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Articles 601 - 630 of 17469
Full-Text Articles in Entire DC Network
Attitude Control Of Quadrotor Uav Based On Disturbance Observer And Command Filtering, Boning Li, Ming Chen, Shuchang Qi, Haoran Meng, Lei Wang
Attitude Control Of Quadrotor Uav Based On Disturbance Observer And Command Filtering, Boning Li, Ming Chen, Shuchang Qi, Haoran Meng, Lei Wang
Journal of System Simulation
Abstract: A finite-time fault-tolerant control scheme based on backstepping was proposed for the attitude tracking control problem of quadrotor UAVs. A finite-time neural network disturbance observer was designed, which could quickly compensate for the impacts of actuator failures and external disturbances, thereby enhancing the system's robustness. A first-order command filter and a compensation mechanism were introduced, which could avoid the computational complexity caused by differentiating the virtual control law and eliminate the influence of filtering errors. The hyperbolic tangent function was selected as the constraint function for the input torque, which restricted the input signal to prevent excessive magnitude …
Research On Path Smoothing Processing Of Mobile Robot Based On Improved A* Algorithm, Mengyuan Chen, Guifang Qiao, Xu Zou, Jiayu Cao, Lei Tian
Research On Path Smoothing Processing Of Mobile Robot Based On Improved A* Algorithm, Mengyuan Chen, Guifang Qiao, Xu Zou, Jiayu Cao, Lei Tian
Journal of System Simulation
Abstract: Traditional bidirectional A* algorithm has many path inflection points, undergoes smoothness, and faces diagonal obstacles in path traversing. Therefore, an improved bidirectional A* algorithm was proposed. Local path constraint search was added to the forward search and backward search, respectively to solve the problem of planning paths traversing diagonal obstacles, and the effectiveness of the improved bidirectional A* algorithm to avoid traversing diagonal obstacles was verified through simulations. The path inflection points were optimized by introducing the cubic B-spline curve, and the paths before and after smoothing were tracked and controlled, respectively by using the differential-driven mobile robot. The …
Boolean Network Model Optimization Based On Neural Network And Genetic Programming, Jinlin Tang, Yan Wang, Xiang Liu, Tuanjie Wang, Zhicheng Ji
Boolean Network Model Optimization Based On Neural Network And Genetic Programming, Jinlin Tang, Yan Wang, Xiang Liu, Tuanjie Wang, Zhicheng Ji
Journal of System Simulation
Abstract: To address the issues of complex node relationships and low accuracy in large-scale Boolean network inference, a new optimization algorithm integrated with long short-term memory (LSTM) networks and genetic programming was proposed. An enhanced LSTM network combined with a self-attention mechanism was designed to extract potential regulatory nodes from time-series data. These nodes were utilized as terminals of the syntax tree for the design of the genetic programming algorithm, and new operators were introduced to optimize Boolean function search. Experimental results have demonstrated that the proposed method significantly outperforms the most advanced existing algorithms in inference accuracy. The Boolean …
Evolutionary Reinforcement Learning Based On Elite Instruction And Random Search, Jian Di, Xue Wan, Limei Jiang
Evolutionary Reinforcement Learning Based On Elite Instruction And Random Search, Jian Di, Xue Wan, Limei Jiang
Journal of System Simulation
Abstract: Evolutionary reinforcement learning currently suffers from low sample efficiency, a single coupling method, and poor convergence, which can affect its performance and scaling. To address this issue, an improved algorithm based on elite gradient instruction and double random search was proposed. The direction of the reinforcement strategy gradient update was corrected by introducing elite strategy gradient guidance carrying evolutionary information during reinforcement strategy training. Double stochastic search was used to replace the original evolutionary component, reducing the complexity of the algorithm while making the policy search meaningful and controllable in the parameter space. The introduction of complete replacement information …
