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2022 21st International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES)最新文献

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Machine Learning enabled Missing Measurement Data Detection and Recovery of Electricity Grids 机器学习实现了电网缺失测量数据的检测和恢复
2022 21st International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES) Pub Date : 2022-10-01 DOI: 10.1109/DCABES57229.2022.00041
Min He, Jia Yang, Simeng Zheng, Ying Lin
{"title":"Machine Learning enabled Missing Measurement Data Detection and Recovery of Electricity Grids","authors":"Min He, Jia Yang, Simeng Zheng, Ying Lin","doi":"10.1109/DCABES57229.2022.00041","DOIUrl":"https://doi.org/10.1109/DCABES57229.2022.00041","url":null,"abstract":"This paper proposes a machine learning enabled missing data detection and recovery of electrical measurements based on the improved CPCAE. The proposed solution firstly accurately models the missing generation process to generate the missing mask and then combines the absolute difference sequence and the linear correlation as criteria to detect the possible missing segments under different signal-noise ratios (SNR). The solution divides the detected missing mask into different grades and reshapes the origin of one-dimensional data and mask into two-dimensional matrices as a kind of data enhancement. Then we intuitively turn to the deep learning technologies on image processing and design an improved CPCAE model to repair the damaged images. The proposed machine learning-enabled missing data detection and recovery solution are assessed through simulations and the numerical results confirmed its effectiveness for different missing situations.","PeriodicalId":344365,"journal":{"name":"2022 21st International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117169108","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
Frequent and High Utility Itemsets Mining Based on Bi-Objective Evolutionary Algorithm with An Improved Mutation Strategy 基于改进突变策略的双目标进化算法的频繁高效用项集挖掘
2022 21st International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES) Pub Date : 2022-10-01 DOI: 10.1109/DCABES57229.2022.00034
Chongyang Li
{"title":"Frequent and High Utility Itemsets Mining Based on Bi-Objective Evolutionary Algorithm with An Improved Mutation Strategy","authors":"Chongyang Li","doi":"10.1109/DCABES57229.2022.00034","DOIUrl":"https://doi.org/10.1109/DCABES57229.2022.00034","url":null,"abstract":"Frequent and high utility itemsets mining (FHUIM) is one of the important tasks in pattern mining. In order to solve the exponential search space and parameter setting problems that traditional HUIM algorithms encountered, the task of FHUIM was reformulated as a bi-objective problem that can be solved by multi-objective evolutionary algorithms (MOEAs). However, the search efficiency of the MOEAs may become lower when the total distinct items, the number of transactions, and the average length of transactions in the database are larger. To further improve the efficiency of MOEAs for FHUIM, we proposed FHUIM based on bi-objective evolutionary algorithm with an improved mutation strategy (FHUIM-BOEA-IMS). In FHUIM-BOEA-IMS, an improved mutation strategy is proposed to make the items with higher support and utility more likely to be saved in population, by which the FHUIs are more likely to be searched. The results on four popular datasets show that the proposed FHUIM-BOEA-IMS has better performance than the compared baseline in the task of FHUIM in terms of the convergence and final solutions.","PeriodicalId":344365,"journal":{"name":"2022 21st International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES)","volume":"271 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116248577","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
RIS-Aided Channel Construction in Random Opportunistic Networks 随机机会网络中ris辅助通道构建
2022 21st International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES) Pub Date : 2022-10-01 DOI: 10.1109/DCABES57229.2022.00069
Fei Gao, Xin Yan
{"title":"RIS-Aided Channel Construction in Random Opportunistic Networks","authors":"Fei Gao, Xin Yan","doi":"10.1109/DCABES57229.2022.00069","DOIUrl":"https://doi.org/10.1109/DCABES57229.2022.00069","url":null,"abstract":"Random opportunistic networks are dynamic, resulting in nodes not being able to sense the state of the network, and the network topology of nodes changes all the time. Therefore, this paper proposes a RIS-aided channel construction algorithm, which can be used to maintain and change the topology of random opportunistic networks. A machine learning algorithm with spatio-temporal feature fusion is first used to predict the current position of the node, and finally the RIS-aided channel construction is implemented based on the predicted position. The simulation experiments show that the algorithm can find the optimal path between the target node and the source node in the presence of errors in the target node.","PeriodicalId":344365,"journal":{"name":"2022 21st International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129701732","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
Application of Ship Data Based on Blockchain 基于区块链的船舶数据应用
