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The node deployment of wireless sensor networks based on mobile edge computing 基于移动边缘计算的无线传感器网络节点部署
Web Intell. Pub Date : 2022-06-27 DOI: 10.3233/web-220017
Fangrong Zhou, Hemeng Yang, Yi Ma, Yanfang Chen, G. Wen, Yansheng Cheng
{"title":"The node deployment of wireless sensor networks based on mobile edge computing","authors":"Fangrong Zhou, Hemeng Yang, Yi Ma, Yanfang Chen, G. Wen, Yansheng Cheng","doi":"10.3233/web-220017","DOIUrl":"https://doi.org/10.3233/web-220017","url":null,"abstract":"When deploying network nodes, there are many redundant nodes, low network coverage and high energy consumption of network nodes, the node deployment method of wireless sensor networks(WSN) based on mobile edge computing is studied. WSN nodes are divided into anchor nodes and unknown nodes. Taking the location information of anchor nodes as a reference, the specific location of unknown nodes is obtained by trilateral measurement. Minimizing the node distance error is taken as the objective function, and the cuckoo search algorithm is used to solve it to obtain the final location result of the node. The mobile edge computing method is used to design the node deployment method of WSN to complete the node deployment. Simulation results show that the number of redundant nodes in this method is 3, maximum network coverage is 89%, maximum energy consumption of network nodes is 34.3J.","PeriodicalId":245783,"journal":{"name":"Web Intell.","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123145661","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}
引用次数: 0
Privacy protection data mining algorithm in blockchain based on decision tree classification 基于决策树分类的区块链隐私保护数据挖掘算法
Web Intell. Pub Date : 2022-06-09 DOI: 10.3233/web-210485
Yu Cao, Wei Wei, Jingcheng Zhou
{"title":"Privacy protection data mining algorithm in blockchain based on decision tree classification","authors":"Yu Cao, Wei Wei, Jingcheng Zhou","doi":"10.3233/web-210485","DOIUrl":"https://doi.org/10.3233/web-210485","url":null,"abstract":"Aiming at the problems of low mining accuracy and high privacy protection data noise in privacy protection data mining methods in blockchain, a privacy protection data mining algorithm in blockchain based on decision tree classification is proposed. Extract the privacy protection data in the blockchain, calculate and update the distance between the data in the data set to be denoised, and denoise the updated data. Finally, starting from the root of the decision tree, calculate the information gain value of this part of privacy protection data, determine the attribute probability of privacy protection data, and complete the in-depth mining of privacy protection data in the blockchain through the calculation of decision leaf density value. The experimental results show that the mining accuracy of the proposed algorithm is always more than 90%, and the data noise is stable below 0.6 dB.","PeriodicalId":245783,"journal":{"name":"Web Intell.","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126564117","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}
引用次数: 1
Study on secure distribution of vehicle road collaborative data based on attribute-based encryption 基于属性加密的车辆道路协同数据安全分发研究
Web Intell. Pub Date : 2022-06-08 DOI: 10.3233/web-220015
Heniguli Wumaier, Jin Zhou, Jian Gao
{"title":"Study on secure distribution of vehicle road collaborative data based on attribute-based encryption","authors":"Heniguli Wumaier, Jin Zhou, Jian Gao","doi":"10.3233/web-220015","DOIUrl":"https://doi.org/10.3233/web-220015","url":null,"abstract":"In order to solve the problems of poor effect, low distribution accuracy and high average delay in traditional methods, a secure distribution method of vehicle road collaborative data based on attribute-based encryption is proposed. The attribute-based encryption algorithm is used to initialize the global and authorization center, and receive the vehicle road cooperation data to be distributed. The decision tree algorithm is used to classify the vehicle road collaboration data, and the corresponding index is established for the vehicle road collaboration data. The user private key is generated according to the data classification results, and the ciphertext is sent to the fog node to realize the safe distribution of vehicle road collaborative data. The experimental results show that the proposed method has a good effect on the secure distribution of vehicle road cooperative data, which can effectively improve the distribution accuracy and reduce the average distribution delay.","PeriodicalId":245783,"journal":{"name":"Web Intell.","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130389636","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}
引用次数: 0
Financial risk evaluation method of blockchain digital currency based on CART algorithm 基于CART算法的区块链数字货币财务风险评估方法
Web Intell. Pub Date : 2022-06-08 DOI: 10.3233/web-210489
Xiuling Fan, Haiyang Lv
