Clustering of Copper Flotation Process Based on the AP-GMM Algorithm

Wang, Zhiqiang; He, Dakuo; Li, Bo

doi:10.1109/access.2019.2951444

Cited by 6 publications

(3 citation statements)

References 34 publications

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“…As can be seen from the data in the table, the proportion of action A1 is erroneously identified as B6 (conveying stapler) and B7 (conveying beverage). This is because the average recognition rate of the three actions is only 37.8% [22]. These three actions are similar to the human skeleton coordinate space.…”

Section: A Analysis Of Action Instance Recognition Resultsmentioning

confidence: 96%

Retracted: Aided Image Acquisition System for Aerobics Training Based on Motion Recognition Technology

Hai-ying

Liu

2024

IEEE Access

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The image acquisition system is the main part of acquiring image information, and its performance largely determines the accuracy and difficulty of subsequent planning. The main purpose of this article is to design an image acquisition system for aerobics training based on motion recognition technology. This article mainly introduces the teaching experiments based on the design of aerobics courses. Through the empirical investigation and analysis of the impact of relevant experimental data on aviation training courses, attempts to establish the connection between aerobics social adaptability and various dimensions The cultivation of student' s social adaptability. In this paper, the GMM algorithm is mainly used to distinguish the rest time when the action occurs, and the subsequent rest period is used as the basis for segmenting multiple events in the action sequence. Finally, the characteristics of the action coding mapping of each event are derived, and the support vector machine is used to complete the energy recognition process of the existence of a single energy. The experimental results of this paper show that the designed embedded image acquisition system has high integration and stability, the acquired image resolution is 640x480, and the wireless transmission rate is 5MbPs, which has wide application prospects.

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Section: A Analysis Of Action Instance Recognition Resultsmentioning

confidence: 96%

Retracted: Aided Image Acquisition System for Aerobics Training Based on Motion Recognition Technology

Hai-ying

Liu

2024

IEEE Access

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“…The surface oxidation level was investigated in [19]. Furthermore, various attempts in the modeling of the whole process or parts of it, introducing different types of algorithms, were presented in many papers [20][21][22][23][24][25][26]. We have also conducted many studies on copper ore processing and its optimization.…”

Section: Introductionmentioning

confidence: 99%

Multidimensional Optimization of the Copper Flotation in a Jameson Cell by Means of Taxonomic Methods

et al. 2021

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Three factors were measured in the flotation process of copper ore: the copper grade in a concentrate (β), the copper grade in tailings (ϑ), and the recovery of copper in a concentrate (ε). The experiment was conducted by means of a Jameson cell. The factors influencing the quality of the process were the particle size (d), the flotation time (t), the type of collector (k), and the dosage of the collector (s). The considered vector function is then (β(d, t, k, s), ϑ(d, t, k, s), ε(d, t, k, s)). In this work, the optimization was based on determining the values of the adjustable factors (d, t, k, s). The goal was to obtain the possibly highest values of the functions β and ε (maximum) with the possibly lowest values of the function ϑ (minimum). To this end, taxonomic methods were applied. Thanks to the applied method, the optimum—with the adopted assumptions—was found. The presented methodology can be successfully applied in the search for the optima in a variety of technological processes.

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“…After determining all the cluster centers, assign the remaining data points to the corresponding cluster centers. Where α is the damping coefficient, the value is [0.5, 1]; generally 0.9, t is the number of iterations, and the maximum value is set to 500 [38,39]. Section 3.1.2 shows the pseudocode for clustering RSSI values using the AP clustering algorithm.…”

mentioning

confidence: 99%

RFID Indoor Positioning Based on AP Clustering and Improved Particle Swarm Algorithm

Zhang

et al. 2022

Journal of Sensors

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This paper proposes a method based on AP clustering and an improved particle swarm algorithm for radio frequency identification (RFID) indoor positioning, called the AP-PSO method. Firstly, an AP clustering algorithm is used to cluster the RSSI values of the experimental region tags with similarity, in order to achieve the division of tagged regions, reduce the search area of the later improved particle swarm algorithm, and reduce the search time. Secondly, the learning factor of the particle swarm algorithm is dynamically adjusted, in order to improve the search ability and convergence speed of the global optimal solution of particles. The experimental results show that the algorithm can effectively achieve RFID indoor positioning of the tags to be measured, with high positioning accuracy and with the algorithm spending less time.

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Clustering of Copper Flotation Process Based on the AP-GMM Algorithm

Cited by 6 publications

References 34 publications

Retracted: Aided Image Acquisition System for Aerobics Training Based on Motion Recognition Technology

Retracted: Aided Image Acquisition System for Aerobics Training Based on Motion Recognition Technology

Multidimensional Optimization of the Copper Flotation in a Jameson Cell by Means of Taxonomic Methods

RFID Indoor Positioning Based on AP Clustering and Improved Particle Swarm Algorithm

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