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Articles 2731 - 2760 of 3613
Full-Text Articles in Computer Sciences
Adaptive Optimization In Feature-Based Slam Visual Odometry, Yanan Yu, Dunhuang Shi, Chunjie Hua
Adaptive Optimization In Feature-Based Slam Visual Odometry, Yanan Yu, Dunhuang Shi, Chunjie Hua
Journal of System Simulation
Abstract: Aiming to reduce the impact of dynamic environments on simultaneous localization and mapping (SLAM) of mobile robots, an adaptive optimization method in a feature-based visual odometry is proposed. The method helps to improve the invariance of image feature in illumination changing situation and to extract features effectively in areas where the texture information is not sufficient to make contributions to feature matching. Meanwhile, down sampling is applied to establish image pyramids and each scaled image is divided into cells based on a defined rule. Illumination adaptive nonlinear adjustments for each cell are applied to increase the image details, and …
Planning And Analysis On Uav Trajectory Based On Pce Method, Sijie Zeng, Yan Liang, Xiaojun Duan
Planning And Analysis On Uav Trajectory Based On Pce Method, Sijie Zeng, Yan Liang, Xiaojun Duan
Journal of System Simulation
Abstract: Focusing on the uncertainty in the UAV trajectory planning, combined with the artificial potential energy method, a UAV trajectory planning method based on polynomial chaos expansion (PCE), which can also efficiently obtain the optimal parameters of the model based on artificial potential field method is proposed. The PCE proxy model is established, and the stochastic collocation method is used to quickly solve the problem, so as to avoid the insufficient computing resources. Through the Sobol sensitivity analysis, the calculation overhead of the uncertainty parameters in the trajectory planning model is reduced. Cases of UAV trajectory planning prove the effectiveness …
Research On Intelligent Vehicle Trajectory Tracking Control Based On Robust Model Prediction, Hongguang Lu, Shuen Zhao
Research On Intelligent Vehicle Trajectory Tracking Control Based On Robust Model Prediction, Hongguang Lu, Shuen Zhao
Journal of System Simulation
Abstract: Aiming at the low control accuracy and poor robustness of traditional trajectory tracking controller based on the tracking error model in complex driving environment, a robust model predictive trajectory tracking control strategy is designed. The vehicle convex multicellular dynamic model is used to explicitly describe the vehicle dynamic characteristics, and the robust performance objective function is designed in combination with the trajectory tracking multi-objective constraint, and the state feedback control law is solved through the linear matrix inequality optimization. Feedforward control is introduced to eliminate the steady-state errors and improve the tracking accuracy. The simulation result shows that …
Agent- Based Research On Power Absorption Simulation Analysis Of Renewable Energy, Zhang Luan, Zhengjun Luo, Dequn Zhou
Agent- Based Research On Power Absorption Simulation Analysis Of Renewable Energy, Zhang Luan, Zhengjun Luo, Dequn Zhou
Journal of System Simulation
Abstract: Aiming at the “three abandonment”, a guarantee mechanism for the consumption of renewable energy power is proposed in our country. In order to stimulate the consumption of renewable energy power, a multi-agent simulation method is used to analyze the transaction behavior and interaction of market players, and the key factors affecting the consumption of renewable energy power is analyzed to simulated the consumption of renewable energy and the evolution of the number of active consumers. The results show that the subscribed green certificate can directly promote the consumption of renewable energy power, and it is necessary to comprehensively consider …
Autonomous Vehicle Path Tracking Control System Based On Energy Optimization, Xiaolong Wu, Fugen Xia, Chen Jing, Xu Jia
Autonomous Vehicle Path Tracking Control System Based On Energy Optimization, Xiaolong Wu, Fugen Xia, Chen Jing, Xu Jia
Journal of System Simulation
Abstract: Powertrain control is important to the dynamic performance and economy of driverless cars and a path following control strategy based on energy optimization is proposed. The control strategy includes two parts. The nonlinear model predictive control is used in the upper controller to calculate the required power parameters and front wheel angle. The lower-level controller is designed based on the optimal value of motor energy consumption which ensure the motor being always running at the optimal state of efficiency. In addition, the continuously variable transmission (CVT) is dynamically adjusted according to the motor state to meet the vehicle power …
