Open Access. Powered by Scholars. Published by Universities.®

Artificial Intelligence and Robotics Commons™

Open Access. Powered by Scholars. Published by Universities.®

Engineering

Institution
Keyword
Publication Year
Publication
Publication Type
File Type

Articles 1651 - 1680 of 5401

Full-Text Articles in Artificial Intelligence and Robotics

Scheduling, Complexity, And Solution Methods For Space Robot On-Orbit Servicing, Susan E. Sorenson Aug 2022

Scheduling, Complexity, And Solution Methods For Space Robot On-Orbit Servicing, Susan E. Sorenson

Graduate Theses and Dissertations

This research proposes problems, models, and solutions for the scheduling of space robot on-orbit servicing. We present the Multi-Orbit Routing and Scheduling of Refuellable On-Orbit Servicing Space Robots problem which considers on-orbit servicing across multiple orbits with moving tasks and moving refuelling depots. We formulate a mixed integer linear program model to optimize the routing and scheduling of robot servicers to accomplish on-orbit servicing tasks. We develop and demonstrate flexible algorithms for the creation of the model parameters and associated data sets. Our first algorithm creates the network arcs using orbital mechanics. We have also created a novel way to …

Go to article

Deep Learning Applications In Industrial And Systems Engineering, Winthrop Harvey Aug 2022

Deep Learning Applications In Industrial And Systems Engineering, Winthrop Harvey

Graduate Theses and Dissertations

Deep learning - the use of large neural networks to perform machine learning - has transformed the world. As the capabilities of deep models continue to grow, deep learning is becoming an increasingly valuable and practical tool for industrial engineering. With its wide applicability, deep learning can be turned to many industrial engineering tasks, including optimization, heuristic search, and functional approximation. In this dissertation, the major concepts and paradigms of deep learning are reviewed, and three industrial engineering projects applying these methods are described. The first applies a deep convolutional network to the task of absolute aerial geolocalization - the …

Go to article

Applied Deep Learning: Case Studies In Computer Vision And Natural Language Processing, Md Reshad Ul Hoque Aug 2022

Applied Deep Learning: Case Studies In Computer Vision And Natural Language Processing, Md Reshad Ul Hoque

Electrical & Computer Engineering Theses & Dissertations

Deep learning has proved to be successful for many computer vision and natural language processing applications. In this dissertation, three studies have been conducted to show the efficacy of deep learning models for computer vision and natural language processing. In the first study, an efficient deep learning model was proposed for seagrass scar detection in multispectral images which produced robust, accurate scars mappings. In the second study, an arithmetic deep learning model was developed to fuse multi-spectral images collected at different times with different resolutions to generate high-resolution images for downstream tasks including change detection, object detection, and land cover …

Go to article

Evaluation Of Generative Models For Predicting Microstructure Geometries In Laser Powder Bed Fusion Additive Manufacturing, Andy Ramlatchan Aug 2022

Evaluation Of Generative Models For Predicting Microstructure Geometries In Laser Powder Bed Fusion Additive Manufacturing, Andy Ramlatchan

Computer Science Theses & Dissertations

In-situ process monitoring for metals additive manufacturing is paramount to the successful build of an object for application in extreme or high stress environments. In selective laser melting additive manufacturing, the process by which a laser melts metal powder during the build will dictate the internal microstructure of that object once the metal cools and solidifies. The difficulty lies in that obtaining enough variety of data to quantify the internal microstructures for the evaluation of its physical properties is problematic, as the laser passes at high speeds over powder grains at a micrometer scale. Imaging the process in-situ is complex …

Go to article

Emotion Detection Using An Ensemble Model Trained With Physiological Signals And Inferred Arousal-Valence States, Matthew Nathanael Gray Aug 2022

Emotion Detection Using An Ensemble Model Trained With Physiological Signals And Inferred Arousal-Valence States, Matthew Nathanael Gray

