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2019

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Articles 511 - 540 of 13032

Full-Text Articles in Physical Sciences and Mathematics

System Dynamics Modeling For Simulation Of Water Supply And Demand Relationship In Beijing, Longxi Luo, Jianping Wu, Chen Yun, Zhe Xu Dec 2019

System Dynamics Modeling For Simulation Of Water Supply And Demand Relationship In Beijing, Longxi Luo, Jianping Wu, Chen Yun, Zhe Xu

Journal of System Simulation

Abstract: Beijing is a metropolis and the center of politics and education of China. However, located in the region with a low level of rainfall, Beijing has been struggling with supplying water resources to meet its growing demand. The past and future trend of the water supply and demand balance in Beijing is studied. Historical data is collected and compiled for learning its past behaviors. The system dynamics (SD) modeling can simulate the complicated and integrated relationships in water supply and demand system. An SD model is then constructed based on compiled historical data. The SD model is validated by …

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Research On The Value Accessing Method For Calibrating Micro Traffic Simulation Model Parameters, Chenjing Zhou, Rong Jian, Kwok Lam Dec 2019

Research On The Value Accessing Method For Calibrating Micro Traffic Simulation Model Parameters, Chenjing Zhou, Rong Jian, Kwok Lam

Journal of System Simulation

Abstract: Parameter calibration is the precondition of the application of micro traffic simulation technology. This study focuses on the value accessing method for parameter calibration in order to further improve the parameter calibration process. The analysis of the distribution characteristics of each parameter calibration results shows that the parameters have different trends in the process of gradual iteration, and there are multiple optimal solutions for the model parameter calibration results. In this paper, the dispersion is used as the quantitative analysis index of the concentration degree of each parameter calibration result, and the parameter value of the model is determined …

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Spatiotemporal Mode Analysis Of Urban Dockless Shared Bikes Based On Point Of Interests Clustering, Zhang Fang, Bin Chen, Yanghua Tang, Dong Jian, Chuan Ai, Xiaogang Qiu Dec 2019

Spatiotemporal Mode Analysis Of Urban Dockless Shared Bikes Based On Point Of Interests Clustering, Zhang Fang, Bin Chen, Yanghua Tang, Dong Jian, Chuan Ai, Xiaogang Qiu

Journal of System Simulation

Abstract: The city’s dockless shared bikes have developed rapidly, and its features of convenience, economy and efficiency have been widely welcomed. The digital footprint they generate reveals the movement of people in time and space within the city, which makes it possible to quantify the activities of people in the city using shared bikes. In this paper, based on the collected shared bikes data of Beijing, a clustering method based on the point of interests is proposed to divide the urban space, so as to construct a mobile network of urban shared bikes, and analysis the spatiotemporal mode of bike …

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An Lstm-Based Motion Recognition Method For Power Operation And Maintenance, Peizhen Liu, Yuxiang Jia, Shihong Xia Dec 2019

An Lstm-Based Motion Recognition Method For Power Operation And Maintenance, Peizhen Liu, Yuxiang Jia, Shihong Xia

Journal of System Simulation

Abstract: The security of power operation and maintenance has always been a subject of great social concern. In order to avoid serious consequences caused by the fault of staffs, a motion recognition method for power operation and maintenance jobs based on LSTM (Long Short-Term Memory) is proposed, which covers the whole process from data collection, data processing to motion classification and recognition, then it can recognise and supervise the behavior of staffs who are at work. In addition, a simulation experiment is conducted between the deep learning algorithm LSTM and the traditional machine learning algorithm KNN based on the newly …

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Design Of Feedback Linearization Nonlinear Controller For Asynchronous Motor Power Consumption Efficiency, Li Rui, Yingnian Wu Dec 2019

Design Of Feedback Linearization Nonlinear Controller For Asynchronous Motor Power Consumption Efficiency, Li Rui, Yingnian Wu

