Optimization of UAV Airfoil Based on Improved Particle Swarm Optimization Algorithm by Tieying Jiang, Liang Jiang

“…The parametric mathematical model of the airfoil and aerodynamic parameter proxy model of airfoil were constructed using the Hicks-Henne improved function and CFD solution sample, focusing on the issues with particle swarm optimization algorithms such as slow convergence, a tendency to fall into local optimal solutions, and oscillation at a late stage; an optimization method for the low-speed airfoil of a small UAV based on improved particle swarm optimization was developed. …”
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Reduction algorithm based on supervised discriminant projection for network security data by Fangfang GUO, Hongwu LYU, Weilin REN, Ruini WANG

“…In response to the problem that for dimensionality reduction, traditional manifold learning algorithm did not consider the raw data category information, and the degree of clustering was generally at a low level, a manifold learning dimensionality reduction algorithm with supervised discriminant projection (SDP) was proposed to improve the dimensionality reduction effects of network security data.On the basis of the nearest neighbor matrix, the label information of the raw data category was exploited to construct a supervised discriminant matrix in order to translate unsupervised popular learning into supervised learning.The target was to find a low dimensional projective space with both maximum global divergence matrix and minimum local divergence matrix, ensuring that the same kind of data was concentrated and heterogeneous data was scattered after dimensionality reduction projection.The experimental results show that the SDP algorithm, compared with the traditional dimensionality reduction algorithms, can effectively remove redundant data with low time complexity.Meanwhile the data after dimensionality reduction is more concentrated, and the heterogeneous samples are more dispersed, suitable for the actual network security data analysis model.…”
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ε-approximate spatial-window aggregation algorithm in wireless sensor networks by Jing GAO, Jian-zhong LI, Yu LIU

“…An efficient ε-approximate spatial-window aggregate query processing technique was proposed to approximate aggregate values over arbitrary regions with arbitrary accuracy.A dynamic programming algorithm was devised to compute minimum number of data to refine approximate summation to reach arbitrary accuracy.The proposed algorithm was efficient to compute minimum/maximum values by only transmitting values promising to be in the exact results in order to reduce energy consumption.The experiment using real-world data demonstrates that the algorithms provide high quality results in arbitrary region and reach arbitrary accuracy with low energy cost.…”
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Optimization of Railway Transportation Planning by Combining TST Model and Genetic Algorithm by Wei Cao, Fan Chen

“…These challenges include high transportation costs, low punctuality rates, and inefficient resource utilization. …”
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An Improved Algorithm of Wireless Sensor Networks Routing Protocol Based on LEACH by Jinshen Weng, Huabiao Qin, Zongguo Zhang

“…One of the most popular research focuses of wireless sensor network is postponing the life cycle of sensor network as well as reducing energy consumption.An efficient clustering routing algorithm based on LEACH（low energy adaptive clustering hierarch）was presented，which is the representative of hierarchy based protocol in wireless sensor network.The residual energy，average energy and maximum energy are considered in this algorithm while electing the cluster header.It can also limit the number of members of each cluster.At the same time，it can produce the first cluster header among the cluster heads which will use the multi-hop mode to balance the load of network.The simulation results show that this improved algorithm can reduce the energy consumption，extend the network life cycle and ensure the load balance of the system.…”
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An Improved SHEPWM Modulation Algorithm for Three-levelEnergy Feedback Inverter by WU Xuefeng, CHEN Jielian, WANG Xiong, SONG Qianru, YIN Weiheng

“…The maximum switching frequency of high power converters is limited by the heat dissipation system and cannot be randomly increased. …”
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Quantifying the Impact of Environmental Factors on the Methane Point-Source Emission Algorithm by Zixuan Wang, Linxin Wang, Ding Li, Lingjing Yang, Lixue Cao, Qin He, Kai Qin

“…Similarly, elevated water vapor levels can lead to a maximum error of −16.2%. These findings highlight the substantial challenges in accurately detecting low-concentration CH₄ emissions. …”
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Conflict-based strategy combined integrated optimal conflict avoidance algorithm by Kejin Jia, Cheng Peng, Yun Du, Hongwei Wen, Yufei Gao, Zhe Zhang

“…Next, the low-level model of the traditional CBS algorithm is improved, transforming the path search process into two distinct algorithms with different focuses. …”
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Improving the functionality of wireless sensor networks through the use of reinforcement learning and metaheuristic based energy efficient system by Shiwei Zhang, Xinghan Liu

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Commercial Video Evaluation via Low-Level Feature Extraction and Selection by Xiangmin Lun, Mingxuan Wang, Zhenglin Yu, Yimin Hou