Research On Temperature Compensation Technology Of Fiber Optic Gyroscope Based On Iscso-Bp Neural Network Model, Zhili Zhang, Jin Liu, Zhaofa Zhou, Zhe Liang, Yunhao Zhang
Research On Temperature Compensation Technology Of Fiber Optic Gyroscope Based On Iscso-Bp Neural Network Model, Zhili Zhang, Jin Liu, Zhaofa Zhou, Zhe Liang, Yunhao Zhang
Journal of System Simulation
Abstract: To address the issue that changes in ambient temperature significantly affect the output accuracy of the fiber optic gyro (FOG), which causes zero bias drift, increases measurement errors, and limits their application accuracy in complex environments, a temperature compensation model based on BP neural networks was proposed. To improve the performance of neural networks, the sand cat swarm optimization (SCSO) was improved, and the improved SCSO (ISCSO) was used to optimize the weights and thresholds of BP neural networks. Experimental results show that using the ISCSO-BPNN temperature compensation model to compensate for the gyro's temperature errors significantly improves the …
Dynamic Supernetwork Modeling Of Command Information System Based On Task Timing, Xuehuan Qiu, Zhiming Dong, Liang Li, Zhuoli Liu
Dynamic Supernetwork Modeling Of Command Information System Based On Task Timing, Xuehuan Qiu, Zhiming Dong, Liang Li, Zhuoli Liu
Journal of System Simulation
Abstract: Due to the difficulty in reflecting the various information activities and interactions within the command information system using general modeling methods for complex system structure, the advantages of supernetwork in characterizing node heterogeneity and link multiplicity of the system were utilized. Based on the research on the mapping mechanism of the command information system across three domains, the dynamic and multifunctional properties of the functional network structure were analyzed. A dynamic supernetwork model based on task timing was constructed considering task requirements, providing model support for further research on complex interaction relationships in the command information system. The dynamic …
Research On Time Sequence Design Method Of Dynamic Simulation Scene For Starlight Navigation, Xiaoting Su, Xiaowei Zhang, Yi Tian, Qi Li, Shuaihao Wang
Research On Time Sequence Design Method Of Dynamic Simulation Scene For Starlight Navigation, Xiaoting Su, Xiaowei Zhang, Yi Tian, Qi Li, Shuaihao Wang
Journal of System Simulation
Abstract: To solve the problem of misidentification of star maps due to time sequence mismatch in the hardware-in-the-loop simulation system of star navigation, where star trackers with different shutter types (global shutter and rolling shutter) and star simulators with varying refresh display methods (whole frame refresh and line sweep refresh) operated without synchronization, a time sequence design method of the dynamic simulation scene for starlight navigation without the need of external synchronization signals was proposed. The method could design the refresh frequency and duty cycle of the corresponding star simulators according to the detector integration time of the tested star …
Robot Path Planning Optimization Based On Fusion Of Improved Ant Colony Algorithm And A* Algorithm, Lanying Yang, Chao Li, Haifeng Zou, Jiangtao Wan, Renqiang Zhang, Hui Liu, Hong Lu
Robot Path Planning Optimization Based On Fusion Of Improved Ant Colony Algorithm And A* Algorithm, Lanying Yang, Chao Li, Haifeng Zou, Jiangtao Wan, Renqiang Zhang, Hui Liu, Hong Lu
Journal of System Simulation
Abstract: To improve slow search efficiency and achieve real-time obstacle avoidance in traditional ant colony algorithms, an adaptive ant colony algorithm was proposed. A guidance direction mechanism was introduced to shorten the time of node selection. The A* algorithm's path-finding mechanism was introduced into the heuristic function to reduce the length and number of circles of the optimal path solution. The route planned by the traditional A* algorithm was used as the initial iteration data of the ant colony algorithm in global path planning, so as to solve the problem of slow initial convergence of the ant colony algorithm. The …
Secret Key Generation Based On The Physical Layer Characteristics For Iot Networks, Abdullah Dakhlallah Alshamdayn