Journal of System Simulation

Abstract: In order to realize precise feedback linearization and optimal control of motor power consumption for MIMO nonlinear affine system, we build the model of induction motor within which dynamic power loss factor is included. Based on the differential geometry theory, a nonlinear optimization model of the controller is designed for this model to control the asynchronous motor outputs accurately and enhance the power efficiency. This paper presents an optimal control law for multiple inputs multiple outputs affine nonlinear system and the detailed design steps are given combined with examples for multiple outputs tracking problem. The simulation results show that …

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Numerical Simulation Analysis Of Anti-Blast Impact Of Underground Rescue Capsule Based On Ls-Dyna, Zhang Fan, Yuanhua Yang, Xiaoxu He, Deng Yu Dec 2019

Numerical Simulation Analysis Of Anti-Blast Impact Of Underground Rescue Capsule Based On Ls-Dyna, Zhang Fan, Yuanhua Yang, Xiaoxu He, Deng Yu

Journal of System Simulation

Abstract: Aiming at the strength problem of the underground rescue cabin under explosion impact load, a finite element model of overall explosion impact load and fluid-solid coupling structure response is established in transient dynamic soft LS-DYNA. The flow field impact load is generated by explosion algorithm, and the propagation of the impact load in the air is calculated. The dynamic response of the rescue cabin structure under the impact load is calculated by the fluid-solid coupling method. The results show that the maximum load occurs on the end surface closest to the explosion source, and the structural deformation is small …

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The Scheduling Algorithm Of Cloud Job Based On Hopfield Neural Network, Yudong Guo, Jinping Zuo Dec 2019

The Scheduling Algorithm Of Cloud Job Based On Hopfield Neural Network, Yudong Guo, Jinping Zuo

Journal of System Simulation

Abstract: Focusing on the low efficiency of cloud job scheduling and the insufficient utility of resource, a job scheduling algorithm based on Hopfield Neural Network is proposed. In order to improve the resource scheduling ability of the system, The resource characteristics which influence the cloud job scheduling are shown. The mathematical model of resource constraints is established, and the Hopfield energy function is designed and optimized. The average utilization rate of 9 nodes is analyzed by using the standard test cases, and the performance and resource utilization of the proposed strategy are compared with three typical algorithms. …

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Simulation Research On Attitude Solution Method Of Micro-Mini Missile, Chunbo Zhao, Junfang Fan, Liu Ning Dec 2019

Simulation Research On Attitude Solution Method Of Micro-Mini Missile, Chunbo Zhao, Junfang Fan, Liu Ning

Journal of System Simulation

Abstract: Aiming at the problem of attitude measurement error in the inertial navigation system of micro and small guided ammunition under eccentric structure, the attitude solution and error compensation optimization are studied by using rotation vector optimization of multiple sub-samples, such as monotone sample, two sub-samples, three sub-samples and four sub-samples, and the fourth-order runge kutta algorithm. Through error compensation and optimization of measured data, the results show that the monomorphic modified algorithm has the worst optimization effect, the fourth-order runge kutta optimization algorithm has the best effect, and the maximum drift error of attitude Angle is better than 10 …

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A Method Of Manifold Learning For Locality Preserving Projections Based On Geodesic, Lijun Xu, Jinghan Fang, Yiping Wang Dec 2019

A Method Of Manifold Learning For Locality Preserving Projections Based On Geodesic, Lijun Xu, Jinghan Fang, Yiping Wang

Journal of System Simulation

Abstract: In order to solve the problem of under-fitting state of LPP algorithm in practical application,in this paper, the mapping principle of Locality Preserving Projections (LPP) is discussed in detail. The relationship of LPP method between the under-fitting state on certain dataset and adjacency graph is analyzed. The LPP manifold learning method (ISOLPP) is proposed on the basis of geodesic. The experiment results show that the good embedded effect is achieved by implenmenting ISOLPP method on multiple test data sets. It significantly improves the adaptability of the algorithm by not only inheriting the advantages of LPP algorithm with explicit projection …