Electrical & Computer Engineering Theses & Dissertations

Affective computing is an exciting and transformative field that is gaining in popularity among psychologists, statisticians, and computer scientists. The ability of a machine to infer human emotion and mood, i.e. affective states, has the potential to greatly improve human-machine interaction in our increasingly digital world. In this work, an ensemble model methodology for detecting human emotions across multiple subjects is outlined. The Continuously Annotated Signals of Emotion (CASE) dataset, which is a dataset of physiological signals labeled with discrete emotions from video stimuli as well as subject-reported continuous emotions, arousal and valence, from the circumplex model, is used for …

Go to article

Adaptive Risk Network Dependency Analysis Of Complex Hierarchical Systems, Katherine L. Smith Aug 2022

Adaptive Risk Network Dependency Analysis Of Complex Hierarchical Systems, Katherine L. Smith

Computational Modeling & Simulation Engineering Theses & Dissertations

Recently the number, variety, and complexity of interconnected systems have been increasing while the resources available to increase resilience of those systems have been decreasing. Therefore, it has become increasingly important to quantify the effects of risks and the resulting disruptions over time as they ripple through networks of systems. This dissertation presents a novel modeling and simulation methodology which quantifies resilience, as impact on performance over time, and risk, as the impact of probabilistic disruptions. This work includes four major contributions over the state-of-the-art which are: (1) cyclic dependencies are captured by separation of performance variables into layers which …

Go to article

Computational Models To Detect Radiation In Urban Environments: An Application Of Signal Processing Techniques And Neural Networks To Radiation Data Analysis, Jose Nicolas Gachancipa Jul 2022

Computational Models To Detect Radiation In Urban Environments: An Application Of Signal Processing Techniques And Neural Networks To Radiation Data Analysis, Jose Nicolas Gachancipa

Beyond: Undergraduate Research Journal

Radioactive sources, such as uranium-235, are nuclides that emit ionizing radiation, and which can be used to build nuclear weapons. In public areas, the presence of a radioactive nuclide can present a risk to the population, and therefore, it is imperative that threats are identified by radiological search and response teams in a timely and effective manner. In urban environments, such as densely populated cities, radioactive sources may be more difficult to detect, since background radiation produced by surrounding objects and structures (e.g., buildings, cars) can hinder the effective detection of unnatural radioactive material. This article presents a computational model …

Go to article

A Modified Point Matching Method For Non-Rigid Image Registration, Jintai Shangguan, Yawen Dang, Wei Lian Jul 2022

A Modified Point Matching Method For Non-Rigid Image Registration, Jintai Shangguan, Yawen Dang, Wei Lian

Journal of System Simulation

Abstract: Aiming at the problem that the registration results tend to converge to local minima due to the complexity of the relative position changes between two point sets in the non-rigid body point matching process, a joint estimation method for non-rigid body point matching based on precenter alignment is proposed, a modified matching method for non-rigid image registration based on centre preregistration is proposed. To better achieve the point matching accuracy between two point sets, a centre preregistration step is applied before the iterative closest point matching algorithm, which converges to a solution more close to a global optimum and …

Go to article

Transfer Method Of Operational Simulation Experiment Scope Using Compromised Case-Based Reasoning, Jun Ma, Jingyu Yang, Xi Wu Jul 2022

Transfer Method Of Operational Simulation Experiment Scope Using Compromised Case-Based Reasoning, Jun Ma, Jingyu Yang, Xi Wu

Journal of System Simulation

Abstract: The scope of operational simulation experiment is usually determined by experts, which costs relatively high. In order to transfer the knowledge of experimental scope selection from historical data of operational simulation experiment to new operational experiment cases, the method of compromised case-based reasoning is proposed. According to the data characteristics of the case, the representation method of the operational simulation experiment case is proposed; according to the structure and attribute characteristics of the case, the hybrid similarity calculation method of subjective and objective comprehensive weighting is proposed; aiming at the problems of retrieval failure and less information content …