{"title":"Financial risk evaluation method of blockchain digital currency based on CART algorithm","authors":"Xiuling Fan, Haiyang Lv","doi":"10.3233/web-210489","DOIUrl":"https://doi.org/10.3233/web-210489","url":null,"abstract":"In order to overcome the problems existing in traditional financial risk evaluation methods, such as high generalization error and fitting degree with actual value, this paper designs a financial risk evaluation method of blockchain digital currency based on CART algorithm. After screening and ranking the financial risk indicators of blockchain digital currency, the financial risk level of blockchain digital currency is determined by combining CART algorithm. Finally, by calculating the covariance matrix of the financial risk decision matrix, the positive ideal solution and the negative ideal solution of the financial risk are found, and then the final evaluation result is obtained by combining the progress of the financial risk. Experimental results show that the minimum generalization error of this method is only 0.021, the fitting degree of the obtained results and the actual risk can reach 98.0%, and the maximum risk accuracy can reach 0.978.","PeriodicalId":245783,"journal":{"name":"Web Intell.","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117148655","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}
引用次数: 0
Intelligent retrieval method of library document information based on hidden topic mining 基于隐藏主题挖掘的图书馆文献信息智能检索方法
Web Intell. Pub Date : 2022-06-07 DOI: 10.3233/web-210484
Yujie An, Yuwei Yan
{"title":"Intelligent retrieval method of library document information based on hidden topic mining","authors":"Yujie An, Yuwei Yan","doi":"10.3233/web-210484","DOIUrl":"https://doi.org/10.3233/web-210484","url":null,"abstract":"In order to overcome the problems of retrieval accuracy and time-consuming of traditional document information retrieval methods, this paper designs an intelligent retrieval method of library document information based on hidden topic mining. Firstly, LDA model is used to mine the hidden topics of library document information, and then, based on the mining results, similarity degree of document information is calculated in inference network model. Finally, the Bayesian model is constructed in the sample space to retrieve the library literature information under the maximum retrieval space coverage. Experimental results show that, compared with traditional retrieval methods, the proposed method improves the retrieval accuracy significantly, with the highest retrieval accuracy reaching 99%, and the retrieval time is significantly reduced, indicating that the proposed method effectively improves the retrieval accuracy and timeliness.","PeriodicalId":245783,"journal":{"name":"Web Intell.","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123485775","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}
引用次数: 0
A power information security partition storage method based on multidimensional data mining 基于多维数据挖掘的电力信息安全分区存储方法
Web Intell. Pub Date : 2022-06-07 DOI: 10.3233/web-210486
Ling Li, Yan Fang
{"title":"A power information security partition storage method based on multidimensional data mining","authors":"Ling Li, Yan Fang","doi":"10.3233/web-210486","DOIUrl":"https://doi.org/10.3233/web-210486","url":null,"abstract":"Aiming at the problems of low security coefficient and low storage efficiency of traditional methods, a power information security partition storage method based on multidimensional data mining is designed. Firstly, the relationship value between power information data is analyzed and determined, and the power information collection is completed with the help of covariance matrix. Then, the membership function of multidimensional power information data is calculated, and the noise reduction of multidimensional power information is completed by calculating Lagrange coefficient. Finally, the multidimensional information data is analyzed by two-dimensional correlation, the multidimensional power information data is layered, the partition structure is optimized, the data of the three regions after stratification are encrypted respectively, so as to complete the secure storage of power information data. Experimental results show that the security factor of power information security partition storage using this method is always higher than 0.9, and the storage efficiency is high.","PeriodicalId":245783,"journal":{"name":"Web Intell.","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115449836","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}
引用次数: 0
Secure retrieval method of network space data based on block chain technology 基于区块链技术的网络空间数据安全检索方法
Web Intell. Pub Date : 2022-06-07 DOI: 10.3233/web-210483
Yaping Gao, Huimin Wang
{"title":"Secure retrieval method of network space data based on block chain technology","authors":"Yaping Gao, Huimin Wang","doi":"10.3233/web-210483","DOIUrl":"https://doi.org/10.3233/web-210483","url":null,"abstract":"In order to solve the shortcomings of traditional methods in storage capacity, fault tolerance and time consuming, a secure data retrieval method based on block chain technology was proposed. Initialize the blockchain system, encrypt the cyberspace data through the public key, and upload the encrypted data by connecting the public key of the data aggregator. Complete the blockchain data consensus and verify the encrypted data through the aggregator workload calculation and cyberspace data verification. The blockchain data storage structure is constructed by combining the on-chain index table and the off-chain database. Decrypt the data retrieval instruction with the key, and then transfer the required data into the block chain data storage structure to achieve secure data retrieval in network space. Experimental results show that the proposed method has high storage capacity and fault tolerance, and the maximum running time is only 1.43 s.","PeriodicalId":245783,"journal":{"name":"Web Intell.","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121604159","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}
