In this paper, we introduce the concept of “social activity” to describe individual behavior on social networks, acknowledging its potential impact on rumor propagation within complex networks. With this in mind, we develop a dynamic model of rumor propagation based on social behavior and analyze the influence of various parameters on the scale of rumors through static comparison. Using this model, we investigate an optimal solution that balances costs and benefits. Numerical simulations and comparative experiments demonstrate the practical value of these findings for strategies aimed at suppressing rumors.
{"title":"A Social Activity-Based Control Model for Rumor Propagation","authors":"Qingyi Zhu, Ziqi Fan, Chenquan Gan, Kefei Cheng, Yu Wu, Lu-Xing Yang","doi":"10.1115/1.4064200","DOIUrl":"https://doi.org/10.1115/1.4064200","url":null,"abstract":"\u0000 In this paper, we introduce the concept of “social activity” to describe individual behavior on social networks, acknowledging its potential impact on rumor propagation within complex networks. With this in mind, we develop a dynamic model of rumor propagation based on social behavior and analyze the influence of various parameters on the scale of rumors through static comparison. Using this model, we investigate an optimal solution that balances costs and benefits. Numerical simulations and comparative experiments demonstrate the practical value of these findings for strategies aimed at suppressing rumors.","PeriodicalId":506262,"journal":{"name":"Journal of Computational and Nonlinear Dynamics","volume":" 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139626830","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}
In this paper, a novel multiscale morphological filter, called multiscale enhanced cascaded difference filter (MECDF), is proposed for the fault detection of road heading bearings. Firstly, the cascaded morphological operators are established based on the cascade of the basic morphological operators with similar properties, and then the morphological difference operation is introduced to propose the cascaded difference operators. Subsequently, the enhanced cascaded difference operator (ECDO) is constructed through the convolution of cascaded difference operators. Moreover, since the scale range of structure element (SE) also determines the filtering performance of multiscale morphological filter, an improved multiscale analysis method is presented to select the optimal scale range. Finally, the bearing experimental signals are implemented to validate the effectiveness of MECDF. Experimental results testify that the scale range determined by the MECDF is better than other multiscale morphological filters. Meanwhile, the feature extraction capability of ECDO is also better than other existing morphological difference operators.
{"title":"Fault Diagnosis for Road Heading Bearings Based On a Multiscale Enhanced Cascaded Difference Filter","authors":"Xiaofei Qu, Yongkang Zhang, Li Yin","doi":"10.1115/1.4064407","DOIUrl":"https://doi.org/10.1115/1.4064407","url":null,"abstract":"\u0000 In this paper, a novel multiscale morphological filter, called multiscale enhanced cascaded difference filter (MECDF), is proposed for the fault detection of road heading bearings. Firstly, the cascaded morphological operators are established based on the cascade of the basic morphological operators with similar properties, and then the morphological difference operation is introduced to propose the cascaded difference operators. Subsequently, the enhanced cascaded difference operator (ECDO) is constructed through the convolution of cascaded difference operators. Moreover, since the scale range of structure element (SE) also determines the filtering performance of multiscale morphological filter, an improved multiscale analysis method is presented to select the optimal scale range. Finally, the bearing experimental signals are implemented to validate the effectiveness of MECDF. Experimental results testify that the scale range determined by the MECDF is better than other multiscale morphological filters. Meanwhile, the feature extraction capability of ECDO is also better than other existing morphological difference operators.","PeriodicalId":506262,"journal":{"name":"Journal of Computational and Nonlinear Dynamics","volume":"7 4","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139380809","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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