Go to article

Optimal Dispatch Of Integrated Energy System Considering Ladder-Type Carbon Trading, Liying Wang, Jialin Lin, Houqi Dong, Ming Zeng, Yuqing Wang Jul 2022

Optimal Dispatch Of Integrated Energy System Considering Ladder-Type Carbon Trading, Liying Wang, Jialin Lin, Houqi Dong, Ming Zeng, Yuqing Wang

Journal of System Simulation

Abstract: With the development of the electricity market and carbon market,the introduction of demand response and carbon trading mechanisms into the operation and dispatch of integrated energy systems will help guide users and system operators to optimize electricity consumption and dispatch plans.The comprehensive incentive measures such as time-of-use electricity prices and demand response incentive subsidies are used to guide users to participate in demand response.A two-layer stochastic optimal scheduling model for a comprehensive energy system considering the ladder-type carbon trading mechanism and demand response is constructed based on IGDT (information gap decision theory) theory.The two-layer model is converted …

Go to article

Bi-Level Optimization Of Distribution Network For Hybrid Energy Storage System Of Storage Battery And Hydrogen Storage, Feibo Feng, Xingde Yan, Baoqiang Zheng, Xiaofeng Yin, Mengzhen Zhou, Xin Jiang Jul 2022

Bi-Level Optimization Of Distribution Network For Hybrid Energy Storage System Of Storage Battery And Hydrogen Storage, Feibo Feng, Xingde Yan, Baoqiang Zheng, Xiaofeng Yin, Mengzhen Zhou, Xin Jiang

Journal of System Simulation

Abstract: Under the background of carbon neutralization and emission peaking goals and the utilization of clean hydrogen energy, aiming at the demand of distribution network configuring electrochemical energy storage and hydrogen energy storage system to form a hybrid energy storage system to improve power quality, a bi-level optimization model of the hybrid energy storage system is established. The upper level location and capacity model comprehensively considers the investment cost, network loss cost and voltage offset, while the lower level optimization operation model considers the operation cost of hybrid energy storage system, and the voltage stability index is introduced for evaluation. …

Go to article

Modeling And Simulation Of Optimal Strategy For Electric Vehicles Participating In Power Grid Frequency Regulation, Li Yao, Junjie Hu, Wenshuai Ma, Zhile Yang Jul 2022

Modeling And Simulation Of Optimal Strategy For Electric Vehicles Participating In Power Grid Frequency Regulation, Li Yao, Junjie Hu, Wenshuai Ma, Zhile Yang

Journal of System Simulation

Abstract: Electric vehicles (EVs) have similar characteristics of distributed energy storage, and making full use of the flexibility of EVs can provide ancillary services to the grid and gain benefits. Considering the influence of uncertain factors, a bidding model for electric vehicle aggregator (EVA) to participate in the day-ahead energy market and frequency regulation ancillary service market is constructed with the maximum revenue expectation of EVA as the target. A real-time energy distribution incentive strategy based on contract theory is proposed to realize the distribution of EVA's frequency regulation demand under the condition of maximizing social welfare. Through case studies, …

Go to article

Simulation Model Of Forest Fire Spread Based On Swarm Intelligence, Aibin Chen, Fubo Ding, Guoxiong Zhou, Bo Zhou Jul 2022

Simulation Model Of Forest Fire Spread Based On Swarm Intelligence, Aibin Chen, Fubo Ding, Guoxiong Zhou, Bo Zhou

Journal of System Simulation

Abstract: Aiming at the shortcomings of high computational complexity and low simulation accuracy of traditional forest fire spread model, a forest fire spread simulation model based on swarm intelligence is proposed.By establishing fuel factor matrix and landform factor matrix, and combining with the real-time meteorological information, the computational complexity is reduced; the spread behavior of the forest fire is abstracted as the cluster behavior of each module fire point, and the correlation between modules is considered to improve the accuracy of forest fire spread simulation model.The model is compared with Wang Zhengfei model and two-dimensional cellular automata model. …