Secret Key Generation Based On The Physical Layer Characteristics For Iot Networks, Abdullah Dakhlallah Alshamdayn
Doctoral Dissertations
The rapid expansion of low-resource devices, coupled with advances in telecommunications, has significantly increased the number of connected devices and enabled the development of affordable, energy-efficient, portable, and high-performance sensors for diverse applications. However, this convenience comes with security and privacy concerns related to the reliability of hardware, software, and communication infrastructure. The extensive interconnectivity of limited-resource devices and the transmission of large data volumes pose significant security challenges in wireless networks. The future wireless technologies, such as 5G, will enable the transfer of critical data, including personal, financial, military, and industrial information, necessitating secure communication in wireless networks. Generally, …
A Novel Hybrid Intrusion Detection Model: A New Metaheuristic Approach For Feature Selection Based On Ai Techniques For Cyber Threat Detection, Maryam Mahdi Alhusseini, Alireza Rouhi
A Novel Hybrid Intrusion Detection Model: A New Metaheuristic Approach For Feature Selection Based On Ai Techniques For Cyber Threat Detection, Maryam Mahdi Alhusseini, Alireza Rouhi
Iraqi Journal for Computer Science and Mathematics
The rapid increase in internet usage, digital transformation, and the rise of interconnected devices have greatly expanded the attack surface, introducing new and evolving cybersecurity challenges. Conventional security solutions frequently have difficulty adjusting to complex threats and the vast dimensionality of network traffic data, particularly in the case of imbalanced datasets. To tackle these challenges, this research introduces a Hybrid Intrusion Detection System (HyIDS-EVO) that combines the Energy Valley Optimizer (EVO) for feature selection and dimensionality reduction with machine learning classifiers, which include Support Vector Machine (SVM), Random Forest (RF), Decision Tree (DT), and K-Nearest Neighbors (KNN). The system’s effectiveness …
Cv: Young "Paul" Kim (Computer Engineering), Young "Paul" Kim
Cv: Young "Paul" Kim (Computer Engineering), Young "Paul" Kim
ECaMS Department Faculty Curricula Vitae
No abstract provided.
A Robust And Energy-Efficient Federated Ids For Iiot Using Spiking Neural Networks And Differential Evolution With Adversarial Resilience, Mohammad Othman Nassar
A Robust And Energy-Efficient Federated Ids For Iiot Using Spiking Neural Networks And Differential Evolution With Adversarial Resilience, Mohammad Othman Nassar
Iraqi Journal for Computer Science and Mathematics
The Industrial Internet of Things (IIoT) is faced with increasing cybersecurity threats that require lightweight, fast, and resilient intrusion detection systems (IDS). This study presents a novel federated IDS framework that integrates federated learning (FL), Spiking Neural Networks (SNNs), and differential evolution (DE). The use of SNNs within a federated context is a rare and innovative contribution that enables effective temporal feature extraction from IIoT traffic. DE is employed as a global optimization mechanism, enhancing robustness and generalization beyond conventional federated aggregation. To further strengthen resilience, synthetic adversarial noise is injected during training, allowing evaluation in realistic poisoning scenarios. The …
Cal Poly (Cp) Legged Robot, Sebastian Barboza, Jonathan Mchale, Isabella Sorensen, Isaac Golan
Cal Poly (Cp) Legged Robot, Sebastian Barboza, Jonathan Mchale, Isabella Sorensen, Isaac Golan
Mechanical Engineering
The Navy spends $60 billion annually on dangerous ship maintenance performed by sailors. To save lives and resources, the Naval Surface Warfare Center (NSWC) is looking for robots to replace sailors and navigate ships to perform various tasks. Robots with tracks and wheels have been most recently explored by NSWC, however they have encountered significant problems navigating the ships, especially through naval ship doorways with a significant ledge. By using a legged robot, our team hopes to solve these problems and have a robot that can navigate the ship with relative ease and stability.
