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Adaptive SOM neural network algorithm 3

Adaptive SOM neural network algorithm

引用

3rd International Conference on Artificial Intelligence, Automation, and High-Performance Computing, AIAHPC 2023

作者： Wang, Xin Yan, Taishan School of Information Science and Engineering Hunan Institute of Science and Technology Hunan Yueyang China Hunan Institute of Science and Technology School of Information Science and Engineering China Key Laboratory of Hunan Province on Intelligent Control and Optimization of Complex Industrial Logistics System Hunan Yueyang China

ISBN: (数字)9781510666580

ISBN: (纸本)9781510666573

In order to improve the performance of traditional SOM model, an adaptive SOM neural network algorithm is proposed. By introducing the error square sum solution formula, the clustering error of the model sub-data set is calculated by using the method of cutting the data set, and the change trend of the clustering error is quickly obtained. Then the learning rate of the SOM network is adaptively adjusted according to this, and the convergence speed is accelerated on the basis of ensuring that the network is fully trained, thereby improving the performance of the SOM network. © 2023 SPIE.

关键词： Errors

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Vision Inertial Fusion Based on BP Neural Network for Aircraft Autonomous Positioning

Vision Inertial Fusion Based on BP Neural Network for Aircra...

引用

International Conference on Guidance, Navigation and control, ICGNC 2020

作者： Liu, Haiqiao Guan, Xujun Luo, Shibin Wu, Xia Xu, Dequan School of Automation Central South University Changsha410083 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China School of Aeronautics and Astronautics Central South University Changsha410083 China

ISBN: (纸本)9789811581540

Long-term navigation for aircraft in global position system (GPS) denied environment is a very challenging task. In this thesis, a novel aircraft autonomous positioning method based on fusion multi-modal image matching and inertial navigation system (INS) is proposed. This method consists of three steps. First, the coordinates of ground control points were obtained by matching the real-time image with the reference image. Then, PnP algorithm is employed for calculating the position of the aircraft. Finally, aircraft gets the optimal position by using BP neural network to combine the position estimated by inertial navigation and the results of multi-modal image matching. Simulation result displays that our method can effectively improve the positioning accuracy of aircraft. The accuracy of this method proposed in this thesis is comparable with that of GPS. Therefore, the study of this data fusion method has certain effects, the positioning accuracy can be improved of the aircraft. It is a great significance for the aircraft to achieve autonomous navigation. © 2022, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Image matching

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An Improved Task Planning Method for Unmanned Swarms with Coupled Physical and Logical Constraints

An Improved Task Planning Method for Unmanned Swarms with Co...

引用

2024 IEEE International Conference on Unmanned systems, ICUS 2024

作者： Chen, Xiubin Zhang, Lei Xu, Fang Yao, Weiran School of Astronautics Harbin Institude of Technology Harbin China Wuhan 2nd Ship Design and Research Institute Wuhan China Marine Military Intelligence Innovation Institute CSSC Systems Engineering Research Institute Beijing China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing China

ISBN: (纸本)9798350384185

Traditional task allocation methods for unmanned swarm systems ignore the effects of actual paths, resulting in estimation accuracy *** paper formulates task planning problem by incorporating physical and logical constraints, and establishes an integrated framework of task allocation and path ***-based search method is used to address path planning with physical constraints.A genetic algorithm is employed to solve multi-traveling salesman allocation problem.A bounded suboptimal optimization, a data dictionary, and an island model are introduced to accelerate the convergence speed of the genetic *** experiments verify that compared to the decoupled task planning methods, the proposed method improves task execution efficiency and remains adaptability to various complex spatial maps. © 2024 IEEE.

关键词： Genetic algorithms

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Simulation and analysis of far-field single-photon response model in Geiger avalanche mode 7

Simulation and analysis of far-field single-photon response ...

引用

7th Global intelligent Industry Conference, GIIC 2024

作者： Ou, Hengchang Ma, Le Jiang, Peng Wang, Pengfei Lu, Jie Zhou, Xin Sun, Jianfeng National Key Laboratory of Laser Spatial Information Institute of Opto-Electronic Harbin Institute of Technology Heilongjiang Harbin150001 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China Beijing Institute of Remote Sensing Beijing100854 China 44th Research Institute China Electronics Technology Group Corporation Chongqing400060 China Research Center for Space Optical Engineering Harbin Institute of Technology Heilongjiang Harbin150001 China Zhengzhou Research Institute of Harbin Institute of Technology Zhengzhou Henan450046 China