“…After extracting the low-level features of the videos, this paper improved the Correlation-Based Feature Selection (CFS) method which is widely used and proposed an algorithm named CFS-Spearmen which combined the Spearmen correlation coefficient and the classical CFS to select features. …”
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Optimizing Renewable Energy Systems Placement Through Advanced Deep Learning and Evolutionary Algorithms by Konstantinos Stergiou, Theodoros Karakasidis

“…As the world shifts towards a low-carbon economy, the strategic deployment of renewable energy sources (RESs) is critical for maximizing energy output and ensuring sustainability. …”
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Inhomogeneous Illumination Image Enhancement Under Extremely Low Visibility Condition by Libang Chen, Jinyan Lin, Qihang Bian, Yikun Liu, Jianying Zhou

“…Despite improvements through neural network-based approaches, these techniques falter under extremely low visibility conditions exacerbated by inhomogeneous illumination, which degrades deep learning performance due to inconsistent signal intensities. …”
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Exact and Approximation Algorithms for Task Offloading with Service Caching and Dependency in Mobile Edge Computing by Bowen Cui, Jianwei Zhang

“…Considering the requirements of applications for service caching and task dependency, we define an optimization problem to minimize the delay under the constraint of maximum completion cost and present a <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mo>(</mo><mn>1</mn><mo>+</mo><mi>ϵ</mi><mo>)</mo></mrow></semantics></math></inline-formula>-approximation algorithm and an exact algorithm. …”
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Simulations suggest offshore wind farms modify low-level jets by D. Quint, D. Quint, J. K. Lundquist, J. K. Lundquist, J. K. Lundquist, D. Rosencrans

“…We validate the algorithm to the extent possible by comparing LLJs identified by lidar, constrained to the lowest 200 m, to WRF simulations of these very low LLJs (vLLJs). …”
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A combined algorithm for tunnel personnel localization based on error areal division by Jian Xu, Haiying Wang, Yiqing Ren, Yingzhi Zhang

“…The positioning errors of some areas are greater than the average positioning errors, which lead to a low positioning accuracy. In this study, based on the simulation of the positioning error areal distributions of the quadrilateral centroid localization and maximum likelihood estimation algorithms, the causes for large positioning errors in upper and lower edges and four corners were analyzed. …”
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Population Economic Transfer Function Model Based on Genetic Tabu Search Algorithm by Qian Wang

“…Aiming at the problem that the evaluation effect of the traditional analysis model of population economic transfer is not good, a population economic transfer function model based on the genetic tabu search algorithm is proposed. Firstly, the defects of the genetic algorithm are analyzed, and the tabu search algorithm is integrated into the genetic tabu search algorithm to obtain the genetic tabu search algorithm, which avoids the problems of premature convergence and low search efficiency. …”
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Topology restoration algorithm for heterogeneous sensor networks based on connected dominating tree by Ting-jun SHI, Xu-ming FANG, Yun YANG

“…For currently lacking the study of the topology restoration algorithm for heterogeneous sensor networks,a topology restoration algorithm for heterogeneous sensor networks based on connected dominating tree (HSNTR) was proposed.Firstly the algorithm constructed a virtual backbone forwarding data at very low cost,and secondly when a node fails,the algorithm would dynamically locally restore the backbone to make it still connect and cover all nodes.Theoretical analysis proved the maximum number of nodes the algorithm uses during constructing and restoring the backbone.Simulation analysis showed that the algorithm is better than other algorithms in terms of energy efficiency,scalability and reliability.…”
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Harmonic Measurement Algorithm of Power System Integrating Wavelet Transform and Deep Learning by Hanshu Jiang, Yutian Li, Zhu Liu, Guanghao Wu, Zeyang Liu

“… INTRODUCTION: The problem of low accuracy in harmonic measurement is a significant challenge in power systems. …”
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Structural Parameter Identification Using Multi-Objective Modified Directional Bat Algorithm by LIU Li-jun, LIN Ying-hai, SU Yong-hui, LEI Ying

“…In the truss damage identification case， MOMDBA demonstrated superior performance under challenging conditions， including 3% noise in the input data. The algorithm successfully identified damage locations and severities， achieving a maximum relative error of 3.85% for damaged elements. …”
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Optimal restoration algorithm for active distribution network considering island mode of the microgrids by J. Marín Quintero, J. Ayala Uribe, O. Bernal, C. Orozco Henao

“…With the growing integration of active agents such as Microgrids (MGs) and distributed generation (DG) into the electrical grid, it becomes crucial to develop methods that restore power to the maximum number of users in the shortest possible time, while considering the dynamic behavior of the network. …”
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