Elastic Momentum-Enhanced Adaptive Hybrid Method for Short-Term Load Forecasting by Wenting Zhao, Haoran Xu, Peng Chen, Juan Zhang, Jing Li, Tingting Cai

“…The particle swarm optimization (PSO) algorithm is improved by adjusting its elastic momentum, and the enhanced APSO algorithm is employed to optimize the adaptive weights of the hybrid model. …”
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Vehicle detection and classification for traffic management and autonomous systems using YOLOv10 by Anning Ji, Xintao Ma

“…The main purpose of this study is to address these challenges and improve vehicle detection in ITS environments. We propose a novel detection framework, YDFNet, that integrates the YOLOv10 algorithm for fast feature extraction, the BiFPN (Bidirectional Feature Pyramid Network) for multi-scale feature fusion, and the DETR (Detection Transformer) architecture for global feature modeling. …”
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Classification-based point cloud denoising and 3D reconstruction of roadways by Denghong CHEN, Ning PANG, Wen NIE, Juqiang FENG, Jiliang KAN, Jinjing ZHANG

“…Meanwhile, the existing 3D reconstruction algorithms suffer from low modeling accuracy and high susceptibility to distortion. …”
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Enabling High-Level Worker-Centric Semantic Understanding of Onsite Images Using Visual Language Models with Attention Mechanism and Beam Search Strategy by Hui Deng, Kejie Fu, Binglin Yu, Huimin Li, Rui Duan, Yichuan Deng, Jia-rui Lin

“…The addition of the attention mechanism and beam search strategy improves the model, making it more accurate and generalizable. …”
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The authors would like to thank the staff of the Organisation of Transportation and Transport Management Department by B. S. Trofimov, I. S. Trofimova

“…To plan the work of a lorry, taking into account changes in its design, it is required to use improved methods for optimizing the planning of the work of a freight motor transport enterprise, which is the relationship of activities for the transportation of goods, maintenance and current repair. …”
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A Blockchain-Based Architecture of Web3.0: A Comprehensive Decentralized Model With Relay Nodes, Unique IDs and P2P by Hyunjoo Yang, Sejin Park

“…This paper introduces a decentralized architecture for Web3.0, leveraging blockchain, relay nodes, unique IDs, and P2P communication. The proposed model integrates a blockchain-based unique ID management system for secure node identification and employs a multistep TPM-based verification algorithm to validate node authenticity in real time. …”
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Data-Driven ANN-Based Predictive Modeling of Mechanical Properties of 5Cr-0.5Mo Steel: Impact of Composition and Service Temperature by Muhammad Ishtiaq, Saurabh Tiwari, Molakatala Nagamani, Sung-Gyu Kang, Nagireddy Gari Subba Reddy

“…The ANN model’s findings offer valuable insights for researchers and designers, aiding in developing steel components with optimized properties. …”
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Traffic safety evaluation of emerging mixed traffic flow at freeway merging area considering driving behavior by Yaqin He, Dingshan Xiang, Daobin Wang

“…First, human drivers’ driving behaviors were classified into aggressive driving, normal driving, and conservative driving using a k-means clustering algorithm based on field dataset analysis. Next, an improved lane-changing model of HDVs, accounting for driving behavior, was developed by incorporating lane-changing duration and a lane-changing motivation function within a multi-objective optimization framework. …”
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Robust Sandstorm Image Restoration via Adaptive Color Correction and Saturation Line Prior-Based Dust Removal by Shan Zhou, Fei Shi, Zhenhong Jia, Guoqiang Wang, Jian Huang

“…Finally, the atmospheric scattering model is employed for comprehensive image restoration, ensuring that color correction and dust removal are optimized. …”
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Predicting metabolic dysfunction associated steatotic liver disease using explainable machine learning methods by Yihao Yu, Yuqi Yang, Qian Li, Jing Yuan, Yan Zha

“…The random forest (RF) model performed best in discriminative ability among 6 ML models, and the optimal 10-feature RF model was finally chosen. …”
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Full-chain comprehensive assessment and multi-scenario simulation of geological disaster vulnerability based on the VSD framework: a case study of Yunnan province in China by Li Xu, Shucheng Tan, Runyang Li