ISBN: (纸本)9781510682986

Poisson distribution model is the basis of data analysis for GM-APD lidar, but it is only applicable to the mirror reflected target under ideal conditions, and cannot accurately describe the photon triggering process of actual GM-APD lidar detection. For the actual target with rough surface, the negative binomial distribution with M as the parameter can describe the photon distribution model more accurately. In order to solve this problem, this paper compares and analyzes Poisson distribution triggering model and the negative binomial distribution triggering model that conforms to the triggering situation of the echo signal of the target with rough surface, considering the differences in the triggering probability under different noise and signal levels. The results show that the trigger probability curve corresponding to the trigger model based on negative binomial distribution is lower in peak value, wider in bottom value and fatter overall than that of the trigger model based on Poisson distribution, and the difference between the two is more prominent under the conditions of low noise level and high signal level. This study has guiding significance for the signal extraction research based on different surface echoes. © 2024 SPIE.

关键词： Photons

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Distributed Cooperative Guidance of Multi-missile with Unreliable Communications

Distributed Cooperative Guidance of Multi-missile with Unrel...

引用

International Conference on Autonomous Unmanned systems, ICAUS 2021

作者： Ye, Pengpeng Wei, Jianing Lu, Yu Li, Feifei Lin, Tao Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China Beijing Electro-Mechanical Engineering Institute Beijing100074 China Department of Automation Shanghai Jiao Tong University Shanghai200240 China

ISBN: (纸本)9789811694912

The salvo attack of multi-missile is investigated, where the communication topology is randomly switching and unsustainably connected due to the unreliable links, and the probability of the packet loss is unavailable. Based on feedback linearization, a cooperative guidance protocol is developed in a fully distributed manner, in which gains can be designed incongruently for all missiles, and only the local topology information is essential. Multiple missiles disconnect with each other once the consensus of impact time is reached, and are guided to the target under the proportional navigation guidance (PNG) law individually. Sufficient conditions are established to guarantee the consensus of impact time. A simulation experiment is delivered to validate the effectiveness of the obtained results. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Feedback linearization

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An Optimized One-Stage Detector for Autonomous PV Defect Detection

An Optimized One-Stage Detector for Autonomous PV Defect Det...

引用

International Conference on Autonomous Unmanned systems, ICAUS 2021

作者： Huidi, Xiao Jiajia, Zhao Lihui, Wang Qiucheng, Shen Nongjie, Ma Key Laboratory of Micro-Inertial Instrument and Advanced Navigation Technology Ministry of Education School of Instrument Science and Engineering Southeast University Nanjing210096 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China School of Mechanical and Electronic Control Engineering Beijing Jiaotong University Beijing China

ISBN: (纸本)9789811694912

To realize the defect detection of Photovoltaic (PV) modules based on infrared images, a one-stage detector based on FPT and loss function optimization is proposed. Firstly, ResNet50 is selected as the backbone network for feature extraction, combining with the idea of migration learning to strengthen its feature extraction ability. Besides, replacing the traditional feature pyramid with FPT, using Transformer structure help realize the interaction of the same position between different pyramid layers as well as different positions of the same layer, improving the feature fusion capability of the model. Finally, to alleviate the problem of suppression of non-optimal predictions by NMS strategy, a bipartite graph matching algorithm based on loss function minimization is designed to enhance the learning of the distribution of ground truth targets by the network. The dataset is expanded by Mosaic data enhancement method for model training, so as to achieve infrared image-based PV defect detection. Results show that the improved one-stage target detection network has a promising detection effect on PV module defects under infrared images, with the average accuracy improving by 2.20% compared with the original algorithm. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Defects

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Multi-Source Dynamic Time Series Data Processing Method Based on Comprehensive Weighted Fusion 12

Multi-Source Dynamic Time Series Data Processing Method Base...

引用

12th International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering, QR2MSE 2022

作者： Geng, Huapin Yuan, Feimeng Suo, Bin Science and Technology on Complex System Control and Intelligent Agent Cooperative Laboratory Beijing China Beijing Electro-mechanical Engineering Institute Beijing China School of Mathematics Southwest Jiaotong University Chengdu China School of Information Engineering Southwest University of Science and Technology Mianyang China

ISBN: (纸本)9781839538360

Aiming at the fusion problem of multi-source heterogeneous dynamic data sources, based on the subjective and objective comprehensive weighting idea, an efficient multi-source dynamic data fusion algorithm is proposed. First, the outlier detection method based on linear regression model is used to preprocess the multi-source dynamic time series data. Then, determine the weight of the dynamic data. The prior weight of the data source is determined by the AHP method, cyclic scoring method, etc., and the posterior weight is determined according to the similarity between the time series data. Based on the Euclidean distance, a similarity measure between different data sources and a similarity measure between different dynamic data samples are constructed respectively. The former is used for the fusion of dynamic data standard deviation expectations, and the latter is used for the fusion of mean expectations. Finally, the comprehensive weight of each dynamic time series of each data source is obtained, and the comprehensive weighted fusion method is used to obtain the expected value and standard deviation of the dynamic response. The analysis of the calculation example shows that the proposed algorithm has higher computational efficiency than the method that treats dynamic data as several discrete static data. © 2022 IEEE.