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Research On Intelligent Clustering Algorithm For Complex Water Wireless Network Surveillance, Hua Xiang, Hongtao Liang, Zhaoxin Dong, Wang Zhao, Hongjuan Yao, Baohua Li, Bingqing Jiang Dec 2019

Research On Intelligent Clustering Algorithm For Complex Water Wireless Network Surveillance, Hua Xiang, Hongtao Liang, Zhaoxin Dong, Wang Zhao, Hongjuan Yao, Baohua Li, Bingqing Jiang

Journal of System Simulation

Abstract: The clustering of irregular networks will cause load imbalance, which results in the phenomenon of “energy hot zone”. Aiming at the unreasonable topology of irregular network clustering, an intelligent clustering algorithm based on genetic strategy is proposed for the wireless network surveillance of complex water system. An irregular complex water topology model and an energy consumption model are built, and a genetic clustering strategy is designed via the principle of minimum energy consumption. The P matrix coding method is given, which avoids the squared increment of data calculation. Simultaneously, an adaptive genetic operator and a fuzzy modified operator are …

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Moving Object Detection Based On Deep Convolutional Neural Network, Yuqiu Lu, Jinyu Sun, Shiwei Ma Dec 2019

Moving Object Detection Based On Deep Convolutional Neural Network, Yuqiu Lu, Jinyu Sun, Shiwei Ma

Journal of System Simulation

Abstract: A deep convolution neural network MONet is designed for the intermittent motion problem in moving objects detection. In the absence of training data sets, a synthetic dataset GoChairs is generated by affine transformation, and on this basis the network training and testing are performed. The results show that the trained MONet can effectively detect the moving objects based on the correspondence between the pixels. The traditional datasets CDnet and I2R are also tested to verify the generalization performance of the network. In addition, MONet is compared qualitatively and quantitatively with classical methods for the intermittent motion problem of …

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3d Shape Deformation Simulation Algorithm Based On Haptics, Binbin Qi, Xuefang Zhu, Lipeng Fan Dec 2019

3d Shape Deformation Simulation Algorithm Based On Haptics, Binbin Qi, Xuefang Zhu, Lipeng Fan

Journal of System Simulation

Abstract: Shape deformation is widely used in virtual reality, system simulation, computer animation and other graphics applications. Few people pay attention to introducing haptic interaction into 3D model deformation. We provide a haptic interactive framework by introducing haptic interaction into shape editing field. Based on the above haptic interactive framework, we propose a 3D model deformation simulation algorithm based on haptics. In order to realize the shape deformation, this algorithm needs to involve three parts: grid hierarchical structure, local mass-spring model and the dynamic shape deformation. Experimental results show that this algorithm has good stability and strong robustness, and the …

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Fault Prediction Of Satellite Attitude Control System Based On Neural Network, Xiaofan Meng, Song Hua Dec 2019

Fault Prediction Of Satellite Attitude Control System Based On Neural Network, Xiaofan Meng, Song Hua

Journal of System Simulation

Abstract: A new method based on BP neural network(BPNN), wavelet neural network(WNN) and wavelet decomposition-LSTM(wLSTM) network is proposed for predicting faults in the satellite attitude control system. Normal satellite attitude data is used to train BPNN which is used as the standard model of satellite attitude control system. The real-time attitude residuals is obtained by subtracting the BPNN output attitude angle from the real-time data of satellite attitude. The time series of the residuals are used to build WNN and wLSTM models to predict the faults of satellite attitude control system. A conclusion is given according to comparing the …

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Design And Implement Of Semi Physical Simulation System For Underwater Acoustic Imaging, Ruonan Fan, Jijun Jiang, Naiwei Sun Dec 2019

Design And Implement Of Semi Physical Simulation System For Underwater Acoustic Imaging, Ruonan Fan, Jijun Jiang, Naiwei Sun

