Pub Date : 2022-10-13DOI: 10.1109/PHM-Yantai55411.2022.9941942
Zhichang Huang, Shi Yuan Tang
In order to better meet the requirements of node deployment method, a node deployment method of edge computing based on improved particle swarm optimization algorithm is proposed. Based on the improved particle swarm optimization algorithm, the node distribution model of edge computing is constructed, and the node distribution structure is optimized. The node distribution algorithm of edge computing is designed, which simplifies the deployment process of edge computing nodes. The experiment proves that the node deployment method of edge computing based on improved particle swarm optimization algorithm has high practicability and fully meets the research requirements.
{"title":"Edge Computing Node Robust Deployment Method Based on Improved Particle Swarm Algorithm","authors":"Zhichang Huang, Shi Yuan Tang","doi":"10.1109/PHM-Yantai55411.2022.9941942","DOIUrl":"https://doi.org/10.1109/PHM-Yantai55411.2022.9941942","url":null,"abstract":"In order to better meet the requirements of node deployment method, a node deployment method of edge computing based on improved particle swarm optimization algorithm is proposed. Based on the improved particle swarm optimization algorithm, the node distribution model of edge computing is constructed, and the node distribution structure is optimized. The node distribution algorithm of edge computing is designed, which simplifies the deployment process of edge computing nodes. The experiment proves that the node deployment method of edge computing based on improved particle swarm optimization algorithm has high practicability and fully meets the research requirements.","PeriodicalId":315994,"journal":{"name":"2022 Global Reliability and Prognostics and Health Management (PHM-Yantai)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121976635","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-13DOI: 10.1109/PHM-Yantai55411.2022.9942085
Yuan Zhao, Yunxue Liu, Zhuoran Cai
Realizing highly accurate and noncontact heart rate estimation with frequency modulated continuous wave (FMCW) radar is a big challenge under the interference of background noise and respiration harmonics. In this paper, various methods are employed to eliminate the interference, including impulse noise removal, improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) algorithm, peak-to-valley amplitude difference processing and peak-to-peak time interval processing. A novel heart rate estimation scheme that can efficiently suppress noise, interference and respiration signal for vital sign detection is proposed. After preprocessing the radar raw data, the scheme first removes the impulse noise of the vital signal. Then, the ICEEMDAN algorithm is used for further denoising, and the appropriate component is selected from the decomposition results to reconstruct the heartbeat signal. The heart rate is estimated in time domain and frequency domain, respectively. In the time domain, peak-to-valley amplitude difference and peak-to-peak time interval are used to eliminate noise and interference. In the frequency domain, fast Fourier transform (FFT) and Rife algorithms are applied to improve the estimation accuracy of the heart rate. Finally, the estimated data in the time and frequency domains are fused as the estimated heart rate of the scheme. Extensive experiments reveal that, compared with other methods, the root mean square error (RMSE) and mean absolute percentage error (MAPE) are greatly improved and the estimation accuracy of the heart rate is significantly enhanced by using the proposed scheme.
{"title":"A Novel Scheme for Vital Sign Detection with FMCW Radar","authors":"Yuan Zhao, Yunxue Liu, Zhuoran Cai","doi":"10.1109/PHM-Yantai55411.2022.9942085","DOIUrl":"https://doi.org/10.1109/PHM-Yantai55411.2022.9942085","url":null,"abstract":"Realizing highly accurate and noncontact heart rate estimation with frequency modulated continuous wave (FMCW) radar is a big challenge under the interference of background noise and respiration harmonics. In this paper, various methods are employed to eliminate the interference, including impulse noise removal, improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN) algorithm, peak-to-valley amplitude difference processing and peak-to-peak time interval processing. A novel heart rate estimation scheme that can efficiently suppress noise, interference and respiration signal for vital sign detection is proposed. After preprocessing the radar raw data, the scheme first removes the impulse noise of the vital signal. Then, the ICEEMDAN algorithm is used for further denoising, and the appropriate component is selected from the decomposition