Mosquito Classification And Explainability From Image Data Via Deep Learning Techniques, Farhat Binte Azam
Mosquito Classification And Explainability From Image Data Via Deep Learning Techniques, Farhat Binte Azam
USF Tampa Graduate Theses and Dissertations
According to the World Health Organization (WHO), mosquitoes are the deadliest animals on Earth, responsible for more human deaths annually than any other species. Mosquito-borne illnesses continue to pose severe risks to global health. In 2015 alone, there were an estimated 214 million malaria cases worldwide. Similarly, a 2016 report from the Centers for Disease Control and Prevention (CDC) revealed that Puerto Rico’s Department of Health received over 62,500 suspected cases of Zika, with 29,345 confirmed positive cases. In 2019, Southeast Asia experienced its worst dengue outbreak in recorded history. Of the approximately 4,500 mosquito species distributed across 34 genera, …
Retracted: Analysis Of Energy Sector Co2 Emanations Using Wavelet-Based Numerical Technique, Yeshwanth R., Kumbinarasaiah S.
Retracted: Analysis Of Energy Sector Co2 Emanations Using Wavelet-Based Numerical Technique, Yeshwanth R., Kumbinarasaiah S.
Iraqi Journal for Computer Science and Mathematics
This study aims to present the modified Chebyshev wavelet collocation method (CWCM) to investigate and obtain the numerical approximation of $CO_2$ emissions from the energy sector utilizing the fractional mathematical model. The need for energy rises as the population grows. Burning fossil fuels produces a significant portion of the world's energy, which raises the atmospheric concentration of $CO_2$ and causes global warming. The combination of mathematical modeling studies and numerical simulations allows us to understand the $CO_2$ emissions from the energy sector. Our objective is to build an operational matrix of integration (OMI) based on Chebyshev wavelets and use it …
Shifted Frequency Analysis Hybrid Simulation Algorithm Based On Multi-Rate Asynchronous Coordination, Yankan Song, Libin Wen, Ying Chen, Jinji Xi, Haoyuan Zhang, Li Xiong
Shifted Frequency Analysis Hybrid Simulation Algorithm Based On Multi-Rate Asynchronous Coordination, Yankan Song, Libin Wen, Ying Chen, Jinji Xi, Haoyuan Zhang, Li Xiong
Journal of System Simulation
Abstract: Large-scale AC/DC power systems exhibit complex dynamics across multiple time scales, and existing hybrid simulations suffer from interface delays and frequency losses during multi-rate coordination, compromising accuracy. To address this issue, a multi-rate asynchronous coordination method was proposed to construct hybrid simulations using shifted frequency analysis (SFA). Within the multi-area Thevenin equivalence (MATE) framework, the algorithm introduced an interpolation-based asynchronous coordination mechanism, effectively eliminating interface delays; by extending SFA theory and designing a universal interface model, it achieved lossless data exchange between partitions with different rates and model types. Case studies on an AC/DC test system demonstrate that …
Soft Sensor Modeling Based On Improved Transformer In Dual-Stream Framework, Hao Gu, Jiayu Wang, Weili Xiong
Soft Sensor Modeling Based On Improved Transformer In Dual-Stream Framework, Hao Gu, Jiayu Wang, Weili Xiong
Journal of System Simulation
Abstract: Industrial process information is highly nonlinear and dynamic, with long-term dependencies between data, making it difficult to adequately extract time-series features. To address this issue, an improved Transformer-based soft sensor model in a dual-stream framework was proposed. The data were segmented and expanded. The features were extracted in parallel using a dual-stream structure combining a convolutional neural network with a self-attention mechanism and the improved Transformer model. The dual-stream features were fused for soft sensor regression. Residual connections were further introduced to accelerate the convergence speed of the model, and an orthogonal random features-based improved multi-head attention mechanism was …
Path Planning Of Improved Rrt Algorithm Based On Deep Reinforcement Learning, Xiuman Liang, Ziliang Liu, Zhendong Liu
Path Planning Of Improved Rrt Algorithm Based On Deep Reinforcement Learning, Xiuman Liang, Ziliang Liu, Zhendong Liu
Journal of System Simulation