Journal of System Simulation

Abstract: A semi physical simulation system based on underwater scale target and acoustic imaging is designed. Functional requirements are presented, the echo models of underwater scale target acoustic image are established through the planar element method, the structure, hardware and software are designed, the real-time signal generation techniques of applying the model to the simulation system are researched. The results of underwater experiment show that the simulation system can simulate the acoustic imaging echo signal of Benchmark submarine model, the imaging results are recognizable to some extent, it can be promoted to any underwater scale target and meet the …

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Research On Supporting Action Model Of Long-Rang Strike Space Reconnaissance Based On Combination Mode, Changliang Xiao, Jingyu Yang, Wu Xi, Ma Jun, Xiaojing Yin Dec 2019

Research On Supporting Action Model Of Long-Rang Strike Space Reconnaissance Based On Combination Mode, Changliang Xiao, Jingyu Yang, Wu Xi, Ma Jun, Xiaojing Yin

Journal of System Simulation

Abstract: Space reconnaissance support operations mainly undertake the tasks of target detection and identification in the early stage of strike, target guidance during strike and damage effect evaluation after strike. Based on EBI(Entity, Behavior, Interaction)modeling framework, this paper describes the entity models of signal intelligence sensor, radar alarm sensor and imaging sensor, constructs a combined mode of space reconnaissance support operation. It mainly models the combined mode algorithm of three sensors and their respective target detection behavior rules, whick is conductive to improving reconnaissance efficiency and enhancing intelligence quality in combat operations.

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The Distribution Of Ultra-Diffuse And Ultra-Compact Galaxies In The Frontier Fields, Steven Janssens, Roberto Abraham, Jean Brodie, Duncan Forbes, Aaron Romanowsky Dec 2019

The Distribution Of Ultra-Diffuse And Ultra-Compact Galaxies In The Frontier Fields, Steven Janssens, Roberto Abraham, Jean Brodie, Duncan Forbes, Aaron Romanowsky

Faculty Publications

Large low-surface-brightness galaxies have recently been found to be abundant in nearby galaxy clusters. In this paper, we investigate these ultra-diffuse galaxies (UDGs) in the six Hubble Frontier Fields galaxy clusters: A2744, MACS J0416.1−2403, MACS J0717.5+3745, MACS J1149.5+2223, AS1063, and A370. These are the most massive (1–3 × 1015 M ⊙) and distant (0.308 < z < 0.545) systems in which this class of galaxy has yet been discovered. We estimate that the clusters host of the order of ~200–1400 UDGs inside the virial radius (R 200), consistent with the UDG abundance–halo-mass relation found in the local universe, and suggest that UDGs may be formed in clusters. Within each cluster, however, we find that UDGs are not evenly distributed. Instead their projected spatial distributions are lopsided, and they are deficient in the regions of highest mass density as traced by gravitational lensing. While the deficiency of UDGs in central regions is not surprising, the lopsidedness is puzzling. The UDGs, and their lopsided spatial distributions, may be associated with known substructures late in their infall into the clusters, meaning that we find evidence both for formation of UDGs in clusters and for UDGs falling into clusters. We also investigate the ultra-compact dwarfs (UCDs) residing in the clusters, and find that the spatial distributions of UDGs and UCDs appear anticorrelated. Around 15% of UDGs exhibit either compact nuclei or nearby point sources. Taken together, these observations provide additional evidence for a picture in which at least some UDGs are destroyed in dense cluster environments and leave behind a residue of UCDs.

