In this paper, we study some common coincidence point theorems for four mappings from T1 topological space to complete b- metric spaces. By using the proper mapping conditions and the closure of image, it is proved that under the suitable conditions, the four mappings have common coincidence points. Meanwhile, one concrete example is constructed to illustrate the application of our results.
{"title":"Common Coincidence Point Theorems for Four Mappings","authors":"Y. Hao, H. Guan","doi":"10.1145/3424978.3425040","DOIUrl":"https://doi.org/10.1145/3424978.3425040","url":null,"abstract":"In this paper, we study some common coincidence point theorems for four mappings from T1 topological space to complete b- metric spaces. By using the proper mapping conditions and the closure of image, it is proved that under the suitable conditions, the four mappings have common coincidence points. Meanwhile, one concrete example is constructed to illustrate the application of our results.","PeriodicalId":178822,"journal":{"name":"Proceedings of the 4th International Conference on Computer Science and Application Engineering","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132980402","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}
Driven by the growing number of DNS requests on the Internet, the architecture of the recursive resolver has become more huge and complex, especially for open resolvers that provide resolution services to the public. There are many service nodes with different roles in the open resolver, and the nodes that directly communicate with the authoritative server are called recursive egress nodes. This paper proposed a distributed measurement system and performed active measurement and analysis on the characteristics of the egress node of open resolvers collected from passive DNS traffic and third party active scanning. The results from 65 vantage points show that (1) most open resolvers have dozens of recursive egress nodes, and (2) most open resolvers have deployed at least one IPv6 address egress node, while IPv4 address still dominates the service node configuration. (3) A small amount of recursive egress nodes is reused by a large number of open resolvers, so that a large amount of DNS request traffic on the Internet is concentrated on limited recursive egress nodes, which will reduce the redundancy of DNS and cause cyber security risks. (4) The median distances between most open resolvers with multiple egress nodes and the users usually exceed 1000 kilometers, which will bring negative effect on the scheduling accuracy of CDN.
{"title":"Active Measurement of Open Resolver Service Nodes","authors":"Hailing Li, Xiaohang Zhang, Shoufeng Cao, Longtao He, Hui Zhang","doi":"10.1145/3424978.3425039","DOIUrl":"https://doi.org/10.1145/3424978.3425039","url":null,"abstract":"Driven by the growing number of DNS requests on the Internet, the architecture of the recursive resolver has become more huge and complex, especially for open resolvers that provide resolution services to the public. There are many service nodes with different roles in the open resolver, and the nodes that directly communicate with the authoritative server are called recursive egress nodes. This paper proposed a distributed measurement system and performed active measurement and analysis on the characteristics of the egress node of open resolvers collected from passive DNS traffic and third party active scanning. The results from 65 vantage points show that (1) most open resolvers have dozens of recursive egress nodes, and (2) most open resolvers have deployed at least one IPv6 address egress node, while IPv4 address still dominates the service node configuration. (3) A small amount of recursive egress nodes is reused by a large number of open resolvers, so that a large amount of DNS request traffic on the Internet is concentrated on limited recursive egress nodes, which will reduce the redundancy of DNS and cause cyber security risks. (4) The median distances between most open resolvers with multiple egress nodes and the users usually exceed 1000 kilometers, which will bring negative effect on the scheduling accuracy of CDN.","PeriodicalId":178822,"journal":{"name":"Proceedings of the 4th International Conference on Computer Science and Application Engineering","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130557659","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}
The forecasting of box office receipts is always a difficult and challenging problem. In this paper, a forecasting approach is proposed to accurately forecasting weekend box office receipts based on multifractal detrend cross-correlation analysis (MF-DCCA) and multiple neural networks (DNN, CNN, LSTM). The MF-DCCA quantitatively finds that there is a long-range cross-correlation between each factor and box office receipts, which is multifractal. Its rolling window can reflect the intrinsic mechanism of neural network, and extract effective data that can improve the generalization ability of the model from the original data. The predictive performance of these frameworks is able to meet or exceed the method based on a single neural network. For (MF-DCCA)-DNN, the classification accuracy is 0.843, (MF-DCCA)-CNN is 0.786, and (MF-DCCA)-LSTM is 0.986. This research provides a theoretical method to further to enrich and improve the accuracy of box office receipts prediction and the extraction of effective feature.