Abstract: To address the low planning efficiency, poor safety, and limited practicability of the RRT algorithm in global path planning within complex three-dimensional environments, which fail to meet the requirements of planning the safe flight path of UAVs, an improved SAC-RRT algorithm was proposed, which fused SAC deep reinforcement learning algorithm and RRT algorithm. A target point bias strategy and a dynamic step size based on the SAC decision-making network were designed to reduce the blindness of RRT. A random point correction process was designed to optimize the position of random points based on actions from the decision network and …
Low-Energy Multi-Robot Path Planning Algorithm Under Hca* Framework, Ning Wang, Jianlin Mao, Dayan Li, Chengyuan Fang, Chengze Qian
Low-Energy Multi-Robot Path Planning Algorithm Under Hca* Framework, Ning Wang, Jianlin Mao, Dayan Li, Chengyuan Fang, Chengze Qian
Journal of System Simulation
Abstract: To address the energy optimization problem in multi-robot path planning, this paper proposed a multi-robot path planning algorithm based on the energy-guided hierarchical cooperative A* (E-HCA*) algorithm. To address the issue of robot oscillations caused by mutual avoidance at bottlenecks and narrow passages in multi-robot systems, a node expansion method with path length as a secondary feature was introduced, and a greedy suppression strategy under the cooperative A* framework was proposed. A differential-drive robot energy consumption model was established, and an energy-guided heuristic function was constructed by integrating energy metrics into the underlying A* algorithm to guide low-energy path …
Multi-Objective Optimization Of Signal Timing At Intersections Considering Tailpipe Emissions, Xinhuan Ding, Huaqing Wang, Xu Dang
Multi-Objective Optimization Of Signal Timing At Intersections Considering Tailpipe Emissions, Xinhuan Ding, Huaqing Wang, Xu Dang
Journal of System Simulation
Abstract: In order to alleviate urban road congestion and improve the traffic and environmental benefits at intersections, a multi-objective timing optimization model with total delay time, total number of stops, capacity, and total tailpipe emission at intersections as optimization objectives was developed. The model incorporated tailpipe emissions into a mathematical optimization model and quantified the mathematical relationship between traffic efficiency indicators and tailpipe emissions by constructing a specific power-based algorithm for measuring total tailpipe emissions. According to the intersection delay time and the number of stops, the total tailpipe emissions could be estimated. Both the NDX crossover operator and the …
Multisource Information Fusion Method For Human Gait Perception, Guiliang Chen, Guowei Liu, Yongchao Li, Chao Cai, Zihao Li, Dong Yang
Multisource Information Fusion Method For Human Gait Perception, Guiliang Chen, Guowei Liu, Yongchao Li, Chao Cai, Zihao Li, Dong Yang
Journal of System Simulation
Abstract: In response to the insufficient gait perception capability during lower limb exoskeleton assistance, a human lower limb gait phase optimization classification model was proposed. A wireless transmission gait information collection system was designed for collecting the required gait phase feature information. Human joint angles were accurately calculated by fusing acceleration and angular velocity information using extended Kalman filtering. Additionally, kernel principal component analysis was applied to reduce dimensionality in conjunction with plantar pressure data. The LSSVM algorithm was employed to classify gait data, and the PSO algorithm was utilized to find the optimal classification parameters. Experimental results demonstrate that …
Optimal Scheduling Of Integrated Energy Systems Considering Source-Load Uncertainty And Linear Carbon Trading, Huaping Zhong, Yubo Fan, Jijun Shui, Danhao Wang, Daogang Peng
Optimal Scheduling Of Integrated Energy Systems Considering Source-Load Uncertainty And Linear Carbon Trading, Huaping Zhong, Yubo Fan, Jijun Shui, Danhao Wang, Daogang Peng
Journal of System Simulation