results to reconstruct the heartbeat signal. The heart rate is estimated in time domain and frequency domain, respectively. In the time domain, peak-to-valley amplitude difference and peak-to-peak time interval are used to eliminate noise and interference. In the frequency domain, fast Fourier transform (FFT) and Rife algorithms are applied to improve the estimation accuracy of the heart rate. Finally, the estimated data in the time and frequency domains are fused as the estimated heart rate of the scheme. Extensive experiments reveal that, compared with other methods, the root mean square error (RMSE) and mean absolute percentage error (MAPE) are greatly improved and the estimation accuracy of the heart rate is significantly enhanced by using the proposed scheme.","PeriodicalId":315994,"journal":{"name":"2022 Global Reliability and Prognostics and Health Management (PHM-Yantai)","volume":"118 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122469922","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-13DOI: 10.1109/PHM-Yantai55411.2022.9942144
Fanhao Zhou, Kun Yang, Dayang Li, Huimin Gao, Xinfa Shi
Turbine oil is very easy to generate a large number of air bubbles in the process of operation. Air bubbles not only have a great impact on the quality of oil and the operation of machinery, but also have a great impact on the reliability of oil online monitoring, resulting in monitoring data errors. Therefore, it is necessary to analyze the influence of air bubbles in the oil on the monitoring parameters. In this study, the dielectric constant sensor, particle contamination sensor, particle number sensor and viscosity sensor were used to study the changing law of the influence of bubbles on various characteristic parameters of oil, and make a qualitative analysis. And under the experimental conditions, the influence of temperature on the physical and chemical indicators was excluded by the temperature control method. The experimental results show that the number of air bubbles will affect the oil, and the more air bubbles, the worse the performance of the oil.
{"title":"Research on Influence of Turbine Oil Bubbles on Oil Condition Monitoring","authors":"Fanhao Zhou, Kun Yang, Dayang Li, Huimin Gao, Xinfa Shi","doi":"10.1109/PHM-Yantai55411.2022.9942144","DOIUrl":"https://doi.org/10.1109/PHM-Yantai55411.2022.9942144","url":null,"abstract":"Turbine oil is very easy to generate a large number of air bubbles in the process of operation. Air bubbles not only have a great impact on the quality of oil and the operation of machinery, but also have a great impact on the reliability of oil online monitoring, resulting in monitoring data errors. Therefore, it is necessary to analyze the influence of air bubbles in the oil on the monitoring parameters. In this study, the dielectric constant sensor, particle contamination sensor, particle number sensor and viscosity sensor were used to study the changing law of the influence of bubbles on various characteristic parameters of oil, and make a qualitative analysis. And under the experimental conditions, the influence of temperature on the physical and chemical indicators was excluded by the temperature control method. The experimental results show that the number of air bubbles will affect the oil, and the more air bubbles, the worse the performance of the oil.","PeriodicalId":315994,"journal":{"name":"2022 Global Reliability and Prognostics and Health Management (PHM-Yantai)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121268605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With China’s exploration of the sea, unmanned boats on the water are receiving more and more attention. Due to the complex situation on the water, unmanned boat obstacle avoidance still has defects. To address the above problems, this paper designs unmanned fish-finding and obstacle avoidance based on Pixhawk. The Kalman filter algorithm is used for sensor information fusion, which realizes the state estimation of the fish-finding unmanned ship. The BUG2 obstacle avoidance algorithm is used for obstacle avoidance, that optimizes the automatic obstacle avoidance function of the fish-finding unmanned ship. The fish finder is used to detect the position information of the fish, that realizes the function of the fish-finding unmanned ship tracking the fish. The PID control algorithm is used to control the driving of the ship, which makes the fish-finding unmanned ship converge to the desired course quickly and accurately. The lateral error of the vessel is within 1m. The simulation results verify the feasibility of the system, and the sea trial experiments of the unmanned fish-finding vessel prove the reliability and stability of the system.