Fault Tolerant Control And Simulation Of Quadrotor Based On Adaptive Observer, Zhao Jing, Wang Peng, Xiaoqian Ding, Guoping Jiang, Fengyu Xu, Yanfei Sun
Fault Tolerant Control And Simulation Of Quadrotor Based On Adaptive Observer, Zhao Jing, Wang Peng, Xiaoqian Ding, Guoping Jiang, Fengyu Xu, Yanfei Sun
Journal of System Simulation
Abstract: Focusing on the actuator fault of quadrotor, an integral backstepping sliding mode combined with adaptive observer is proposed to ensure the safety and reliability of the quadrotor. A dynamic model of the quadrotor with actuator fault are established. An adaptive observer is proposed to observe the state and estimate the actual value of the fault. The attitude fault tolerant controller and position controllers are designed by the method of integral backstepping combined with the sliding mode control to complete the trajectory tracking of attitude and position. The simulation results show that the control strategy can quickly and accurately track …
Simulation Of Rocket Exhaust Plumes Recognition Based On Dynamic Time Warping, Liu Hao, Hongxia Mao, Zhihe Xiao, Liu Zheng
Simulation Of Rocket Exhaust Plumes Recognition Based On Dynamic Time Warping, Liu Hao, Hongxia Mao, Zhihe Xiao, Liu Zheng
Journal of System Simulation
Abstract: By analyzing the infrared radiation characteristics of the rocket exhaust plumes and summarizing the changing law of the radiant intensity sequence, an improved recognition algorithm based on Dynamic Time Warping algorithm is proposed. In order to improve the effect of sequence shape similarity measurement, the distance matrix and matching path are calculated by the derivative sequence, and the distance is recalculated according to the matching path and radiant intensity value. The problem of path matching affected by the non-uniformity of observation sequence length is solved to a certain extent by using the prefix and suffix relaxation factors. The simulation …
Engine Wear Fault Diagnosis Based On Supervised Kernel Entropy Component Analysis, Zhichao Zhu, Dinghui Wu, Yuanchang Yue
Engine Wear Fault Diagnosis Based On Supervised Kernel Entropy Component Analysis, Zhichao Zhu, Dinghui Wu, Yuanchang Yue
Journal of System Simulation
Abstract: Focus on the influence of environment on engine operation, which leads to a large amount of redundant information and nonlinear structure in oil spectral data that affects the engine fault diagnosis results, the feature extraction method of SKECA (supervised kernel entropy component analysis) is proposed. A supervised learning algorithm is adopted on the basis of Kernel Entropy Component Analysis, which extracts the inherent geometric features of oil spectrum data to make the extracted fault features include the discriminative information. GA (genetic algorithm) is used to find parameters to optimize the results of feature extraction, and SVM (support vector machine) …
Visual Analysis Of Cross-Domain Association Of Time-Series Data, Beibei Han, Yingmei Wei, Yujie Fang, Shanshan Wan
Visual Analysis Of Cross-Domain Association Of Time-Series Data, Beibei Han, Yingmei Wei, Yujie Fang, Shanshan Wan
Journal of System Simulation
Abstract: Time series data is the important research object of data mining. The current visual analysis technology of time series data rarely conducts the cross-domain correlation. The development and evolution of statistical time series data in the spatio-temporal domain and the text theme data in the cognitive domain cannot be simulitaneously supervised in a unified view. The user's visual analysis process based on cross-domain time series data is abstracted and a visual analysis process model is proposed. A multi-view collaborative cross-domain correlation visual analysis tool is designed on the basis of the model. The case study of epidemic time …
Uncertainty Simulation Method Based On Deep Bayesian Networks Learning, Nie Kai, Kejun Zeng, Qinghai Meng
Uncertainty Simulation Method Based On Deep Bayesian Networks Learning, Nie Kai, Kejun Zeng, Qinghai Meng
Journal of System Simulation
Abstract: There are lots of uncertain elements in battlefields situation assessment and the uncertainty simulation would enhance the ability of situation assessment. A deep variational autoencoder bayesian networks (BN) model with memory module is proposed aiming at the problem of being unable to represent the uncertainties exactly caused by the various combat objects and more uncertain elements. Based on the deep BN learning, the situation assessment model is designed from the deep generative model. The principle of deep generative model mixing with the memory module is discussed and the leaning and reasoning process of the model is explained. The proposed …