Abstract: In order to overcome the impact of source-load uncertainty on the scheduling of integrated energy systems (IES) and reflect the flexibility of the carbon trading price with the change in trading volume, an optimal scheduling method for integrated energy systems considering source-load uncertainty and linear carbon trading was proposed. The equipment within the IES was modeled, and nonparametric kernel density estimation was used to obtain the probability density function for each time period, generating the set of scenes through Monte Carlo simulation and calculating the probability of each scene. For the time shift of wind and solar output peaks …
Simulation Of Three-Degree-Of-Freedom Internal Mode Sliding Mode Control For Non-Ideal Single-Inductor Dual-Output Boost Converter, Bingli Liu, Jiarong Wu, Lin Yang, Dinglin Yan
Simulation Of Three-Degree-Of-Freedom Internal Mode Sliding Mode Control For Non-Ideal Single-Inductor Dual-Output Boost Converter, Bingli Liu, Jiarong Wu, Lin Yang, Dinglin Yan
Journal of System Simulation
Abstract: To reduce the cross-interference in the single-inductor dual-output (SIDO) Boost converter and to enhance the output accuracy and stability of the system, the parasitic resistances of the circuit components were considered, and a three-degree-of-freedom internal model sliding mode control strategy was proposed for the non-ideal SIDO Boost converter. An affine nonlinear mathematical model of the non-ideal SIDO Boost converter was established, and the nonlinear system was linearized and decoupled into two linear subsystems based on the differential geometry theory. The linear subsystem was designed as a three-degree-of-freedom internal model controller and a sliding mode controller, respectively. The robustness …
An Improved Virtual Terrain Generation Method Based On Simplex Noise, Bo Shen, Jianqin Zhang, Shuaibao Ma, Zheng Wen
An Improved Virtual Terrain Generation Method Based On Simplex Noise, Bo Shen, Jianqin Zhang, Shuaibao Ma, Zheng Wen
Journal of System Simulation
Abstract: To address the issues of high computational complexity, slow generation speed, and insufficient realism present in traditional virtual terrain generation methods, this study proposed an improved virtual terrain generation method based on Simplex noise. This method leveraged the advantages of Simplex noise, such as high computational efficiency, low hardware overhead, and more natural randomness, to construct a basic terrain template. A fractal algorithm was introduced to enhance the level of terrain details through the superposition of noises with multiple frequencies and amplitudes. With the integration of a turbulence algorithm, random perturbations and complexity were added to further improve the …
Research On Constrained Programming Of Manipulator Using Rrt* Algorithm And Ellipse Prior, Zhen Yang, Li Su, Zhiyu Cheng
Research On Constrained Programming Of Manipulator Using Rrt* Algorithm And Ellipse Prior, Zhen Yang, Li Su, Zhiyu Cheng
Journal of System Simulation
Abstract: There are problems in the traditional RRT* algorithm using a uniform sampling strategy applied in constrained programming problems, such as inaccurate turning guidance of sampling points and unnecessary node cost comparisons, which lead to an increase in additional time costs. To address these issues, an improved RRT* algorithm was proposed. This algorithm leveraged a heuristic function cost of the projected sampling points to make an ellipse prior judgment on the sampling points. Based on the ellipse prior, the sampling points were judged to determine whether they could optimize the path and shorten the programming time. The geodesics were used …
Robust Identification Of Dual-Rate Sampled Nonlinear Systems Based On Salr Network, Wenbin Jiang, Yuqing Cao, Li Xie, Huizhong Yang
Robust Identification Of Dual-Rate Sampled Nonlinear Systems Based On Salr Network, Wenbin Jiang, Yuqing Cao, Li Xie, Huizhong Yang
Journal of System Simulation
Abstract: A robust identification algorithm based on the self-join adjacent-feedback loop reservoir (SALR) network was proposed for dual-rate sampled nonlinear systems with complex nonlinear characteristics and measurement outputs containing outliers. The SALR network was applied to describe the nonlinear characteristics of the target system, and wavelet neurons were injected into the reservoir to enhance its memory and nonlinear description capabilities. The identification problem of the nonlinear system was transformed into the identification problem of the network's output weight matrix. The Huber loss function was used to construct the criterion function, and an error threshold was introduced to improve the robustness …