关键词： Data fusion

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An Approach for Upper Limb Movement Intention Recognition Using EEG and sEMG Fusion based on the MCPSA-CIIM

An Approach for Upper Limb Movement Intention Recognition Us...

引用

WRC Symposium on Advanced Robotics and Automation (WRC SARA)

作者： Weiming Zhang Xiaodong Zhang Cheng Xu Guchuan Zhou Teng Zhang Yu Wang Shaanxi Key Laboratory of Intelligent Robot School of Mechanical Engineering Xi’an Jiaotong University Xi’an Shaanxi China Science and Technology on Complex System Control and Intelligent Agent Cooperative Laboratory Beijing China

The upper limb motion intention recognition method based on electroencephalography (EEG) and surface electromyography (sEMG) fusion has achieved significant results in fields such as prosthetic control. However, most existing fusion methods use manual means to select features, which cannot capture temporal and spatial features at different scales, and ignore the correlation features between the two types of signals. To address these issues, this article proposes a fusion recognition method for upper limb motion intention EEG and sEMG based on Multi-scale Convolution, Polarized Self-Attention, and Cross Intelligence Integration Module. This article extracts multidimensional temporal and spatial features of EEG and sEMG through multi-scale convolution, and introduce polarized self-attention mechanism to filter the extracted multi-scale features. Simultaneously using cross enhancement strategy to extract correlation features between EEG and sEMG. Finally, the features are input into the classification network for recognition. This method was validated on the Jeong database, and the results showed that compared with CNN-LSTM and EEGNet, the recognition accuracy of this method increased by 2.63% and 3.15%, respectively.

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Scalable Distributed Organizational Structure and Self-Organization Mechanisms for Unmanned system Cluster 9

Scalable Distributed Organizational Structure and Self-Organ...

引用

9th IEEE International Conference on Computer science and Network technology, ICCSNT 2021

作者： Liu, Haibo Lin, Yang Shen, Jing Wang, Xing Shi, Changting Zhang, Jiayu College of Computer Science And Technology Harbin Engineering University Harbin150001 China Science And Technology On Complex System Control Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (纸本)9781665443647

Reasonable control organizational structure can help an unmanned system cluster cooperate more effectively to complete tasks. Previous research of existing organizational structures has problems implementing the task in a natural environment, such as the cluster's lack of scalability. This paper proposes a three-layer scalable distributed organizational structure and dynamic self-organization mechanisms, which overcomes the lack of scalability and ensures that the cluster can still perform stably after the cluster size changes. The simulation results show that the organizational structure realizes information sharing and cross-layer control, which enhance the flexibility and stability of unmanned system clusters. Comparison results show that our achievements can make a good performance, contributing to this area of future research. © 2021 IEEE.

关键词： Scalability

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Distributed Multi-Sensor Multi-View Fusion of PHD Filter for Maneuvering Targets

Distributed Multi-Sensor Multi-View Fusion of PHD Filter for...

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2021 CIE International Conference on Radar, Radar 2021

作者： Peng, Cong Chai, Lei Yi, Wei Chen, Linxiu School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9781665498142

This paper addresses the problem of maneuvering multi-target tracking by a network of sensors having different and limited fields of view (FoV s). Each local sensor runs the Gaussian Mixture Probability Hypothetical Density (GMPHD) filter. Due to the target maneuver, based on a single motion model, severe tracking performance degradation can be observed. We propose to use multi-model (MM) method to realize the adaptation to motion characteristic so as to overcome maneuverability of targets. Then considering FoV s of sensors in the network are different and limited, the standard weighted arithmetic average (WAA) fusion is no longer applicable and leads to an underestimation of the target number. Therefore, we use state-dependent WAA (SD-WAA) fusion rule, which performs the WAA in a more robust way by calculating a set of state-related fusion weights. Numerical experiment is designed to demonstrate the efficacy of the proposed method. © 2021 IEEE.

关键词： fields of view gaussian mixture maneuvering multi-target tracking multi-model method probability hypothesis density filter state-dependent weighted arithmetic average

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