{"title":"Design of Unmanned System for Fish-finding and Obstacle Avoidance Based on Pixhawk","authors":"Zhikuan Chen, Zhengxing Wang, Lan Xia, Zhiquan Zhou, Qinghua Luo, Zhenbin Lv","doi":"10.1109/PHM-Yantai55411.2022.9941991","DOIUrl":"https://doi.org/10.1109/PHM-Yantai55411.2022.9941991","url":null,"abstract":"With China’s exploration of the sea, unmanned boats on the water are receiving more and more attention. Due to the complex situation on the water, unmanned boat obstacle avoidance still has defects. To address the above problems, this paper designs unmanned fish-finding and obstacle avoidance based on Pixhawk. The Kalman filter algorithm is used for sensor information fusion, which realizes the state estimation of the fish-finding unmanned ship. The BUG2 obstacle avoidance algorithm is used for obstacle avoidance, that optimizes the automatic obstacle avoidance function of the fish-finding unmanned ship. The fish finder is used to detect the position information of the fish, that realizes the function of the fish-finding unmanned ship tracking the fish. The PID control algorithm is used to control the driving of the ship, which makes the fish-finding unmanned ship converge to the desired course quickly and accurately. The lateral error of the vessel is within 1m. The simulation results verify the feasibility of the system, and the sea trial experiments of the unmanned fish-finding vessel prove the reliability and stability of the system.","PeriodicalId":315994,"journal":{"name":"2022 Global Reliability and Prognostics and Health Management (PHM-Yantai)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122326891","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-13DOI: 10.1109/phm-yantai55411.2022.9941855
Zheng Lan, Liu Zihang, Ye Qunfeng
Through the fuzzy comprehensive evaluation method, the simplicity of maintenance is analyzed. The maintenance simplicity of the scheme can be effectively analyzed from five aspects: the simplicity of fault isolation and installation test, simplicity of the access for maintenance, the simplicity of assembly and disassembly equipment, the simplicity of support sources and maintenance frequency. The method used in this paper can effectively reflect the maintenance simplicity of different schemes via fuzzy comprehensive evaluation method for decision-making.
{"title":"Research on the maintenance simplicity of civil aircraft based on the fuzzy comprehensive evaluation","authors":"Zheng Lan, Liu Zihang, Ye Qunfeng","doi":"10.1109/phm-yantai55411.2022.9941855","DOIUrl":"https://doi.org/10.1109/phm-yantai55411.2022.9941855","url":null,"abstract":"Through the fuzzy comprehensive evaluation method, the simplicity of maintenance is analyzed. The maintenance simplicity of the scheme can be effectively analyzed from five aspects: the simplicity of fault isolation and installation test, simplicity of the access for maintenance, the simplicity of assembly and disassembly equipment, the simplicity of support sources and maintenance frequency. The method used in this paper can effectively reflect the maintenance simplicity of different schemes via fuzzy comprehensive evaluation method for decision-making.","PeriodicalId":315994,"journal":{"name":"2022 Global Reliability and Prognostics and Health Management (PHM-Yantai)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125512234","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-13DOI: 10.1109/PHM-Yantai55411.2022.9941998
Yong Zhang, Erqing Ren, Gang Li
Aiming at the resource allocation of ecological network courses in higher education, the corresponding allocation framework is constructed based on fuzzy particle swarm optimization. Because of the slow convergence speed of particle swarm optimization algorithm in the later stage, it is easy to converge in local optimization. Therefore, combined with the characteristics of resource allocation problem, particle swarm optimization algorithm is improved. The resource allocation model of ecological network courses in higher education is solved by using fuzzy particle swarm optimization algorithm under the constraints, and the resource allocation scheme is obtained. The results show that compared with the manual allocation scheme, the higher education ecological network curriculum resource allocation scheme obtained by the research algorithm has higher curriculum resource utilization efficiency and resource allocation efficiency, indicating the effectiveness of the research algorithm.
{"title":"Resource Security Allocation Algorithm of Ecological Network Curriculum in Higher Education Based on Fuzzy Particle Swarm Optimization","authors":"Yong Zhang, Erqing Ren, Gang Li","doi":"10.1109/PHM-Yantai55411.2022.9941998","DOIUrl":"https://doi.org/10.1109/PHM-Yantai55411.2022.9941998","url":null,"abstract":"Aiming at the resource allocation of ecological network courses in higher education, the corresponding allocation framework is constructed based on fuzzy particle swarm optimization. Because of the slow convergence speed of particle swarm optimization algorithm in the later stage, it is easy to converge in local optimization. Therefore, combined with the characteristics of resource allocation problem, particle swarm optimization algorithm is improved. The resource allocation model of ecological network courses in higher education is solved by using fuzzy particle swarm optimization algorithm under the constraints, and the resource allocation scheme is obtained. The results show that compared with the manual allocation scheme, the higher education ecological network curriculum resource allocation scheme obtained by the research algorithm has higher curriculum resource utilization efficiency and resource allocation efficiency, indicating the effectiveness of the research algorithm.","PeriodicalId":315994,"journal":{"name":"2022 Global Reliability and Prognostics and Health Management (PHM-Yantai)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124238940","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-13DOI: 10.1109/PHM-Yantai55411.2022.9941919
Chunmei Zhao, Jun Liu
Aiming at the problem that it is easy to fall into local minimum in the multi domain resource allocation process of wireless communication in the Internet of things, a multi domain resource allocation algorithm of wireless communication in the Internet of things based on chaotic neural network is proposed. The effects of attenuation factor and temperature fading parameters on the chaotic characteristics of chaotic neural network are analyzed, and the network parameters are selected reasonably. This paper obtains the multi domain resources of integrated Internet of things wireless communication, updates the multi domain resources, and builds a multi domain resource configuration model through relevant network parameters. In this paper, we use data mining method to obtain the multi domain resource data of wireless communication. And the parameters of the network are appropriately selected to make the neural network appear chaotic, so the resource allocation process based on the chaotic neural network is designed. Therefore, the resource allocation process based on chaotic neural network is designed. The experimental results show that the configuration results of the algorithm are consistent with the ideal configuration results, and the shortest end-to-end delay is 10 ms, and the lowest packet loss rate is 4%.
