Investigation on the Aerodynamic Parameters of the Triangle Shape of Tall Buildings by Using of CFD Method by Mehdi Noormohamadian, Eysa Salajegheh

“…In this research, three optimized triangular models will be investigated using the computational fluid dynamics method. …”
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Reliability Analysis of Three-dimensional Soil Slopes Considering Spatial Variability of Soil Parameters by Wan Yukuai, Zhou Yuqi, Shao Linlan, Wang Yuke, Zhang Fei

“…To address these limitations, this study employs the covariance matrix decomposition method to generate 3D lognormal random fields for soil parameters, enabling efficient modeling of spatial variability. The particle swarm optimization (PSO) algorithm is refined with enhanced termination criteria and integrated with the 3D Bishop method to search for the minimum factor of safety (F). …”
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Research on the ordering strategy problem in supply chain with profit allocation under two-level price-fluctuation sales. by Minchao Zheng, Ying Yu, Jiayang Xu, Yunzhi Mu

“…A discrete algorithm is proposed to approximate the optimal solution, with its convergence rigorously proven. …”
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Credit approval classification through a WASD neuronet by Mourtas Spyridon D.

“…In light of this, a new weights and structure determination (WASD) neuronet has been developed to address the two issues of credit approval mentioned above, as well as to manage its particular features. We improve the learning process of the WASD algorithm with a novel activation function for optimal adaptation to the credit approval model, motivated by the finding that WASD neuronets perform better than traditional back-propagation neuronets in terms of slow training speed and trapping in a local minima. …”
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Research on Heat Dissipation Effect of Radiator Structure of Disc Brake for High-speed Train by Xin WANG, Guoquan WANG, Yong CHEN

“…In order to improve the safety of the braking process of high-speed train, the brake disc heat dissipation structure needs to be optimized. …”
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Research on autonomous obstacle avoidance of mountainous tractors based on semantic neural network and laser SLAM. by Ningjie Chang, Xianghai Yan, Bingxin Chen, Yiwei Wu, Liyou Xu

“…Finally, the 3D map of mountain environment containing semantic information is further constructed by combining laser SLAM technology. A* algorithm is used on the map for global path planning to realize the autonomous obstacle avoidance function of mountain tractors. …”
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A Reliability Assessment Method for Distribution Networks Based on Conditional Generative Adversarial Network and Multi-agent Reinforcement Learning by Huihui XU, Yunfei TIAN, Yuyang ZHAO, Jing PENG, Qingxin SHI, Rui CHENG

“…Secondly, a multi-agent reinforcement learning (MARL) model is established, and a training algorithm integrating imitation learning and exploratory learning is proposed, enabling the agents to acquire optimal policies through interactive learning with an expert experience model. …”
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KT-Deblur: Kolmogorov–Arnold and Transformer Networks for Remote Sensing Image Deblurring by Baoyu Zhu, Zekun Li, Qunbo Lv, Zheng Tan, Kai Zhang

“…Supported by the Fast Spatial Feature Module (FSFM), it effectively improves the model’s ability to handle complex blur patterns. …”
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Research on anode inlet pressure control strategy of PEMFC through hardware-in-the-loop test by Jing Zhang, Zhongkao Tan, Chengzhi Fan, Jingying Tan, Guoan Luo, Weiye Lu, Zhiqiang Liang, Cong Xu, Yixuan He, Xiaodong Wang, Zhongmin Wan

“…Through the HIL test, it is verified that the NLADRC algorithm is also applicable to the FCU. The model and control method proposed in this paper can be used to optimize the control of the hydrogen supply system and improve the dynamic performance of PEMFC.…”
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The significance of the leaf area index for evapotranspiration estimation in SWAT-T for characteristic land cover types of West Africa by F. Merk, T. Schaffhauser, F. Anwar, Y. Tuo, J.-M. Cohard, M. Disse

“…The comprehensive parameter set is then optimized using the shuffled complex evolution algorithm. …”
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The Application of the Gestalt Theory in Music Psychotherapy for Piano by Fukun Cai