Optimization And Prediction For Multi-Robot Combination Maximum Coverage Area, Yutong Wang, Shiwei Ma, Yuanrui Yang, Chaoyu Chen
Optimization And Prediction For Multi-Robot Combination Maximum Coverage Area, Yutong Wang, Shiwei Ma, Yuanrui Yang, Chaoyu Chen
Journal of System Simulation
Abstract: Aiming at the optimal control of the multi-robot combination maximum coverage area, based on the intensity radial attenuation disc model and following the superposition principle, a method for estimating, optimizing and predicting the effective coverage area of the multi-robot combination is proposed. The Monte Carlo method is used to estimate the effective coverage area of the robot combination, and the multiple population genetic algorithm is used to obtain the maximum effective coverage area of the combination, and the support vector machine regression is used to predict the relationship between the number of robots and the maximum effective coverage area. …
Research And Implementation Of On-Board Human Factors Collaborative Simulation System, Changqing Yin, Tianran Tan, Jianmin Wang
Research And Implementation Of On-Board Human Factors Collaborative Simulation System, Changqing Yin, Tianran Tan, Jianmin Wang
Journal of System Simulation
Abstract: In order to improve the multi-vehicle evaluation and follow the trend of the Internet of Vehicles in modern vehicle-road collaborative system, an on-board human factors collaborative simulation system is built. Distributed theory is used to establish a joint platform for vehicle simulation, and an on-board human factors co-simulation system is built and MQTT network is used to optimize the data distribution mechanism and data collection mechanism. The simulation experiment shows that the built on-board human factor co-simulation platform reduces the coupling between the participating experimental subsystems and the main system, and has good robustness and flexibility. The distributed data …
Research On Optimal Allocation Method Of Aircraft Towing Rules Based On Multi-Agent, Zhao Zheng, Hu Li, Yuanyuan Qian, Jin Hui, Aiping Jia
Research On Optimal Allocation Method Of Aircraft Towing Rules Based On Multi-Agent, Zhao Zheng, Hu Li, Yuanyuan Qian, Jin Hui, Aiping Jia
Journal of System Simulation
Abstract: In order to study and optimize the effect of aircraft towing rules on aircraft on bridge rate and flight normality, a towing rule configuration method based on surface capacity and demand balance is proposed. By constructing a multi-agent discrete simulation model based on surface operation, the collaborative optimization effect of aircraft on bridge rate and flight regularity is achieved, and which is verified by the example of Beijing Daxing International Airport. The results show that the towing rule configuration method based on airfield capacity and demand balance can obviously improve the aircraft on bridge rate and flight normality, …
Design And Implementation Of Photovoltaic Energy Harvesting Automaton, Iskandar Askarov
Design And Implementation Of Photovoltaic Energy Harvesting Automaton, Iskandar Askarov
Theses
Global domestic electricity consumption has been rapidly increasing in the past three decades. In fact, from 1990 to 2020, consumption has more than doubled from 10,120 TWh to 23,177 TWh [1]. Moreover, consumers have been turning more towards clean, renewable energy sources such as Photovoltaic. According to International Energy Agency, global Solar power generation alone in 2019 has reached almost 3% [4] of the electricity supply. Even though the efficiency of photovoltaic panels has been growing, presently, the highest efficiency solar panels available to an average consumer range only from 20%-22% [14]. Many research papers have been published to increase …
Digital Evidence In Appeals Of Criminal Cases Before The U.S. Courts Of Appeal: A Review Of Decisions And Examination Of The Legal Landscape From 2016 – 2020, Martin Novak
Journal of Digital Forensics, Security and Law
This study is a follow-up to Digital Evidence in Criminal Cases before the U.S. Courts of Appeal: Trends and Issues for Consideration – 2010 to 2015. The current study examines appeals of criminal cases before the United States Courts of Appeal from January 2016 through August 2020, where one or more appeal claims were related to digital evidence. The purpose of this research was to determine if the legal landscape has changed since 2015; examine the most relevant legal issues related to digital evidence; and analyze how precedential cases may have affected digital forensics as evidence.
