Application of deep reinforcement learning in parameter optimization and refinement of turbulence models by Zhan Zhang

“…The aim of this study is to improve the accuracy of simulations by optimizing turbulence model parameters, in order to address the cost and time limitations of traditional wind tunnel tests and on-site measurements. …”
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Frequency Optimization Objective during System Prototyping on Multi-FPGA Platform by Mariem Turki, Zied Marrakchi, Habib Mehrez, Mohamed Abid

“…Many scenarios are proposed to obtain the most optimized results in terms of prototyping system frequency. …”
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Greedy gradient-free adaptive variational quantum algorithms on a noisy intermediate scale quantum computer by César Feniou, Muhammad Hassan, Baptiste Claudon, Axel Courtat, Olivier Adjoua, Yvon Maday, Jean-Philip Piquemal

“…However, practical implementations on current quantum processing units (QPUs) are challenging due to the noisy evaluation of a polynomially scaling number of observables, undertaken for operator selection and high-dimensional cost function optimization. We introduce an adaptive algorithm using analytic, gradient-free optimization, called Greedy Gradient-free Adaptive VQE (GGA-VQE). …”
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Optimization of Intelligent English Pronunciation Training System Based on Android Platform by Qianyu Cao, Hanmei Hao

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Bayesian Optimization of insect trap distribution for pest monitoring efficiency in agroecosystems by Eric Yanchenko, Thomas M. Chappell, Anders S. Huseth

“…In this study, a Bayesian optimization (BO) algorithm was used to learn more about the optimal distribution of a fine-scale trap network targeting Helicoverpa zea (Boddie), a significant agricultural pest across North America. …”
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Optimizing Feature Selection for IOT Intrusion Detection Using RFE and PSO by zahraa mehssen agheeb Alhamdawee

“…Two feature selection mechanisms, which are Particle Swarm Optimization Algorithm (PSO) and Correlation-based Feature Selection Recursive Feature Elimination (RFE) have been used to compare their performances. …”
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Reliability-Based Geotechnical Design Method Using the Gaussian Process Regression–Based Differential Evolution Algorithm by Kai Wen, Zemin Kuang, Wei Zeng, Sanyou Zeng, Yue Qiu

“…A fundamental challenge in reliability-based geotechnical design is optimizing cost-effectiveness while adhering to a predefined failure probability target. …”
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Optimized DINO model for accurate object detection of sesame seedlings and weeds by Yong Wang, ShunFa Xu, ZhenYuan Ye, KongHao Cheng

“…However, in environments where the target and the surrounding morphology are highly similar, such as distinguishing sesame seedlings from weeds, the problem essentially becomes one of optimizing edge detection algorithms for similar targets. …”
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RIS-assisted terahertz frequency band vehicle network capacity optimization by Fatang CHEN, Xiaoling LIU, Dan WANG, Ruofan ZHANG

“…In order to alleviate the spectrum scarcity and capacity limitation of the current wireless system, the terahertz frequency band was introduced and the reconfigurable intelligent surface (RIS) was used for auxiliary communication to construct a downlink vehicle network.Considering the constraints of limited total system power, QoS constraints of cellular mobile users, and randomness constraints of vehicle and user locations, a hybrid optimization model was established for optimal power allocation and optimal deployment of RIS with the aim of maximizing the total rate of vehicle users.Based on the balance method, linear transformation method, and element elimination method, the original NP-hard problem was transformed into a convex optimization problem with complex correlation constraints and multivariate coupling.The inner layer iteration was based on the Lagrange multiplier method to solve the optimal power allocation, and the outer layer iteratively solved the optimal deployment of RIS based on a improved genetic algorithm.The simulation results show that rationally deploying the number and distribution density of RIS nodes based on optimal power allocation can save costs while achieving a higher target total capacity.…”
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Improved RRT*-Connect Manipulator Path Planning in a Multi-Obstacle Narrow Environment by Xueyi He, Yimin Zhou, Haonan Liu, Wanfeng Shang

“…This paper proposes an improved RRT*-Connect algorithm (IRRT*-Connect) for robotic arm path planning in narrow environments with multiple obstacles. …”
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Reliability Optimization Model of Stop-Skipping Bus Operation with Capacity Constraints by Zhenhua Mou, Hu Zhang, Shidong Liang

“…The objective function is to minimize the total costs of bus operation system. Besides, a Genetic Algorithm combined with Monte Carlo Simulation method is defined and implemented to solve the reliability optimization model. …”
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Bi-Objective Optimization of Product Selection and Ranking Considering Sequential Search by Yuyang Tan, Hao Gong, Chunxiang Guo