Go to article

Two Stage Optimization Algorithm To Solve The Green Packing Vehicle Routing Problem, Rong Hu, Wen Jiang, Bin Qian, Naikang Yu Jul 2022

Two Stage Optimization Algorithm To Solve The Green Packing Vehicle Routing Problem, Rong Hu, Wen Jiang, Bin Qian, Naikang Yu

Journal of System Simulation

Abstract: The green open vehicle routing problem with two-dimensional loading constraints (2L-GOVRP) is integration of the green open vehicle routing problem and two-dimensional bin packing problem. The model of 2L-GOVRP is established and a two-stage optimization algorithm (TSOA) is proposed to minimize fuel consumption. In the first stage of TSOA, adaptive whale optimization algorithm (AWOA) is designed to solve the vehicle routing problem, which determine the initial delivery route of the vehicle (the initial solution of 2L-GOVRP). The algorithm has four kinds of variable neighborhoods local operation to perform a local search. In the second stage of TSOA, the skyline …

Go to article

A Method Of Loose Coupling Entity Modeling Based On Variable Rules, Zheng Yang, Zhimin Xiang, Shiwen Ma Jul 2022

A Method Of Loose Coupling Entity Modeling Based On Variable Rules, Zheng Yang, Zhimin Xiang, Shiwen Ma

Journal of System Simulation

Abstract: Operational Entity Modeling is a hot research topic in the field of combat simulation. A loose coupling entity modeling method based on variable rules is proposed. The architecture of operational entity model based on variable rules and the internal and external interaction mechanism of the model are presented in terms of entity, mission, action, interaction, event and rule. On this basis, the running framework of operational entity model is designed, and the entity model uniform scheduling mechanism is standardized, which solves the problems of over-tight coupling of operational rules in the operational entity model and low reliability of the …

Go to article

Research On Prediction Of Model Based On Multi-Scale Lstm, Junjie Qiu, Hong Zheng, Yunhui Cheng Jul 2022

Research On Prediction Of Model Based On Multi-Scale Lstm, Junjie Qiu, Hong Zheng, Yunhui Cheng

Journal of System Simulation

Abstract: Aircraft engine remaining useful life (RUL) prediction is the core issue in equipmentfailure prognostics and health management (PHM). Aiming at the characteristics of high dimensionality, high lag and complexity of engine data, a multi-scale attention-based bidirectional long short-term memory neural network model based on self-training weights is proposed. Multi-scale features are extracted through bidirectional long short-term memory neural network (BiLSTM) of different scales. A fusion algorithm based on self-training weights is proposed, and an attention mechanism is introduced to screen features at different scales to improve prediction accuracy. Various models are compared on the NASA's C-MAPSS data set. The …

Go to article

Space Science Satellite Data Processing Framework Research And System Implementation, Wenzhen Ma, Ziming Zou, Jianhui Li, Qinsi Yu, Jizhou Tong, Jingjing Li Jul 2022

Space Science Satellite Data Processing Framework Research And System Implementation, Wenzhen Ma, Ziming Zou, Jianhui Li, Qinsi Yu, Jizhou Tong, Jingjing Li

Journal of System Simulation

Abstract: Based on the needs of China's space science strategy and series of on-orbit and forthcoming satellite missions in China's Strategic Priority Program on space science, data processing framework and key technologies of the satellite ground segment are studied. A general technical framework SDPF (space science satellite data processing framework) is proposed with two-layer scheduling engine, including mission-level and resource-level. The design and implementation of an automatic, efficient, real-time and standard space science satellite data processing system has been established. In this way, complicated processing procedures on large-scale data from multi-satellite missions and multi-payload can be completed quickly in parallel. …