Simulation Research On U-Automated Container Terminal, Ding Yi, Tiantian Li
Simulation Research On U-Automated Container Terminal, Ding Yi, Tiantian Li
Journal of System Simulation
Abstract: To analyze the new U-layout effect on the handling operation efficiency in automated container terminal, the U-automated container terminal simulation model is established by FlexTerm software to visualize the handling operation process. The traditional automated terminal simulation model is established to compare the working efficiency under different working modes. The working ability of terminal handling equipment such as AGV(Automated Guided Vehicle), yard cranes and rail-mounted gantry cranes are compared by simulation tests. Simulation results show that due to the creation of yard layout and handling technology, the superiority of U-layout is proved when the working efficiency of each handling …
Intelligent Control Of Wastewater Treatment Processes Based On Adaptive Immune Optimization, Li Fei, Su Zhong
Intelligent Control Of Wastewater Treatment Processes Based On Adaptive Immune Optimization, Li Fei, Su Zhong
Journal of System Simulation
Abstract: In order to solve the problems of excessive energy consumption and excessive effluent quality in wastewater treatment process control, an intelligent control system based on adaptive immune optimization (AIOIC) is proposed. A hierarchical control strategy is designed, and a fast online self-organizing fuzzy neural network based on singular value decomposition (SVDFNN) is used to construct the mathematical model of wastewater treatment energy consumption and effluent quality. In order to obtain the optimal set values of dissolved oxygen and nitrate nitrogen, an adaptive hybrid evolutionary immune optimization algorithm is designed. The self-organizing recursive fuzzy neural network controller is used …
Track Deception Modeling Method Based On Multi-Jammer Cooperation, Wang Rui, Xiangyang Li, Zhili Zhang, Hongguang Ma
Track Deception Modeling Method Based On Multi-Jammer Cooperation, Wang Rui, Xiangyang Li, Zhili Zhang, Hongguang Ma
Journal of System Simulation
Abstract: The false track generated by the jammer formation is an effective interference measure against networked radars. This paper starts from the basic principle of false track generation and presents the model of the measurement error of the radar for the false track and the control error of the jammer formation. It also presents an analysis of the effects of these errors on the false track. The effectiveness of the false track is further analyzed through the confrontation scenario between the rectangular front formation of a certain type of equipment and networked radars. The simulation results show that the false …
Research On Supply Chain Recovery Strategy Under Disruption Risks, Yang Yi, Peng Chen, Yujiu Yang, Yulong Wang
Research On Supply Chain Recovery Strategy Under Disruption Risks, Yang Yi, Peng Chen, Yujiu Yang, Yulong Wang
Journal of System Simulation
Abstract: Aiming at supply chain disruptions, two effective supply chain recovery strategies are proposed, namely, a supplier’s preset emergency inventory strategy and a manufacturer’s product change strategy, meanwhile, emergency inventory storage cost and products return rate after change are also taken into consideration. In order to maximize the manufacturer’s profit and customer satisfaction, a single-objective model and a bi-objective model are established, respectively. The optimization problems in the two models are transformed into mixed integer programming problems, moreover, corresponding solution algorithms are presented based on ILOG CPLEX. The simulation results show that the disruption recovery strategies proposed can not only …
Radar Emitter Signal Identification Via Distance Features, Yingkun Huang, Weidong Jin, Yan Kang, Jiehao Zhu
Radar Emitter Signal Identification Via Distance Features, Yingkun Huang, Weidong Jin, Yan Kang, Jiehao Zhu
Journal of System Simulation
Abstract: Aiming at the problem that traditional recognition methods of radar emitter signal have low accuracy in low signal to noise ratio (SNR) environment, and are usually suitable for only several specific radar signals, an identification approach of radar signal based on distance features is proposed. Several cluster centers are extracted via the k-means algorithm, and the Dynamic Time Warping (DTW) values between the radar signal and the cluster center are calculated respectively, which are combined as the input features of k-Nearest Neighbor (k-NN) algorithm. The simulation results show that when the SNR is 3 dB, the identification rate …
An Evolutionary Multi-Objective Simulation Optimization Algorithm For Supply Chain With Uncertain Demands, Hongfeng Wang, Yitian Zhang, Jingze Chen
An Evolutionary Multi-Objective Simulation Optimization Algorithm For Supply Chain With Uncertain Demands, Hongfeng Wang, Yitian Zhang, Jingze Chen