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California Stream Condition Index (Csci) Score Analysis Of Streams Sampled From 1998 To 2017 In The San Francisco Bay Region, Jenna Rais Dec 2019

California Stream Condition Index (Csci) Score Analysis Of Streams Sampled From 1998 To 2017 In The San Francisco Bay Region, Jenna Rais

Master's Projects and Capstones

Human impacts to California’s streams have altered the state’s riparian and hydrological landscape. This is a critical issue with regard to natural resources, including ecosystem services such as water availability and water quality. Regulations have a limited amount of impact on the improvement of this landscape and can also become complicated by politics. Scientific advances have developed ways to quantify and describe the quality of streams, this includes the development of the California Stream Condition Index (CSCI) which is based on benthic macroinvertebrate (BMI) population numbers and functions. This index allows scientists to not only score the quality of a …

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Research On Gear Appearance Defect Recognition Based On Improved Faster R-Cnn, Weixi Ji, Du Meng, Peng Wei, Xu Jie Dec 2019

Research On Gear Appearance Defect Recognition Based On Improved Faster R-Cnn, Weixi Ji, Du Meng, Peng Wei, Xu Jie

Journal of System Simulation

Abstract: In order to achieve automatic identification of gear appearance defects and improve the qualification rate of gear products, aiming at the generalization of traditional defect recognition algorithms and the time-consuming of manual features extraction, this paper proposes an improved gear flaw detection algorithm for Faster R-CNN. VGG-2CF network is designed to improve the ability to identify smaller targets. Introducing AM-Softmax loss function is introduced to reduce the intra-class variation and optimize the inter-class difference. Combining with F-measure in machine learning algorithm, an AMF-Softmax loss function is proposed to solve the problem of data imbalance. The experimental results show the …

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Survey Of Vision-Based Augmented Reality 3d Registration Technology, Shouming Hou, Han Ji, Yudong Zhang, Ziqiu Zhu Dec 2019

Survey Of Vision-Based Augmented Reality 3d Registration Technology, Shouming Hou, Han Ji, Yudong Zhang, Ziqiu Zhu

Journal of System Simulation

Abstract: Three-dimensional registration technology is one of the core technologies for augmented reality system implementation. In recent years, with the maturity of augmented reality hardware technology and the expansion of application fields, vision-based three-dimensional registration technology has received more attention and development. This paper introduces the basic principles and classification methods of 3D registration technology, focuses on the analysis of the principles and research status of three kinds of visual three-dimensional registration technology based on artificial identification, natural feature points and model.Furthermore, the defects and treatment methods of three visual registration technologies are discussed. The development prospect of visual 3D …

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Rehabilitation Training System Of Vr-Based Speech Apraxia, Huanhuan Jiao, Zhigeng Pan, Shuchang Xu, Qingshu Yuan Dec 2019

Rehabilitation Training System Of Vr-Based Speech Apraxia, Huanhuan Jiao, Zhigeng Pan, Shuchang Xu, Qingshu Yuan

Journal of System Simulation

Abstract: Aiming at the problem that the enthusiasm of active training in patients with traditional speech apraxia rehabilitation is gradually weakened, a virtual reality-based rehabilitation training system for speech apraxia is designed. The system simulates the 26 monosyllabic pronunciation mouths shapes made by virtual human in Chinese and uses it for the learning module. It is proposed to identify 26 monosyllabic words by using the isolated word speech recognition algorithm, which improves the accuracy of speech recognition. The system includes a training module and a scene module for assisting the patient's pronunciation rehabilitation training. The evaluation results show that …

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A Temporal Action Detection Algorithm Based On Spatio-Temporal Feature Pyramid Network, Liu Wang, Jinyu Sun, Shiwei Ma Dec 2019

A Temporal Action Detection Algorithm Based On Spatio-Temporal Feature Pyramid Network, Liu Wang, Jinyu Sun, Shiwei Ma

Journal of System Simulation

Abstract: In view of the discontinuity of motion timing detection in the frame-level prediction network structure, a novel algorithm based on spatio-temporal feature pyramid network (ST-FPN) is proposed. In the frame-level action prediction, several 3D convolution-de-convolution (CDC) networks are used to sample spatial feature down to 1 dimension and sample temporal feature up to corresponding proposal level. Then the prediction scores of different CDC networks are fused by non-maximum suppression (NMS). The softmax classifier is used to classify frame-level actions, and then temporal action detection is obtained. The experimental results on dataset THUMOS14 show that the proposed algorithm improves the …