Go to article

Ultra-Real-Time Visual Simulation System For Multi-View Rendering Tasks, Xunyun Liu, Xinhai Xu, Chengzhang Zhu, Hao Li, Lei Zeng Jul 2022

Ultra-Real-Time Visual Simulation System For Multi-View Rendering Tasks, Xunyun Liu, Xinhai Xu, Chengzhang Zhu, Hao Li, Lei Zeng

Journal of System Simulation

Abstract: For multi-view rendering tasks, a theoretical analysis of ultra-real-time visual simulation is given in terms of implementation principle and feasibility. Based on the theoretical results, an ultra-real-time visual simulation architecture is designed, which decouples the simulation and rendering computation. A parallel-rendering-based ultra-real-time visual simulation method is proposed to solve the problems of rendering task assignment, simulation world synchronization, and rendering-execution time selection. An ultra-real-time visual simulation system is implemented based on Unreal Engine 4 (UE4), the performance of which is demonstrated on a designated application case per rendering efficiency and ultra-real-time simulation.

Go to article

Verification Of Transaction Ordering Dependence Vulnerability Of Smart Contract Based On Cpn, Hong Zheng, Zerun Liu, Jianhua Huang, Shihui Qian Jul 2022

Verification Of Transaction Ordering Dependence Vulnerability Of Smart Contract Based On Cpn, Hong Zheng, Zerun Liu, Jianhua Huang, Shihui Qian

Journal of System Simulation

Abstract: The formal verification of smart contracts researches mainly focus on programming language-level vulnerabilities, and the transaction ordering dependence is more difficult to be detected as a blockchain-level vulnerability.The latent transaction ordering dependence vulnerability in smart contracts is formally verified based on colored Petri nets.The latent vulnerability in the Decode reward contractis analyzed, anda colored Petri net model of the contract itself and its execution environment is established from top to bottom.The attacker model is introduced to consider the situation that the contract is attacked. By running the model to verify the existence of transaction ordering dependence vulnerability in …

Go to article

Modeling And Simulation Of Sofc System With Heat Transfer Among Bop Components, Ling Hong, Rongmin Wu, Jianwu Zhou, Tian Xia, Xiaojie Li, Pengjie Tian, Hao Peng, Chunhui Shou Jul 2022

Modeling And Simulation Of Sofc System With Heat Transfer Among Bop Components, Ling Hong, Rongmin Wu, Jianwu Zhou, Tian Xia, Xiaojie Li, Pengjie Tian, Hao Peng, Chunhui Shou

Journal of System Simulation

Abstract: High temperature solid oxide fuel cell (SOFC) is a high temperature and efficient hydrogen-electric conversion device. Its high temperature operating environment puts forward higher requirements for thermal insulation of stack and balance of plants(BoP) in the system. In this paper, a lumped SOFC system model is established based on the thermal efficiency-heat transfer unit number method (ε-NTU method), in combination with limited measurable parameters for high-temperature system.Quantitative analysis of components temperature and heat transfer among components can be achieved by heat exchange simulation between components and BoP hot-box environment. A simple feedback controlleris designed for system self-starting and operation. …

Go to article

Research On Multi-Robot Slam Map Fusionmethod Based On Heuristics, Tong Wang, Guangtao Shang, Shan Gao Jul 2022

Research On Multi-Robot Slam Map Fusionmethod Based On Heuristics, Tong Wang, Guangtao Shang, Shan Gao

Journal of System Simulation

Abstract: Simultaneous Localization and Mapping (SLAM) is a key technology for mobile robots to complete map construction and positioning tasks in an unknown environment. Aiming at the map fusion problem in multi-robot SLAM, a heuristic search method is proposed to guide the repeated regions of the local map for map fusion. Each robot can build a local map without knowing its relative position, and send the local map information to the same workstation, and use the similarity of the local map as the judgment index to fuse to obtain the optimal global map.Verified on the robot physical platform, the …