Journal of System Simulation
Abstract: During the COVID-19 pandemic, supply chain of manufacturing companies is facing more severe product demand uncertainty, which is manifested in the sharp increase in demand for certain types of products and the increased fluctuations in supply for raw materials. For this supply chain optimization problem with demand uncertainty, a multi-objective stochastic programming model is developed in order to maximize the total profit and product order fulfillment rate simultaneously in this paper. For solving the investigated problem, a new evolutionary multi-objective simulation optimization algorithm is proposed by combining the mechanism of NSGA-II and simulation computing budget allocation adaptively. Experimental …
Research On Detection Data Driven Calibration Method Of Traffic Simulation Parameters, Wenxin Ma, Ruimin Li
Research On Detection Data Driven Calibration Method Of Traffic Simulation Parameters, Wenxin Ma, Ruimin Li
Journal of System Simulation
Abstract: To improve the accuracy of traffic simulation model and timely response of traffic demand and driving behavior changes, dynamic calibration method of simulation parameters based on detection data is proposed. Dynamic interaction between detection data and simulation platform is proposed. Intersection of Guanghua Road/Jintong East Road in Beijing and five consecutive intersections on Youyi Street in Baotou are Selected as study cases. Sensitivity analysis is conducted on initial parameter combinations. Based on the analysis results, parameters to be calibrated are selected. Models of cases are developed in VISSIM and driving behavior parameters are calibrated. Simulation results show that …
Weld Bead Size Prediction Of Wire And Arc Additive Manufacturing Based On Acs-Dbn, Dong Hai, Xiuxiu Gao, Mingqi Wei
Weld Bead Size Prediction Of Wire And Arc Additive Manufacturing Based On Acs-Dbn, Dong Hai, Xiuxiu Gao, Mingqi Wei
Journal of System Simulation
Abstract: Welding pass overlap is the essence of wire and arc additive manufacturing (WAAM) technology. Appropriate process parameter selection is of great significance to control the welding pass geometry and improve the dimensional accuracy of the molded parts. A prediction model of deep beilef network (DBN) optimized by adaptive cuckoo search (ACS) algorithm is constructed. The welding width and residual height of the weld pass are predicted based on the four technological parameters of the given nozzle height, welding current, welding speed and wire feeding speed. The optimal number of hidden layers and hidden elements are determined based on the …
Study On Prediction Of Crystal Properties Based On Deep Learning, Buwei Wang, Wang Min, Fan Qian, Ya'nan Wang, Hanwen Zhang, Yunliang Yue
Study On Prediction Of Crystal Properties Based On Deep Learning, Buwei Wang, Wang Min, Fan Qian, Ya'nan Wang, Hanwen Zhang, Yunliang Yue
Journal of System Simulation
Abstract: Predicting crystal properties using traditional machine learning methods requires complex feature engineering. In order to bypass time-consuming feature engineering, element network (ElemNet), representation learning from stoichiometry (Roost), compositionally-restricted attention-based network (CrabNet) and crystal graph convolution neural network (CGCNN) based on deep learning technology are used to simulate the formation energy, total energy per atom, band gap, and Fermi energy of crystal. The residual learning is introduced into CGCNN, and a crystal graph convolution residual neural network (CGCRN) is proposed. In the CGCRN, the number of hidden layers and the number of nodes in the hidden layers are increased, …
Improved Ant Colony Optimization Algorithm For Jamming Resource Allocation, Qingyun Wang, Dezhong Jiao, Shi Shuo, Genyan Peng, Junhua Sun, Yuxin Duan
Improved Ant Colony Optimization Algorithm For Jamming Resource Allocation, Qingyun Wang, Dezhong Jiao, Shi Shuo, Genyan Peng, Junhua Sun, Yuxin Duan
Journal of System Simulation
Abstract: Ant Colony Optimization (ACO) is a new intelligence optimization algorithm. When applied to jamming resource allocation, the velocity of convergence in optimization process is slow and the probability of obtaining the global optimal solution is low. In order to raise the efficiency of jamming resource allocation and the probability of getting global optimal solution, the attenuation factor is improved to a variable that changes according to the exponential function in optimization process. The attenuation factor is taken as a relatively small value in the initial search phase, and increases monotonically and exponentially as the number of iterations increases. Simulation …
Research On Semi-Physical Simulation Model Of Special Vehicle Cockpit With Force Feedback, Liang Feng, Zhili Zhang, Xiangyang Li, Yihao Li, Wang Bei, Long Yong