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Design And Finite Element Analysis Of Reflector Spherical Shell For Flight Simulator, Hailiang Bai, Jiang Nan, Zhang Liao, Yuewen Fu Dec 2019

Design And Finite Element Analysis Of Reflector Spherical Shell For Flight Simulator, Hailiang Bai, Jiang Nan, Zhang Liao, Yuewen Fu

Journal of System Simulation

Abstract: The fight simulator with six-degree-of-freedom motion platform can simulate the flight attitude in real time and provide realistic overload dynamic feeling, which requires that the equipment on the platform must adapt to the overload during flight simulation. To solve the contradiction between the rigidity and weight of material, the glass fiber composite material is used to design and manufacture the spherical shell of the mirror . To improve the optical collimation of the reflector, the specific hyperboloid aspheric surface is selected as the surface design scheme,the 3D model of the spherical shell is constructed. The parameters of the …

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Research On Dual-Antenna Gnss-Assisted Mins Navigation Method, Hailu Wang, Su Zhong, Liu Ning, Liu Hong, Guodong Fu Dec 2019

Research On Dual-Antenna Gnss-Assisted Mins Navigation Method, Hailu Wang, Su Zhong, Liu Ning, Liu Hong, Guodong Fu

Journal of System Simulation

Abstract: For the integrated navigation system of the single-antenna GNSS-assisted MEMS strap-down inertial navigation system (MINS), the heading angle divergence is invalid when the vehicle is stationary and linear motion, and the error is large. The method of the dual-antenna GNSS-assisted MINS integrated navigation based on EKF is proposed. The error state model is established, and the extended Kalman filter combined filter (EKF) algorithm is designsed for simulation verification. The driving test is carried out by comparing the high-precision SPAN-CPT. The results show that the yaw angle and pitch angle accuracy are 0.2 RMS, 0.3 RMS, which can be used …

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Research On Nondestructive Blood Glucose Cloud Detection System Based On Improved Deep Regression Network, Mengjia He, Yingnian Wu, Yang Rui Dec 2019

Research On Nondestructive Blood Glucose Cloud Detection System Based On Improved Deep Regression Network, Mengjia He, Yingnian Wu, Yang Rui

Journal of System Simulation

Abstract: Invasive blood glucose measurement has a strong sense of discomfort and risk of infection, so the study of non-invasive blood glucose has a strong practical significance. At present, the optical method is not convenient for practical use, and the energy conservation method requires strict requirements. In view of the above problems, infrared thermography is used to detect blood glucose. After acquiring infrared thermal images of face figure, we extract the gray feature and reduce its dimension. In order to speed up the training and prevent over fitting, depth regression network is improved to model the infrared thermal image gray …

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Short-Term Wind Power Prediction Based On Improved Firefly Algorithm, Jiale Ding, Guochu Chen, Kuo Yuan Dec 2019

Short-Term Wind Power Prediction Based On Improved Firefly Algorithm, Jiale Ding, Guochu Chen, Kuo Yuan

Journal of System Simulation

Abstract: A wind power prediction model based on improved complementary set empirical mode decomposition and improved firefly algorithm to optimize echo state network is proposed to solve the problems of low accuracy in wind power with large randomness and strong volatility prediction of traditional echo state network prediction model. The wind speed series are decomposed into a series of intrinsic modes by using the improved complementary ensemble empirical mode decomposition. The new modes are used to predict wind power by using echo state network, the optimal weight of the model is found by the improved firefly algorithm. The output results …

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Research On Simulation Optimization Of Disk-Based Storage Operation Mode In Warehouse, Danlan Xie, Liu Meng, Haihong Yu, Chen Jing, Yubo Zhou, Kazi Mohiuddin Dec 2019

Research On Simulation Optimization Of Disk-Based Storage Operation Mode In Warehouse, Danlan Xie, Liu Meng, Haihong Yu, Chen Jing, Yubo Zhou, Kazi Mohiuddin

