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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Deep-learning Enhanced CT Reconstruction Algorithm for Multiphase-flow Measurement by Qian CHEN, Baodi YU, Yanwei QIN, Sunyang WANG, Xiaohui SU, Xin JIN, Fanyong MENG

“…Focusing on the gas–liquid two-phase flow in multiphase flow, this paper addresses limited angle artifacts and excessive reconstruction time in mesoscale dynamic structures and proposes a U-Net-enhanced simultaneous iterative reconstruction technique (SIRT) reconstruction algorithm for bubble-structure measurements based on gas–liquid two-phase flow. …”
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Direct localization algorithm of the aerial target based on external radiation source by Nan XIA, Danyang GAO, Baohui XING, Yaning WANG

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Precision Marketing Method of E-Commerce Platform Based on Clustering Algorithm by Bei Zhang, Luquan Wang, Yuanyuan Li

“…In this paper, we present the formulation and data mining of the correlation rules based on the clustering algorithm through the definition and procedure of the algorithm. …”
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A Data-Driven Front Tracking Algorithm for Autonomous Undersea Vehicles by Jieyang LU, Yongpeng WEN, Qian GUO, Xinke ZHU, Junsheng JIAO

“…To meet the requirement for adaptive observation of autonomous undersea vehicles(AUVs), a data-driven ocean front tracking algorithm was designed. This algorithm constructed a hybrid temperature field prediction model based on Gaussian process regression(GPR) and particle swarm optimization(PSO). …”
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Object Detection Algorithm Based on Feature Enhancement and Anchor-object Matching by LI Cheng-yan, ZHAO Shuai, CHE Zi-xuan

“…In the detector part of the algorithm, the Anchor-object matching method combined with the SSD multi-layer feature map is used to construct the corresponding Anchor package for each detection target. …”
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Accuracy and robustness evaluation of deep learning algorithms in facial recognition systems by Jing Zhang, Ningyu Hu

“…To solve the high cost and low accuracy in facial recognition system, a facial recognition system based on deep learning algorithm is designed in this paper. First, the YOLO model is improved by introducing the EfficientNet to enhance the performance of the facial detection model. …”
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Exact and greedy algorithms of allocating experts to maximum set of programmer teams by A. A. Prihozhy

“…It develops and compares two algorithms: a heuristic greedy and exact optimal. The greedy algorithm iteratively solves the set cover problem on a matrix of expert competences until can create the next workable team of remaining experts. …”
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Research on Path Planning Multiple Mobile Robots Based on the LAPGWO Algorithm by Wan Xu, Dongting Liu, Ao Nie, Junqi Wang, Shijie Liu

“…Given that the traditional optimization algorithm (GWO) often encounters problems like local optimum, and the convergence efficiency is not satisfactory in the path planning task of multiple mobile robots, an improved grey wolf optimization algorithm (LAPGWO) based on the combination of the logistic chaotic mapping and the artificial potential field method (APF) is proposed. …”
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The Automation of C Program Verification by Symbolic Method of Loop Invariants Elimination by Dmitry Kondratyev, Ilya Maryasov, Valery Nepomniaschy

“…This extension includes the verification method of iterations over changeable arrays possibly with loop exit in C-light programs. …”
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A genetic algorithm based method of optimizing dispersion matrix for RDSM system by Peng ZHANG, Xiaoping JIN, Dongxiao CHEN

“…Rectangular differential spatial modulation (RDSM) is a multi-antenna incoherent modulation technology with high spectral efficiency, low power consumption, and zero-overhead for channel estimation.RDSM is especially suitable for 6G communication systems, such as fast-moving Internet of vehicles, Internet of things, cellular networks, etc.However, the construction of the sparse rectangular unitary space-time dispersion matrix (DM) at transmitter is a problem.The proposed Genetic algorithm (GA) will result in less computational complexity than the currently used random research.The fitness of GA was calculated by the rank and determinant criterion (RDC) method to avoid discussions in differential system.Due to characteristics of constellation symbols of RDSM, the proposed method reduced the computational complexity during each single iteration in GA.The simulation results show that the optimized DMS can significantly improve the bit error rate (BER) performance of the RDSM system.Compared with random search, the low-complexity GA effectively improves the DMS optimization efficiency of RDSM.The computational complexity required for optimizing DMS is about 0.1% of random search optimization method.…”
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Dance video action recognition algorithm based on improved hypergraph convolutional networks by Ni Zhen, Yiyi Jiang