2022 21st International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES) Pub Date : 2022-10-01 DOI: 10.1109/DCABES57229.2022.00023
Liu Zixiang, Cheng Cheng, Zhao Feng, Wang Xiang, Wu Feng
{"title":"Application of Ship Data Based on Blockchain","authors":"Liu Zixiang, Cheng Cheng, Zhao Feng, Wang Xiang, Wu Feng","doi":"10.1109/DCABES57229.2022.00023","DOIUrl":"https://doi.org/10.1109/DCABES57229.2022.00023","url":null,"abstract":"Aiming at the need for controlled sharing and application of data during ship design and research, a method based on blockchain is proposed in this paper. Blockchain is introduced in this method for data encryption and storage, as well as property authentication and usage log. Data-driven program is used for data application, making data invisible while accessible for users. A ship resistance prediction program based on dynamic surrogate model with relevant data is used as demonstration and successfully implemented the intended functions, showing this method available for practical application.","PeriodicalId":344365,"journal":{"name":"2022 21st International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES)","volume":"180 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116323261","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
A Method to Improve the Precision of 2-Dimensioanl Size Measurement of Objects through Image Processing 一种通过图像处理提高物体二维尺寸测量精度的方法
2022 21st International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES) Pub Date : 2022-10-01 DOI: 10.1109/DCABES57229.2022.00010
Erbing Yang, Meiqing Wang, Hang Cheng, Rong Liu, Fei Chen
{"title":"A Method to Improve the Precision of 2-Dimensioanl Size Measurement of Objects through Image Processing","authors":"Erbing Yang, Meiqing Wang, Hang Cheng, Rong Liu, Fei Chen","doi":"10.1109/DCABES57229.2022.00010","DOIUrl":"https://doi.org/10.1109/DCABES57229.2022.00010","url":null,"abstract":"Aiming at the problem of two-dimensional size measurement of objects, in this paper, an image-based measurement model with a reference object is first proposed. The bounding boxes of the target objects and the reference are obtained through image processing technology which give the lengths of edges in pixel of objects. The reference object with known length of the edge is used to calculate the pixel unit, the actual size of a pixel and then the size of the target objects are obtained accordingly. Further, a correction model with four small reference objects is proposed to improve the measurement precision. The experimental results show the validity of the proposed models.","PeriodicalId":344365,"journal":{"name":"2022 21st International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123993063","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
Optimal Design of FIR Filter Based on Improved Artificial Bee Colony Algorithm 基于改进人工蜂群算法的FIR滤波器优化设计
2022 21st International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES) Pub Date : 2022-10-01 DOI: 10.1109/DCABES57229.2022.00047
Changsheng Fang, Xiangwei Huang, Ke-wen Xia
{"title":"Optimal Design of FIR Filter Based on Improved Artificial Bee Colony Algorithm","authors":"Changsheng Fang, Xiangwei Huang, Ke-wen Xia","doi":"10.1109/DCABES57229.2022.00047","DOIUrl":"https://doi.org/10.1109/DCABES57229.2022.00047","url":null,"abstract":"The optimal design of FIR filter is very important, and using artificial bee colony algorithm can optimize fir parameters, but it also has the disadvantages of slow convergence speed and easy to fall into local optimum. Therefore, an improved artificial bee colony algorithm is proposed in the paper, which introduced the random disturbance term of chi-square distribution and convergence operator. The improved algorithm is applied to the parameter optimization design of low-pass and band-pass FIR filters, and the design effect is remarkable, especially the filter has small ripple in the passband and stopband, flat amplitude, and good attenuation characteristics.","PeriodicalId":344365,"journal":{"name":"2022 21st International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125433064","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
Model Checking the Reliability of Blockchain-based Edge Computing Network 基于区块链的边缘计算网络可靠性模型检验
2022 21st International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES) Pub Date : 2022-10-01 DOI: 10.1109/DCABES57229.2022.00043
Kai Zheng, Xiang Yao, Zhe Zhang, Liyou Fang
{"title":"Model Checking the Reliability of Blockchain-based Edge Computing Network","authors":"Kai Zheng, Xiang Yao, Zhe Zhang, Liyou Fang","doi":"10.1109/DCABES57229.2022.00043","DOIUrl":"https://doi.org/10.1109/DCABES57229.2022.00043","url":null,"abstract":"In recent years, the development of blockchain and edge computing is very quickly. Compared with centralized cloud scenario, edge computing help to improve the efficiency of it. The end devices can undertake some of the work load to reduce the pressure of centralized cloud devices. Blockchain technology help to enhance the security of the whole network, and it is also an emerging technology. However, the reliability of blockchain-based edge computing network (BBECN) is still a challenge, few of the recent research focus on the reliability evaluation of it. To make up the research, in this paper, a continuous-time Markov chain (CTMC) model is proposed to calculate the reliability of BBECN. In this paper, 4 experiments are proposed to evaluate the influence of different influence factors and compare them. The research work of this paper will help to optimize the architecture design of BBECN.","PeriodicalId":344365,"journal":{"name":"2022 21st International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132038716","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