“…Customer choices in online retailing are often influenced by sequential search behavior. However, most existing models ignore the dynamic property of this process. …”
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A New Image Encryption Method Using an Optimized Smart Codebook by Rami Sihwail, Dyala Ibrahim

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Optimal PMU Placement Considering with HVDC Links and Their Voltage Stability Requirements by Milad Dalali, Hosein Kazemi Karegar

“…However, it is not practical in real networks due to the relatively expensive cost of PMUs and other technical limitations. Optimal PMU Placement (OPP) is an optimization problem providing full observability of the power network with minimum number of PMUs. …”
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Conveyor X-Ray Tomosynthesis Imaging With Optimized Structured Sequential Illumination by Xu Ma, Dong Wang, Angela Cuadros, Tianyi Mao, Qile Zhao, Gonzalo R. Arce, Tingfa Xu

“…Subsequently, a genetic algorithm is developed to optimize the exposure sequence of X-ray sources, and mask patterns, and during the dynamic measurement process. …”
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Optimization mechanism of attack and defense strategy in honeypot game with evidence for deception by Lihua SONG, Yangyang JIANG, Changyou XING, Guomin ZHANG

“…Using game theory to optimize honeypot behavior is an important method in improving defender’s trapping ability.Existing work tends to use over simplified action spaces and consider isolated game stages.A game model named HoneyED with expanded action spaces and covering comprehensively the whole interaction process between a honeypot and its adversary was proposed.The model was focused on the change in the attacker’s beliefs about its opponent’s real identity.A pure-strategy-equilibrium involving belief was established for the model by theoretical analysis.Then, based on the idea of deep counterfactual regret minimization (Deep-CFR), an optimization algorithm was designed to find an approximate hybrid-strategy-equilibrium.Agents for both sides following hybrid strategies from the approximate equilibrium were obtained.Theoretical and experimental results show that the attacker should quit the game when its belief reaches a certain threshold for maximizing its payoff.But the defender’s strategy is able to maximize the honeypot’s profit by reducing the attacker’s belief to extend its stay as long as possible and by selecting the most suitable response to attackers with different deception recognition abilities.…”
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Optimization of Identification and Zoning Method for Landscape Characters of Urban Historic Districts by Hong YUN, Zixuan HU, Zehao HU

“…Then the research utilizes K-means clustering algorithm to optimize the zoning method for historic landscape characters. …”
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Shape optimization of non-uniform parametric piezoelectric energy harvester beam by Milad Hasani, Hossein Shahverdi

“…The model, validated through finite element method (FEM) simulations and experimental data, enables rapid analysis and optimization of PEHs. The Nelder-Mead optimization algorithm was employed to enhance power generation performance across three cross-sectional configurations: rectangular, trapezoidal, and quadratic. …”
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Binary program taint analysis optimization method based on function summary by Pan YANG, Fei KANG, Hui SHU, Yuyao HUANG, Xiaoshao LYU

“…Taint analysis is a popular software analysis method, which has been widely used in the field of information security.Most of the existing binary program dynamic taint analysis frameworks use instruction-level instrumentation analysis methods, which usually generate huge performance overhead and reduce the program execution efficiency by several times or even dozens of times.This limits taint analysis technology’s wide usage in complex malicious samples and commercial software analysis.An optimization method of taint analysis based on function summary was proposed, to improve the efficiency of taint analysis, reduce the performance loss caused by instruction-level instrumentation analysis, and make taint analysis to be more widely used in software analysis.The taint analysis method based on function summary used function taint propagation rules instead of instruction taint propagation rules to reduce the number of data stream propagation analysis and effectively improve the efficiency of taint analysis.For function summary, the definition of function summary was proposed.And the summary generation algorithms of different function structures were studied.Inside the function, a path-sensitive analysis method was designed for acyclic structures.For cyclic structures, a finite iteration method was designed.Moreover, the two analysis methods were combined to solve the function summary generation of mixed structure functions.Based on this research, a general taint analysis framework called FSTaint was designed and implemented, consisting of a function summary generation module, a data flow recording module, and a taint analysis module.The efficiency of FSTaint was evaluated in the analysis of real APT malicious samples, where the taint analysis efficiency of FSTaint was found to be 7.75 times that of libdft, and the analysis efficiency was higher.In terms of accuracy, FSTaint has more accurate and complete propagation rules than libdft.…”
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Classification of finger movements through optimal EEG channel and feature selection by Murside Degirmenci, Yilmaz Kemal Yuce, Matjaž Perc, Matjaž Perc, Matjaž Perc, Matjaž Perc, Matjaž Perc, Yalcin Isler

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