Research on Construction of Mining Model of Association Rules for Temporal Data based on CNN

Gan, Xinyan; DaoQing, Gong; Gao, Xiang; Yun-fang, Zhang; Lin, Liuyun; Tianying, Lan

doi:10.1109/iceib53692.2021.9686436

Cited by 2 publications

(2 citation statements)

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“…PDA can track a single target very effectively, but it is easy to generate error tracking in the target dense environment. In this regard, a data association algorithm is proposed [23]. In order to express the complex relationship between effective echo and each target tracking gate, the concept of confirmation matrix [24] is proposed and defined:…”

Section: Tracking and Measurement Model Of Infrared Weak Andmentioning

confidence: 99%

Correlation Filtering Algorithm of Infrared Spectral Data for Dim Target Tracking

Zheng

Chang

Wang

et al. 2023

Advances in Mathematical Physics

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The correlation filtering algorithm of infrared spectral data for dim and small target tracking is studied to improve the tracking accuracy of small and weak targets and to track small and weak targets in real time. After the image noise reduction processing by the mean shift filtering algorithm, the infrared small and weak target image data model is constructed by using the denoised infrared small and weak target image. And the brightness value and position of unknown small and weak targets are obtained. The tracking and measurement model of small and weak targets is built. The joint probabilistic data association algorithm is used to calculate the probability that each measurement is associated with its possible source targets, and the particle filter is used to update the tracking status of small and weak targets to achieve real-time tracking of small and weak targets. The experimental results show that the algorithm can enhance the edge contour information of small and weak images, so as to accurately track small and weak targets moving in any track, and has good real-time tracking and accuracy. There is a small deviation between the tracking track of weak and small targets tracked by the algorithm and the actual track, and the root mean square difference of tracking weak and small targets is within 2 pixels. In addition, the detection probability of detecting weak and small targets is less affected by SNR environmental factors.

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Section: Tracking and Measurement Model Of Infrared Weak Andmentioning

confidence: 99%

Correlation Filtering Algorithm of Infrared Spectral Data for Dim Target Tracking

Zheng

Chang

Wang

et al. 2023

Advances in Mathematical Physics

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“…Arani et al [5] also used a metaheuristic-based clustering mechanism when analyzing cloud workloads. In addition, Gan et al [6] combined the design of convolutional neural networks (CNN) to address the shortcomings of traditional mining models that cannot extract temporal data effectively by constructing a new temporal association rule mining model. Similar papers include [7,8].…”

Section: Introductionmentioning

confidence: 99%

A Survey on Particle Swarm Optimization for Association Rule Mining

Wang

Chen

et al. 2022

Electronics

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Association rule mining (ARM) is one of the core techniques of data mining to discover potentially valuable association relationships from mixed datasets. In the current research, various heuristic algorithms have been introduced into ARM to address the high computation time of traditional ARM. Although a more detailed review of the heuristic algorithms based on ARM is available, this paper differs from the existing reviews in that we expected it to provide a more comprehensive and multi-faceted survey of emerging research, which could provide a reference for researchers in the field to help them understand the state-of-the-art PSO-based ARM algorithms. In this paper, we review the existing research results. Heuristic algorithms for ARM were divided into three main groups, including biologically inspired, physically inspired, and other algorithms. Additionally, different types of ARM and their evaluation metrics are described in this paper, and the current status of the improvement in PSO algorithms is discussed in stages, including swarm initialization, algorithm parameter optimization, optimal particle update, and velocity and position updates. Furthermore, we discuss the applications of PSO-based ARM algorithms and propose further research directions by exploring the existing problems.

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Research on Construction of Mining Model of Association Rules for Temporal Data based on CNN

Cited by 2 publications

References 0 publications

Correlation Filtering Algorithm of Infrared Spectral Data for Dim Target Tracking

Correlation Filtering Algorithm of Infrared Spectral Data for Dim Target Tracking

A Survey on Particle Swarm Optimization for Association Rule Mining

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