Evolution Enhanced Resilience of Protein Interaction Networks 进化增强了蛋白质相互作用网络的弹性
2022 21st International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES) Pub Date : 2022-10-01 DOI: 10.1109/DCABES57229.2022.00031
Jiarui Zhang, D. Ding
{"title":"Evolution Enhanced Resilience of Protein Interaction Networks","authors":"Jiarui Zhang, D. Ding","doi":"10.1109/DCABES57229.2022.00031","DOIUrl":"https://doi.org/10.1109/DCABES57229.2022.00031","url":null,"abstract":"Most biological functions are presented through protein-protein interaction (PPI) networks. PPI networks show the complex protein-protein interaction relationship within the organism. The generation or destruction of these interaction may lead to changes in biological functions. The latest research results show that the interaction network of species with a higher degree of evolution has higher resilience. Here we explore the resilience changes of a single species during its evolution. We obtain data from public and published websites SNAP. We have proved that no matter what the network structure is, whether it is large or small, when the network fault gradually increases, the resilience gradually decreases. This also indicates that the network with the greatest resilience has a higher degree of evolution.","PeriodicalId":344365,"journal":{"name":"2022 21st International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133142237","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 Comparison Study of Graph Neural Network and Support Vector Machine 图神经网络与支持向量机的比较研究
2022 21st International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES) Pub Date : 2022-10-01 DOI: 10.1109/DCABES57229.2022.00009
Siying Lin, J. Alves, Francesca Bugiotti, F. Magoulès
{"title":"A Comparison Study of Graph Neural Network and Support Vector Machine","authors":"Siying Lin, J. Alves, Francesca Bugiotti, F. Magoulès","doi":"10.1109/DCABES57229.2022.00009","DOIUrl":"https://doi.org/10.1109/DCABES57229.2022.00009","url":null,"abstract":"A variety of issues, including classification, link prediction, and graph clustering, have been solved using graph neural network (GNN), an efficient method for handling non-Euclidean structural data. Another effective and reliable mathematical tool for classification and regression applications is support vector machine (SVM). We hope that this paper will help readers gain a better knowledge of the latest developments in graph neural networks and how they are used in a variety of fields. We also describe current research on using support vector machines for prediction and classification problems. Following that, a comparison between SVM and GNN is made, and the results are discussed.","PeriodicalId":344365,"journal":{"name":"2022 21st International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123517651","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 Intelligent Machine Learning based Ultra-short Term Generation Prediction of Photovoltaic Systems 基于混合智能机器学习的光伏系统超短期发电预测
2022 21st International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES) Pub Date : 2022-10-01 DOI: 10.1109/DCABES57229.2022.00037
Yongguang Wang, Chuncheng Cao, Zhimin Wo, Songtao Tian, Yang Bai, Xu Tai
{"title":"Hybrid Intelligent Machine Learning based Ultra-short Term Generation Prediction of Photovoltaic Systems","authors":"Yongguang Wang, Chuncheng Cao, Zhimin Wo, Songtao Tian, Yang Bai, Xu Tai","doi":"10.1109/DCABES57229.2022.00037","DOIUrl":"https://doi.org/10.1109/DCABES57229.2022.00037","url":null,"abstract":"This work developed an ultra short-term photovoltaic power prediction model based on hybrid intelligent technology. The proposed model adopts a series of data processing technologies, including input variable selection based on statistical analysis, attribute reduction based on principal component analysis (PCA) and feature subset division based on the K-means clustering algorithm, to obtain a more relevant and effective data as input information for prediction. The model uses an adaptive neural fuzzy inference system (ANFIS) to train and learn the input information to obtain the output prediction results. The particle swarm optimization (PSO) algorithm is adopted in the training process to optimize the ANFIS parameters to reduce the prediction error. The proposed solution is evaluated through simulation experiments and the numerical results demonstrate that it can achieve effective prediction accuracy and has good adaptability.","PeriodicalId":344365,"journal":{"name":"2022 21st International Symposium on Distributed Computing and Applications for Business Engineering and Science (DCABES)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125012667","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
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