Go to article

Aerial Target Threat Assessment Method Based On Deep Learning, Huimin Chai, Yong Zhang, Xinyue Li, Yanan Song Jul 2022

Aerial Target Threat Assessment Method Based On Deep Learning, Huimin Chai, Yong Zhang, Xinyue Li, Yanan Song

Journal of System Simulation

Abstract: Due to many factors of aerial target threat assessment and the lack of self-learning ability of current assessment methods, a deep neural network model for aerial target threat assessment is established using deep learning theory. In order to improve the fitting effect of the model training, a symmetric pre-training method is given. The hidden layers of the model are pre-trained layer by layer, and finally the whole model is trained. Sample data and air to air simulation scene experiments are carried out respectively. The experiments results show that the accuracy of the model using the symmetric pre-training method is …

Go to article

Game-Based Resource Allocation And Task Offloading Scheme In Collaborative Cloud-Edge Computing System, Xuewen Wu, Jingxian Liao Jul 2022

Game-Based Resource Allocation And Task Offloading Scheme In Collaborative Cloud-Edge Computing System, Xuewen Wu, Jingxian Liao

Journal of System Simulation

Abstract: Considering the delay, energy consumption and computing resource cost, the utility maximization problem in collaborative cloud-edge system is constructed, and divided into three subproblems: computing resource allocation, uplink power allocation and task offloading strategy. A game-based resource allocation and task offloading(GRATO) scheme is proposed to solve those subproblems. The optimal solution of computing resource allocation is obtained by using convex optimization conditions; a low complexity uplink power allocation method is designed to reduce wireless interfere; a game-based distributed task offloading algorithm (GDTOA) is proposed to optimize the task offloading strategy. Simulation results show that the performance of GRATO is …

Go to article

Research On Inpainting Algorithm Of Digital Murals Based On Enhanced Structural Information, Ziying Zhang, Hua Zhou Jul 2022

Research On Inpainting Algorithm Of Digital Murals Based On Enhanced Structural Information, Ziying Zhang, Hua Zhou

Journal of System Simulation

Abstract: According to the fact that the murals of Fahai Temple in Beijing are missing in blocks and the missing area is structure information, a structure-enhancing digital image restoration algorithm is proposed to solve the problem of insufficient consideration of image structure information in Criminisi algorithm. When calculating the priority function of the filling block, the curvature calculation of the linear convolution is integrated into the data item, and the weight of the structure information is increased to achieve the goal of repairing the structure information-rich region in priority; the regional covariance method is introduced in the similarity calculation of …

Go to article

Simulation Research On Covid-19 Transmission And Control Measures Based On SeiIRd Model, Jing Wang, Ying Dong Jul 2022

Simulation Research On Covid-19 Transmission And Control Measures Based On SeiIRd Model, Jing Wang, Ying Dong

Journal of System Simulation

Abstract: With the spread of the novel coronavirus pneumonia around the world, the data and transmission mechanism are analyzed. The SEIiRD model is constructed based on the existing SEIRD model, and the infected population is divided into asymptomatic infections, mild infections, severe infections and critical infections. The impact of the transmission rate of different infected people on the development of the epidemic was analyzed. Simulation experiments were carried out on the basis of fitting real data, and it was found that the main infected populations that affected the discovery of the epidemic were asymptomatic and mildly infected. On …

Go to article

Interactive Construction Of Scientific Workflow Based On Process Mining, Jun Liu, Yang Gao, Tao Xu, Qing Zhao, Guihua Shan, Xuebin Chi Jul 2022

Interactive Construction Of Scientific Workflow Based On Process Mining, Jun Liu, Yang Gao, Tao Xu, Qing Zhao, Guihua Shan, Xuebin Chi