“…Furthermore, the Ordered Weighted Averaging (OWA) algorithm and the Partical Swarm Optimization-Support Vector Machine (PSO-SVM) model were combined to simulate future GDV scenarios for 2030–2050 under three development preferences: environment oriented, status quo, and economically oriented. …”
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Risk prediction and analysis of gallbladder polyps with deep neural network by Kerong Yuan, Xiaofeng Zhang, Qian Yang, Xuesong Deng, Zhe Deng, Xiangyun Liao, Weixin Si

“…This predictive model can be employed to differentiate the nature of polyps before surgery, enhancing diagnostic accuracy. …”
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Studying the influence of correction codes on coherent reception of M-PSK signals in the presence of noise and harmonic interference by V. D. Nguyen

“…The methods of statistical radio engineering, optimal signal reception theory and computer simulation modeling were used.Results. …”
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Research on path planning for coal mine rescue robots by ZHU Hongbo, YIN Hongliang

“…Firstly, an adjustment mechanism of collision constraint function is incorporated into the bidirectional A* algorithm to improve path safety. Next, a correction factor is incorporated into the cost function of the Bidirectional A* algorithm to ensure that the forward and backward search paths intersect, preventing them from diverging. …”
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Investigations into Picture Defogging Techniques Based on Dark Channel Prior and Retinex Theory by Lihong Yang, Zhi Zeng, Hang Ge, Yao Li, Shurui Ge, Kai Hu

“…The method involves building a two-stage optimization framework: in the first stage, global contrast enhancement is achieved by Retinex preprocessing, which effectively improves the detail information regarding the dark area and the accuracy of the transmittance map and atmospheric light intensity estimation; in the second stage, an a priori compensation model for the dark channel is constructed, and a depth-map-guided transmittance correction mechanism is introduced to obtain a refined transmittance map. …”
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Leveraging Spectral Neighborhood Information for Corn Yield Prediction with Spatial-Lagged Machine Learning Modeling: Can Neighborhood Information Outperform Vegetation Indices? by Efrain Noa-Yarasca, Javier M. Osorio Leyton, Chad B. Hajda, Kabindra Adhikari, Douglas R. Smith

“…Key predictors included spatially lagged spectral bands (e.g., Green_lag, NIR_lag, RedEdge_lag) and VIs (e.g., CREI, GCI, NCPI, ARI, CCCI), highlighting the value of integrating neighborhood data for improved corn yield prediction. This study underscores the importance of spatial context in corn yield prediction and lays the foundation for future research across diverse agricultural settings, focusing on optimizing neighborhood size, integrating spatial and spectral data, and refining spatial dependencies through localized search algorithms.…”
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Machine-learning-based reconstruction of long-term global terrestrial water storage anomalies from observed, satellite and land-surface model data by N. Mandal, P. Das, K. Chanda, K. Chanda

“…The most effective machine learning (ML) algorithms among convolutional neural network (CNN), support vector regression (SVR), extra trees regressor (ETR) and stacking ensemble regression (SER) models are evaluated at each grid cell to achieve optimal reproducibility. …”
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Enhancing cotton irrigation with distributional actor–critic reinforcement learning by Yi Chen, Meiwei Lin, Zhuo Yu, Weihong Sun, Weiguo Fu, Liang He

“…This study introduces a novel intelligent irrigation approach based on distributional reinforcement learning, ensuring that the algorithm simultaneously considers weather, soil, and crop conditions to make optimal irrigation decisions for long-term benefits. …”
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Сontrol of Intelligent Transport System in Minsk by D. V. Kapskiy, D. V. Navoy, P. A. Pegin

“…The paper considers algorithms for searching a maximum traffic volume of road vehicles in a traffic light cycle with a distributed intensity pulse and optimization of shifts under coordinated traffic flow control. …”
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A Dual-Variable Selection Framework for Enhancing Forest Aboveground Biomass Estimation via Multi-Source Remote Sensing by Dapeng Chen, Hongbin Luo, Zhi Liu, Jie Pan, Yong Wu, Er Wang, Chi Lu, Lei Wang, Weibin Wang, Guanglong Ou

“…A dual-variable selection strategy based on SHapley Additive exPlanations (SHAP) was developed, and a genetic algorithm (GA) was used to optimize the parameters of five machine learning models—elastic net (EN), least absolute shrinkage and selection operator (Lasso), support vector regression (SVR), Random Forest (RF), and Categorical Boosting (CatBoost)—to estimate the AGB of <i>Pinus kesiya</i> var. …”
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