引用次数: 0
An automatic classification method of library archives data based on data mining 基于数据挖掘的图书馆档案数据自动分类方法
Web Intell. Pub Date : 2022-06-07 DOI: 10.3233/web-210487
Li-Shan Qiao
{"title":"An automatic classification method of library archives data based on data mining","authors":"Li-Shan Qiao","doi":"10.3233/web-210487","DOIUrl":"https://doi.org/10.3233/web-210487","url":null,"abstract":"Aiming at the problems of poor accuracy of data feature extraction and large classification error in library archives data classification methods, an automatic classification method of library archives data based on data mining is designed. Firstly, the linear relationship between the characteristic variables of library archives data is determined, and the linear coefficient of archives data characteristics is calculated; Then, the characteristic states of library archives data are divided into three states, the characteristic data are normalized, and the adaptive differential evolution algorithm is used to remove the noise in the characteristics of library archives data; Finally, the mapping relation training model in data mining is used to input the data feature training set, and the file data features are labeled according to different weights; Establish automatic data classification model. The experimental results show that the highest accuracy of this method is about 97%.","PeriodicalId":245783,"journal":{"name":"Web Intell.","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123410851","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}
引用次数: 0
A fast encryption method for enterprise financial data based on blockchain 一种基于区块链的企业财务数据快速加密方法
Web Intell. Pub Date : 2022-06-07 DOI: 10.3233/web-210488
L. Kong
{"title":"A fast encryption method for enterprise financial data based on blockchain","authors":"L. Kong","doi":"10.3233/web-210488","DOIUrl":"https://doi.org/10.3233/web-210488","url":null,"abstract":"Aiming at the problems of poor encryption security and long encryption time in the existing enterprise financial data encryption, a fast encryption method of enterprise financial data based on blockchain is proposed. Firstly, the enterprise financial data is collected from the enterprise source database with the help of ETL Technology, and the collection is completed with the help of full extraction; Then, the interference data in the data is filtered with the help of Bloom filter, and the data index position is determined with the help of hash function mapping to complete the preprocessing. Finally, with the help of the data layer, network layer, consensus layer, motivation layer and application layer in the blockchain, the data and related encrypted data and timestamp are encrypted in each node, and the data encryption key is generated to complete the rapid encryption of enterprise financial data. The experimental results show that the security coefficient of enterprise financial data encrypted by the proposed method is high, and the encryption time is short.","PeriodicalId":245783,"journal":{"name":"Web Intell.","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124413536","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}
引用次数: 0
Hybrid tree model for root cause analysis of wireless network fault localization 基于混合树模型的无线网络故障定位根源分析
Web Intell. Pub Date : 2022-06-01 DOI: 10.3233/web-220016
Bin Chen, Li Yu, Weiyi Luo, Chizhong Wu, Manyu Li, Hai Tan, Jiajin Huang, Z. Wan
{"title":"Hybrid tree model for root cause analysis of wireless network fault localization","authors":"Bin Chen, Li Yu, Weiyi Luo, Chizhong Wu, Manyu Li, Hai Tan, Jiajin Huang, Z. Wan","doi":"10.3233/web-220016","DOIUrl":"https://doi.org/10.3233/web-220016","url":null,"abstract":"Localizing the root cause of network faults is crucial to network operation and maintenance. Operational expenses will be saved if the root cause can be identified accurately. However, due to the complicated wireless environments and network architectures, accurate root cause localization of network falut meets the difficulties including missing data, hybrid fault behaviors, and short of well-labeled data. In this study, global and local features are constructed to make new feature representation for data sample, which can highlight the temporal characteristics and contextual information of the root cause analysis data. A hybrid tree model (HTM) ensembled by CatBoost, XGBoost and LightGBM is proposed to interpret the hybrid fault behaviors from several perspectives and discriminate different root causes. Based on the combination of global and local features, a semi-supervised training strategy is utilized to train the HTM for dealing with short of well-labeled data. The experiments are conducted on the real-world dataset from ICASSP 2022 AIOps Challenge, and the results show that the global and local feature based HTM achieves the best model performance comparing with other models. Meanwhile, our solution achieves third place in the competition leaderboard which shows the model effectiveness.","PeriodicalId":245783,"journal":{"name":"Web Intell.","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125474562","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}
引用次数: 1
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