“…Compared with the classification accuracies of DBN, restricted Boltzmann machine (RBM), and K nearest neighbor (kNN) algorithms in mixed music environments, the classification effects were improved by about 3.49%, 12.89%, and 7.24%. …”
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Sparse Feature-Weighted Double Laplacian Rank Constraint Non-Negative Matrix Factorization for Image Clustering by Hu Ma, Ziping Ma, Huirong Li, Jingyu Wang

“…We also propose an efficient alternating iterative update algorithm to optimize the proposed model and provide a theoretical analysis of its performance. …”
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Enhancing prediction of crop yield and soil health assessment for sustainable agriculture using machine learning approach by Kapil Netaji Vhatkar, Shweta Ashish Koparde, Sonali Kothari, Jayesh Sarwade, Kishor Sakur

“…The goal of this research is • to make sophisticated models for precise crop production forecasting and thorough evaluation of soil health, • to improve sustainability by optimize farming methods, and • to assist farmers in making well-informed decisions.Iterative Partitioning-Ensemble Filter (IP-EF) is a technique used for feature selection, enhancing model performance by iteratively partitioning data and refining feature subsets. …”
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RUL Prediction Based on MBGD-WGAN-GRU for Lithium-Ion Batteries by Zhiguo Zhao, Ke Li, Yibo Dai, Biao Chen, Yeqin Wang, Qian Zhao

“…Subsequently, the mini-batch stochastic gradient descent algorithm is employed to optimize a Wasserstein generative adversarial network, thereby augmenting the training set and enhancing data diversity. …”
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Presentation of a Novel Method for Prediction of Traffic with Climate Condition Based on Ensemble Learning of Neural Architecture Search (NAS) and Linear Regression by Javad Artin, Amin Valizadeh, Mohsen Ahmadi, Sathish A. P. Kumar, Abbas Sharifi

“…This study presented a method based on ensemble learning to predict urban traffic congestion based on weather criteria. We used the NAS algorithm, which in the output based on heuristic methods creates an optimal model concerning input data. …”
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EdgeGuard: Decentralized Medical Resource Orchestration via Blockchain-Secured Federated Learning in IoMT Networks by Sakshi Patni, Joohyung Lee

“…We have made several technological advances, including a lightweight blockchain consensus mechanism designed for IoMT networks, an adaptive edge resource allocation method based on reinforcement learning, and a federated learning algorithm optimized for medical data with differential privacy. …”
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Risk Assessment of Constructing Deep Foundation Pits for Metro Stations Based on Fuzzy Evidence Reasoning and Two-tuple Linguistic Analytic Network Process by Jie Jiang, Guangyang Liu, Xi Huang, Xiaoduo Ou

“…Finally, the overall risk grade of the construction project is evaluated by aggregating the risk levels of all risk events through an evidence-reasoning algorithm. The analysis results for a deep foundation pit for a station on Line 5 of Nanning Metro show that the model provides a quantitative basis for determining expert weights and risk loss weights reasonably and improving the reliability of the evaluation system. …”
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A Bilevel Dynamic Pricing Methodology for Electric Vehicle Charging Stations Considering the Drivers’ Charging Willingness by Xin Fang, Bei Bei Wang, Su Yang Zhou, C. C. Chan

“…Meanwhile, the lower-level model represents CS price adjustments as a noncooperative game, solved via a greedy algorithm. …”
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Landslide Segmentation in High-Resolution Remote Sensing Images: The Van–UPerAttnSeg Framework with Multi-Scale Feature Enhancement by Chang Li, Quan Zou, Guoqing Li, Wenyang Yu

“…In addition, this study introduces a sliding window algorithm based on Gaussian fusion as a post-processing method, which optimizes the prediction of landslide edge in high-resolution remote sensing images and ensures the context reasoning ability of the model. …”
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Research on Hybrid Architecture Neural Networks for Time Series Prediction by Fujin Zhuang, Xiao Chen, Punyaphol Horata, Khamron Sunat

“…This multi-module collaborative architecture effectively processes multi-scale features of time series data while providing model interpretability. Through comparative analysis of various optimization algorithms’ convergence performance and prediction accuracy, this study found that the AdamW optimizer, with its effective weight decay mechanism and adaptive learning rate, demonstrated superior performance in training stability and generalization capability, with MSE and R2 metrics outperforming traditional optimizers. …”
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