Research On Semi-Physical Simulation Model Of Special Vehicle Cockpit With Force Feedback, Liang Feng, Zhili Zhang, Xiangyang Li, Yihao Li, Wang Bei, Long Yong
Journal of System Simulation
Abstract: To improve the interaction and immersion of cockpit simulation training system, a semi-physical model of special vehicle cockpit with force feedback is studied. The important force feedback parts of the semi-physical simulation model are designed to provide more real operation experience for operators. The simulation training method of special vehicle cockpit based on dynamic model is studied to match the action input of operators with scene changes and provide a high fidelity visual experience. The driving simulation operation process of special vehicle is analyzed and verified. Simulation experiments show that the model has the characteristics of high precision, fast …
Special Vehicle Driving Training Simulation System Based On Integration Of Virtuality And Reality, Xiangyang Li, Wang Xiao, Zhili Zhang, Yihao Li, Long Yong
Special Vehicle Driving Training Simulation System Based On Integration Of Virtuality And Reality, Xiangyang Li, Wang Xiao, Zhili Zhang, Yihao Li, Long Yong
Journal of System Simulation
Abstract: Aiming at the actual demands of special vehicle driving training, special vehicle driving training simulation system is designed and developed based on the integration of virtuality and reality mode. Through building all kinds of mathematical models, functional modules, workflows and control software, and applying the cab that same as actual equipment with manipulating device, central control instrument and driving seat, immersive driving training environment with integration of virtuality and reality is established based on 6-DoF motion platform and its control system as well as multi-channel visual display device. It can provide the integrated support platform with “educating, training and …
Low Power Visual Odometry Technology Based On Monocular Depth Estimation, Ma Rong, Qiurui Chen, Zhang Han, Mei Zheng, Wang Rui, Wei Wei
Low Power Visual Odometry Technology Based On Monocular Depth Estimation, Ma Rong, Qiurui Chen, Zhang Han, Mei Zheng, Wang Rui, Wei Wei
Journal of System Simulation
Abstract: With the development of artificial intelligence, precision machinery and computing technology, micro-unmanned system will play an important role in the future battlefield. To solve the lack of monocular visual odometry scale, micro robot power consumption and load limits, the monocular depth estimation technology is introduced and a low view dataset is collected. A convolutional neural network to predict depth information from a single image is built, and the structure of neural network model is optimized. The depth estimation with monocular visual odometry are combined and deployed on JetsonNano. Experiments show that the combined monocular visual odometry can recover scale …
Brief Review On Applying Reinforcement Learning To Job Shop Scheduling Problems, Xiaohan Wang, Zhang Lin, Ren Lei, Kunyu Xie, Kunyu Wang, Ye Fei, Chen Zhen
Brief Review On Applying Reinforcement Learning To Job Shop Scheduling Problems, Xiaohan Wang, Zhang Lin, Ren Lei, Kunyu Xie, Kunyu Wang, Ye Fei, Chen Zhen
Journal of System Simulation
Abstract: Reinforcement Learning (RL) achieves lower time response and better model generalization in Job Shop Scheduling Problem (JSSP). To explain the current overall research status of JSSP based on RL, summarize the current scheduling framework based on RL, and lay the foundation for follow-up research, the backgrounds of JSSP and RL are introduced. Two simulation techniques commonly used in JSSP are analyzed and two commonly used frameworks for RL to solve JSSP are given. In addition, some existing challenges are pointed out, and related research progress is introduced from three aspects: direct scheduling, feature representation-based scheduling, and parameter search-based scheduling.
Survey Of Ship Detection In Video Surveillance Based On Shallow Machine Learning, Zhenbo Bi, Shiyou Zhang, Yang Hua, Yuanhong Wu
Survey Of Ship Detection In Video Surveillance Based On Shallow Machine Learning, Zhenbo Bi, Shiyou Zhang, Yang Hua, Yuanhong Wu
Journal of System Simulation
Abstract: At present, detection of ship targets in video surveillance based on shallow machine learning methods is still attracting attention in the fields of underwater cultural heritage protection, marine aquaculture, maritime traffic, and port management. This paper provides a review and discussion for this kind of ship detection methods. The ship target detection based on video surveillance is divided into five parts according to the key technologies involved: preprocessing, region of interest extraction, target segmentation, ship feature extraction and ship type recognition. According to different functional modules, the core problems involved in them are pointed out, and the core ideas, …