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Application of Multi-Strategy Controlled Rime Algorithm in Path Planning for Delivery Robots by Haokai Lv, Qian Qian, Jiawen Pan, Miao Song, Yong Feng, Yingna Li

“…Further experimental analysis confirmed that the algorithm’s multi-strategy framework effectively suppresses the impact of coordinate and dimensional differences on path quality during iteration, making it more suitable for delivery robot path planning scenarios. …”
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One-way hash function construction based on Chen-type hyper-chaotic system and key-stream by REN Hai-peng, ZHUANG Yuan

“…A scheme of constructing one-way hash function based on Chen-type hyper-chaotic system and key-stream was proposed. …”
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The algorithm of the engineering method of parameter optimization dump working equipment of the motor grader by Ignatov S.D.

“…This paper presents an analysis of existing motor grader blade equipment designs, develops an engineering methodology optimization algorithm, and examines the main stages of its implementation, including modeling, iterative optimization procedures, and experimental validation. …”
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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

“…During each iteration， solutions were evaluated based on multiple objectives， and a Pareto frontier was constructed by assigning random weights to these objectives. …”
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Evaluation of the Efficiency of Metaheuristic Algorithms in the Optimal Design of Pile Wall Retaining Systems by Farshad Taiyari

“…For optimization purposes, an integration of the OpenSees software with the MATLAB platform is done to join the modeling space with the mentioned optimization algorithms. The number of iterations for each run is assumed to be 400, which is also considered a termination criterion. …”
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Research on Point Cloud Registration and Stitching Fusion Algorithm Based on GCN-PRFNet by Wenhao Zeng, Gongbing Su, Zixuan Su, Rui Li, Jun Chen

“…., the accuracy of point cloud registration and stitching in robot navigation directly affects the accuracy of map construction. Many researchers have proposed various algorithms for deep learning-based point cloud registration and stitching methods with good performance, and although there are end-to-end methods that have made progress, they still have limitations in local feature fusion efficiency and geometric detail retention. …”
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Oil and Gas Industry Companies’ Classification and Ordering by the Level of Investment Attractiveness Algorithm by Chernova Natalia L., Serhiienko Olena A., Huz Ostap B.

“…To obtain the final division of objects into a given number of clusters, it is suggested to use iterative algorithms. Depending on the contentual interpretation of the received clusters, one is chosen whose objects can potentially be included in the investment portfolio. …”
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Algorithm study of digital HPA predistortion using one novel memory type BP neural network by Chun-hui HUANG, Yong-jie WEN

“…Based on the characteristic analysis of the high power amplifier (HPA) in wide-band CMMB repeater stations,a novel neural network was proposed which can respectively process the memory effect and the nonlinear of power amplifier.The novel model based on real-valued time-delay neural networks(RVTDNN) uses the Levenberg-Marquardt (LM) optimization to iteratively update the coefficients of the neural network.Due to the new parameters w⁰in the novel NN model,the modified formulas of LM algorithm were provided.Next，in order to eliminate the over-fitting of LM algorithm,the Bayesian regularization algorithm was applied to the predistortion system.Additionally,the predistorter of CMMB repeater stations based on the indirect learning method was constructed to simulate the nonlinearity and memory effect of HPA.Simulation results show that both the NN models can improve system performance and reduce ACEPR (adjacent channel error power ratio ) by about 30 dB.Moreover,with the mean square error less than 10⁻⁶,the coefficient of network for FIR-NLNNN is about half of that for RVTDNN.Similarly,the times of multiplication and addition in the iterative process of FIR-NLNNN are about 25% of that for RVTDNN.…”
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