{"title":"Multi Domain Resource Accurate Allocation Algorithm for Wireless Communication of Internet of Things Based on Chaotic Neural Network","authors":"Chunmei Zhao, Jun Liu","doi":"10.1109/PHM-Yantai55411.2022.9941919","DOIUrl":"https://doi.org/10.1109/PHM-Yantai55411.2022.9941919","url":null,"abstract":"Aiming at the problem that it is easy to fall into local minimum in the multi domain resource allocation process of wireless communication in the Internet of things, a multi domain resource allocation algorithm of wireless communication in the Internet of things based on chaotic neural network is proposed. The effects of attenuation factor and temperature fading parameters on the chaotic characteristics of chaotic neural network are analyzed, and the network parameters are selected reasonably. This paper obtains the multi domain resources of integrated Internet of things wireless communication, updates the multi domain resources, and builds a multi domain resource configuration model through relevant network parameters. In this paper, we use data mining method to obtain the multi domain resource data of wireless communication. And the parameters of the network are appropriately selected to make the neural network appear chaotic, so the resource allocation process based on the chaotic neural network is designed. Therefore, the resource allocation process based on chaotic neural network is designed. The experimental results show that the configuration results of the algorithm are consistent with the ideal configuration results, and the shortest end-to-end delay is 10 ms, and the lowest packet loss rate is 4%.","PeriodicalId":315994,"journal":{"name":"2022 Global Reliability and Prognostics and Health Management (PHM-Yantai)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128796313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-13DOI: 10.1109/PHM-Yantai55411.2022.9942042
Anqi Shan, Zengqiang Jiang, M. E, Qi Li
Refined maintenance decisions and health management of products is an important research direction in reliability. This study proposes a differentiation maintenance method considering individual random effects in the degradation process under periodic inspection. First, the slowly degradation products are divided into several groups according to the individual degradation differences, and the degradation models are established respectively. On this basis, a reasonable state space and maintenance decision space are constructed, the state transfer probability of the degradation process is solved. The optimal differential maintenance strategy is solved by strategy iteration under the framework of semi-Markov decision process model to minimize the unit expected cost. The GaAs taser degradation case is used as a validation and compared with the repair strategy with a fixed replacement threshold, and it is demonstrated that the proposed grouped repair strategy can reduce the cost. In addition, the effectiveness of the proposed method for newly put-in-use individuals is also verified by simulating new individual extrapolation.