Journal of System Simulation

Abstract: As the efficiency of operation affects the overall competitiveness of the port, it is very necessary to design the storage operation mode reasonably. A disk-based storage operation mode is proposed. And the simulation model is established by using the logistics simulation software FlexSim based on the operational requirements of the warehouse. Through a large number of simulation experiments, comparing the primary storage mode with the disk-based storage mode, the results of the increase in total idle rate and the more balanced distribution of each hour utilization ratio of the forklifts are obtained. The result verifies the feasibility and effectiveness …

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Path Planning For Mobile Sink Based On Enhanced Ant Colony Optimization Algorithm In Wireless Sensor Networks, Shanshan Ji Dec 2019

Path Planning For Mobile Sink Based On Enhanced Ant Colony Optimization Algorithm In Wireless Sensor Networks, Shanshan Ji

Journal of System Simulation

Abstract: To reduce the energy consumption and sink mobile distance of mobile sink wireless sensor networks simultaneously, a path planning algorithm for mobile sink based on enhanced ant colony optimization algorithm in wireless sensor networks is proposed. Genetic operators are introduced to ant colony optimization algorithm in order to prevent ant colony optimization premature. The non-uniform of data distribution is considered as the constraint condition, the network lifetime and sink mobile distance are considered as a multi-objective problem, and the enhanced ant colony optimization is adopted to search the Pareto sub-optimal sets of rendezvous points. The simulation results show that …

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Attitude Control Of Hypersonic Vehicle Considering Input Saturation, Xiaocen Liu, Yunjie Wu, Xu Peng Dec 2019

Attitude Control Of Hypersonic Vehicle Considering Input Saturation, Xiaocen Liu, Yunjie Wu, Xu Peng

Journal of System Simulation

Abstract: Aiming at the design of attitude control of hypersonic vehicles, the sliding mode disturbance observer is used to compensate the composite disturbance, meanwhile the dynamic surface control method is used to deal with the design of the nonlinear control system. Considering the input saturation problem, the control input is expanded into a new variable to design the controller, which is different from the direct limit of the rudder deviation. The simulation results show that the dynamic surface control method based on sliding mode observer has stronger robustness than the simple dynamic inversion control method, but the control inputs of …

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Fault Identification Of High-Speed Train Bogie Based On Siamese Convolutional Neural Network, Yunpu Wu, Weidong Jin, Junxiao Ren Dec 2019

Fault Identification Of High-Speed Train Bogie Based On Siamese Convolutional Neural Network, Yunpu Wu, Weidong Jin, Junxiao Ren

Journal of System Simulation

Abstract: The performance degradation and failure of high-speed train bogie components will threaten the operation security of train. This paper proposes a fault type identification method based on siamese convolutional neural network to address the scarcity of data and the high-dimension of monitoring signals. Deep residual network with one-dimension convolution layers is employed for features extraction and fusion of vibration signals from multiple sensors. The siamese structure is employed to obtain the similarities between samples. Fault types are identified by ranking similarities in the support set. The experimental results show that the proposed method can identify the fault types with …

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Quality Control Method Based On Quantum Genetic Clustering Algorithm, Wang Jie, Wang Yan Dec 2019

Quality Control Method Based On Quantum Genetic Clustering Algorithm, Wang Jie, Wang Yan

Journal of System Simulation

Abstract: This paper proposes a method of quality control chart recognition based on Quantum Genetic Clustering Algorithm. This method is divided into two parts: quality feature extraction and pattern classification. By combining Quantum Genetic Algorithm(QGA) and K-means algorithm, a quantum genetic clustering algorithm based on a mechanism for determining the rotation direction of a quantum rotary gate is proposed, and its performance is verified by experimental simulation. Based on the clustering analysis of quality data using the quantum genetic algorithm proposed in this paper, a control chart feature description method is proposed. With this feature as input, Support Vector …

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