Optimization Dispatch Method For High-Proportion Renewable Energy Power Systems Based On Sc-Ppo, Zhongkai Xu, Chenyang Chu, Kai Xie, Ruizhuo Zhao, Wenjun Ke
Optimization Dispatch Method For High-Proportion Renewable Energy Power Systems Based On Sc-Ppo, Zhongkai Xu, Chenyang Chu, Kai Xie, Ruizhuo Zhao, Wenjun Ke
Journal of System Simulation
Abstract: The high proportion of renewable energy integration brings significant challenges of randomness, multi-objective coupling, and security constraints to power systems. Traditional model-driven methods have limitations in modeling accuracy and adaptability. To address these issues, this paper proposed a safety-constrained PPO algorithm (SC-PPO). The method included three improvements. A temporal convolutional network was utilized to construct a dynamic state encoder that integrated historical operation, real-time monitoring, and prediction data to form a causal state representation. A hierarchical reward structure was designed, and an adaptive weighting mechanism based on constraint satisfaction degree was introduced to coordinate multi-objective optimization. Physical constraint projection …
Microsimulation Of Infectious Disease Transmission Considering Virus Release, Transmission, And Action, Zhiming Fang, Shengdong Yuan, Ge Huang, Jingqian Yang, Zhongyi Huang
Microsimulation Of Infectious Disease Transmission Considering Virus Release, Transmission, And Action, Zhiming Fang, Shengdong Yuan, Ge Huang, Jingqian Yang, Zhongyi Huang
Journal of System Simulation
Abstract: Existing infection risk assessment methods mostly evaluate infection probability through mathematical models or simulation, but they lack analysis of the relationship between air circulation and individual infection probability. This study proposed a risk prediction model for infectious disease transmission based on indoor air circulation. At the microscopic scale, the space was discretized into grid points. By integrating CFD numerical simulation, the entire process of virus droplet release, transmission, and action was fully simulated. The simulation results show that in an obstacle-free room, the error between the total indoor viral load predicted by the model under windless and low wind …
Modeling And Simulation Of Traffic Signal Control Based On Mlp With Improved Gcn-Td3, Deqi Huang, Yating Tu, Zhenhua Zhang, Xin Guo
Modeling And Simulation Of Traffic Signal Control Based On Mlp With Improved Gcn-Td3, Deqi Huang, Yating Tu, Zhenhua Zhang, Xin Guo
Journal of System Simulation
Abstract: To address the issues of uneven traffic flow at urban intersections, limited road capacity, and the poor coordination of existing traffic signal control algorithms, a traffic signal control algorithm based on graph convolutional reinforcement learning was proposed. By utilizing a multilayer perceptron, the dynamic features of vehicles and phase information at the controlled intersection and its neighboring intersections were extracted. A graph convolutional neural network was then employed to aggregate these vehicle dynamic features into potential features representing regional traffic. The control strategy was derived through multiple iterations of an improved twin delayed deep deterministic policy gradient (TD3) algorithm. …
Dynamic Order Scheduling For Pick-And-Pass System Considering Workload Balance And Learning Effects, Weihong Liu, Sixiang Zhao, Dali Zhang, Zhenhui Jiang
Dynamic Order Scheduling For Pick-And-Pass System Considering Workload Balance And Learning Effects, Weihong Liu, Sixiang Zhao, Dali Zhang, Zhenhui Jiang
Journal of System Simulation
Abstract: In e-commerce logistics, the hybrid pick-and-pass systems offer both complexity and flexibility, enabling adaptation to a wider range of order picking scenarios. Therefore, they have been widely used. However, this also complicates the order scheduling problem, particularly when both workload balance and pickers' learning effects need to be considered. Efficiently scheduling orders to reduce picking time under these conditions poses a significant challenge. This study began by constructing a mathematical model for the static scheduling problem with known orders. Based on this model, a simulation model of hybrid pick-and-pass zones was developed, and a scheduling rule incorporating multiple system …