{"title":"A Grouped Semi-Markov Maintenance Strategy Considering Random Effects","authors":"Anqi Shan, Zengqiang Jiang, M. E, Qi Li","doi":"10.1109/PHM-Yantai55411.2022.9942042","DOIUrl":"https://doi.org/10.1109/PHM-Yantai55411.2022.9942042","url":null,"abstract":"Refined maintenance decisions and health management of products is an important research direction in reliability. This study proposes a differentiation maintenance method considering individual random effects in the degradation process under periodic inspection. First, the slowly degradation products are divided into several groups according to the individual degradation differences, and the degradation models are established respectively. On this basis, a reasonable state space and maintenance decision space are constructed, the state transfer probability of the degradation process is solved. The optimal differential maintenance strategy is solved by strategy iteration under the framework of semi-Markov decision process model to minimize the unit expected cost. The GaAs taser degradation case is used as a validation and compared with the repair strategy with a fixed replacement threshold, and it is demonstrated that the proposed grouped repair strategy can reduce the cost. In addition, the effectiveness of the proposed method for newly put-in-use individuals is also verified by simulating new individual extrapolation.","PeriodicalId":315994,"journal":{"name":"2022 Global Reliability and Prognostics and Health Management (PHM-Yantai)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129074688","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-13DOI: 10.1109/PHM-Yantai55411.2022.9941848
Keqiang Xu, Y. Xiong
In order to improve the practical application effect of the mixed teaching mode, an application effect evaluation algorithm of online and offline hybrid teaching mode in undergraduate colleges is proposed. Firstly, the big data technology is used to collect the big data in the online and offline mixed teaching process of undergraduate colleges, and an evaluation index system is built from three dimensions to extract the required data according to the indicators. Then the association rules between the relevant data of the evaluation indicators are established to obtain the phase space distribution of the data. Finally, the constraint parameter analysis method is used to fuse the control variables and explanatory variables of the index related data to realize the online and offline mixed teaching effect evaluation. The experimental results show that the proposed algorithm achieves an ideal evaluation result of online and offline mixed teaching effect, which is conducive to improving the teaching quality.
{"title":"Application Effect Robust Evaluation Algorithm of Online and Offline Hybrid Teaching Mode in Undergraduate Colleges","authors":"Keqiang Xu, Y. Xiong","doi":"10.1109/PHM-Yantai55411.2022.9941848","DOIUrl":"https://doi.org/10.1109/PHM-Yantai55411.2022.9941848","url":null,"abstract":"In order to improve the practical application effect of the mixed teaching mode, an application effect evaluation algorithm of online and offline hybrid teaching mode in undergraduate colleges is proposed. Firstly, the big data technology is used to collect the big data in the online and offline mixed teaching process of undergraduate colleges, and an evaluation index system is built from three dimensions to extract the required data according to the indicators. Then the association rules between the relevant data of the evaluation indicators are established to obtain the phase space distribution of the data. Finally, the constraint parameter analysis method is used to fuse the control variables and explanatory variables of the index related data to realize the online and offline mixed teaching effect evaluation. The experimental results show that the proposed algorithm achieves an ideal evaluation result of online and offline mixed teaching effect, which is conducive to improving the teaching quality.","PeriodicalId":315994,"journal":{"name":"2022 Global Reliability and Prognostics and Health Management (PHM-Yantai)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130644605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-13DOI: 10.1109/PHM-Yantai55411.2022.9942182
Sisi Wan
In order to solve the challenge that are caused by the traditional k-means algorithm such as local optimal solution, initial value selection with randomness, sensitivity to outlier. An improved K-means clustering algorithm based on density radius was proposed. First, remove the outliers in the dataset according to the Local outlier factor (lof). Then calculate the sample point density within the sample point density radius, and the initial cluster center and k value are selected and determined according to the density. After that according to the traditional K-means thoughts to cluster and get new clusters center. Finally, a k-value optimization strategy based on Bayesian Information Criterion (BIC) score is proposed to optimize the k-value and effectively improve the clustering quality. The theoretical analysis and simulation results show that the improved algorithm improves accuracy.
{"title":"An Improved k-means Algorithm based on BIC Score and Density Radius","authors":"Sisi Wan","doi":"10.1109/PHM-Yantai55411.2022.9942182","DOIUrl":"https://doi.org/10.1109/PHM-Yantai55411.2022.9942182","url":null,"abstract":"In order to solve the challenge that are caused by the traditional k-means algorithm such as local optimal solution, initial value selection with randomness, sensitivity to outlier. An improved K-means clustering algorithm based on density radius was proposed. First, remove the outliers in the dataset according to the Local outlier factor (lof). Then calculate the sample point density within the sample point density radius, and the initial cluster center and k value are selected and determined according to the density. After that according to the traditional K-means thoughts to cluster and get new clusters center. Finally, a k-value optimization strategy based on Bayesian Information Criterion (BIC) score is proposed to optimize the k-value and effectively improve the clustering quality. The theoretical analysis and simulation results show that the improved algorithm improves accuracy.","PeriodicalId":315994,"journal":{"name":"2022 Global Reliability and Prognostics and Health Management (PHM-Yantai)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130756056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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