Journal of System Simulation

Abstract: When dealing with large-scale or complex workflows, the construction efficiency of traditional interactive workflow construction methods is very low. To solve this problem, a workflow construction method based on process mining is proposed. Heuristic methods are used to collect process fragments. The specially designed relation description language is used to record the process description of different levels and aspects in the workflow as text. The text is translated to generate process relational data, which will be output to the process discovery algorithm to generate a sound workflow network. An interactive workflow construction software has been developed and tested in …

Go to article

A Quantization Training Algorithm Of Adaptive Learning Quantization Scale Fators, Hui Nie, Kangshun Li, Yang Su Jul 2022

A Quantization Training Algorithm Of Adaptive Learning Quantization Scale Fators, Hui Nie, Kangshun Li, Yang Su

Journal of System Simulation

Abstract: Deep neural network model is difficult to effectively deploy in embedded terminals due to its excessive number of components, andone of the solutions is model miniaturization (such as model quantization, knowledge distillation, etc.). To address this problem, a quantization training algorithm (referred to as LSQ-BN algorithm) based on adaptive learning of quantizationscale factors with BN folding is proposed.A single CNN (convolutional neural) is usedtoconstruct BN folding and achieve BN and CNN fusion. During the process of quantitative training,the quantization scale factors are set as model parameters. An adaptive quantizationscale factor initialization scheme is proposed to solve the problem …

Go to article

Joint Shift Scheduling Method For Call Center With Mechanism Of Delay Information, Miao Yu, Manru Li, Yu Zhao Jul 2022

Joint Shift Scheduling Method For Call Center With Mechanism Of Delay Information, Miao Yu, Manru Li, Yu Zhao

Journal of System Simulation

Abstract: A joint shift scheduling method is studied for call center with delay information. According to the queue model of call center with delay information, the influence rule of the customer's patience and abandonment behavior is addressed, and a mechanism of delay information is proposed to estimate the waiting time of customers. Considering the influence of non-stationary arrival and other factors, the scheduling model of the call centers is established by the discrete Event-Scheduling approach. Based on the proposed evaluation method of delay information, the joint shift scheduling method by simulation optimization is designed to solve the scheduling problem …

Go to article

Modeling And Simulation Of Ultra Supercritical Unit Using A Composite Weighted Human Learning Network, Chuanliang Cheng, Chen Peng, Deliang Zeng, Tengfei Zhang Jul 2022

Modeling And Simulation Of Ultra Supercritical Unit Using A Composite Weighted Human Learning Network, Chuanliang Cheng, Chen Peng, Deliang Zeng, Tengfei Zhang

Journal of System Simulation

Abstract: Intermediate point temperature is an important parameter in ultra supercritical (USC) unit. However, due to strong nonlinearity, it is difficult to determine the form and coefficients of the corresponding model by using traditional methods. In order to get a better control effect, a novel composite weighted human learning optimization network (CWHLON) is proposed to tackle the above-mentioned problems. Though the real-time dynamic linear model, the characteristics of the object are accurately simulated. In the simulation experiment, CWHLON is compared with the traditional recursive least squares and other three meta heuristic methods. The data show that the proposed method improves …

Go to article

Research On The Number Of Passengers On The Platform Of Rail Transit Station Considering Congestion Propagation, Wei Chen, Zongping Li, Can Liu, Yanni Ju Jul 2022

Research On The Number Of Passengers On The Platform Of Rail Transit Station Considering Congestion Propagation, Wei Chen, Zongping Li, Can Liu, Yanni Ju

Journal of System Simulation

Abstract: It is the basis of improving the safety guarantee ability of urban rail transit system to study and master the change law of the number of passengers in the urban rail transit station under the condition of Congestion Propagation. From the point of view of multi subsystem of passenger, station and train, combined with the multi-attribute characteristics of passenger flow, platform and train, the calculation model of the number of passengers in urban rail transit station is established based on system dynamics. A multi group sensitivity simulation experiment is designed to analyze the influence factors of the number of …

Go to article

First Prev Next Last