overall survival rates in the locally advanced setting. …”
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Uncertainty quantification with graph neural networks for efficient molecular design by Lung-Yi Chen, Yi-Pei Li

“…Using benchmarks from the Tartarus and GuacaMol platforms, our results show that UQ integration via probabilistic improvement optimization (PIO) enhances optimization success in most cases, supporting more reliable exploration of chemically diverse regions. …”
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Deep Learning–Based Prediction of Freezing of Gait in Parkinson's Disease With the Ensemble Channel Selection Approach by Sara Abbasi, Khosro Rezaee

“…Method To address this, we developed a novel algorithm for detecting FoG events based on movement signals. …”
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An Optimised Method for Fetching and Transforming Survey Data based on SQL and R Programming Language by Hasan et al.

“…The development of information systems in recent years has contributed to various methods of gathering information to evaluate IS performance. The most common approach used to collect information is called the survey system. …”
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Machine Learning Techniques Applied to COVID-19 Prediction: A Systematic Literature Review by Yunyun Cheng, Rong Cheng, Ting Xu, Xiuhui Tan, Yanping Bai

“…By establishing a multi-level classification framework that included traditional statistical models (such as ARIMA), ML models (such as SVM), deep learning (DL) models (such as CNN, LSTM), ensemble learning methods (such as AdaBoost), and hybrid models (such as the fusion architecture of intelligent optimization algorithms and neural networks), it revealed that the hybrid modelling strategy effectively improved the prediction accuracy of the model through feature combination optimization and model cascade integration. …”
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A review on agrowaste based activated carbons for pollutant removal in wastewater systems by Karinate Valentine Okiy, Joseph Nwabanne Tagbo, Walter Peter Echeng

“…Among these methods, heavy metal adsorption from aqueous solutions by the activated carbons is the most efficient. The deployment of mathematical and machine learning approaches (ANN and novel GMDH algorithms) in optimization of batch and continuous adsorption processes are also highlighted. …”
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