{"title":"Weekend Box Office Forecasting Based on MF-DCCA and Multiple Neural Networks Approach","authors":"L. Gu, Xinxin Zhang, Ke Li, Guozhu Jia","doi":"10.1145/3424978.3425091","DOIUrl":"https://doi.org/10.1145/3424978.3425091","url":null,"abstract":"The forecasting of box office receipts is always a difficult and challenging problem. In this paper, a forecasting approach is proposed to accurately forecasting weekend box office receipts based on multifractal detrend cross-correlation analysis (MF-DCCA) and multiple neural networks (DNN, CNN, LSTM). The MF-DCCA quantitatively finds that there is a long-range cross-correlation between each factor and box office receipts, which is multifractal. Its rolling window can reflect the intrinsic mechanism of neural network, and extract effective data that can improve the generalization ability of the model from the original data. The predictive performance of these frameworks is able to meet or exceed the method based on a single neural network. For (MF-DCCA)-DNN, the classification accuracy is 0.843, (MF-DCCA)-CNN is 0.786, and (MF-DCCA)-LSTM is 0.986. This research provides a theoretical method to further to enrich and improve the accuracy of box office receipts prediction and the extraction of effective feature.","PeriodicalId":178822,"journal":{"name":"Proceedings of the 4th International Conference on Computer Science and Application Engineering","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123876182","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}
Recently, strategy specification and verification has been an active research direction in many areas, such as multi-agent systems, artificial intelligence, formal methods, logic, and so on. Since alternating-time temporal logic (ATL/ATL*) was proposed by Alur et al., many strategic logics, which are based on ATL/ATL*, have been introduced by many researchers. Among them strategy logic (SL) is an outstanding representative, which can express more properties like the existence of Nash Equilibrium in game theory; however, it cannot express regular temporal properties, nor epistemic properties. Based on linear dynamic logic (LDL), we propose a new strategic logic with knowledge, by extending SL. Moreover, under the semantics of memoryless strategies, we show that the model checking problem for this logic is PSPACE-complete with both the length of the sentence and the size of the model.
{"title":"Model Checking Dynamic Strategy Logic with Memoryless Strategies","authors":"Liping Xiong, Sumei Guo","doi":"10.1145/3424978.3425046","DOIUrl":"https://doi.org/10.1145/3424978.3425046","url":null,"abstract":"Recently, strategy specification and verification has been an active research direction in many areas, such as multi-agent systems, artificial intelligence, formal methods, logic, and so on. Since alternating-time temporal logic (ATL/ATL*) was proposed by Alur et al., many strategic logics, which are based on ATL/ATL*, have been introduced by many researchers. Among them strategy logic (SL) is an outstanding representative, which can express more properties like the existence of Nash Equilibrium in game theory; however, it cannot express regular temporal properties, nor epistemic properties. Based on linear dynamic logic (LDL), we propose a new strategic logic with knowledge, by extending SL. Moreover, under the semantics of memoryless strategies, we show that the model checking problem for this logic is PSPACE-complete with both the length of the sentence and the size of the model.","PeriodicalId":178822,"journal":{"name":"Proceedings of the 4th International Conference on Computer Science and Application Engineering","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124070965","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}
Zesen Cheng, Lijuan Lai, Tianyu Zeng, Sijuan Huang, Xin Yang
In this paper, we try to incorporate residual connection and Attention Gate block into medical image segmentation network. At first, we construct a 2D residual U-Net (a 2D V-Net) to incorporate residual connection for medical image segmentation. In order to incorporate Attention Gate block into the V-Net, we build up the Attention Residual Block which adds a shortcut into Attention Gate Block. The Attention Residual Block will be more adaptive than raw Attention Gate Block. We also insert the Attention Residul Block into the skip connection between the encoder and the decoder of 2D V-Net and create a new network called Attention V-Net. Then we train and evaluate the networks on the 16th CSTRO conference Lung OAR segmentation competition dataset. What's more, we find out when the mirrored OARs are segmented, the networks may mix up them together. Therefore, we use a postprocessing method to correct the result. Finally, we compare the model with the state-of-the-arts to show the superiority of the proposed network.
{"title":"Attention V-Net: A Residual U-Net with Attention Gate Block for Lung Organs At Risk Segmentation","authors":"Zesen Cheng, Lijuan Lai, Tianyu Zeng, Sijuan Huang, Xin Yang","doi":"10.1145/3424978.3425117","DOIUrl":"https://doi.org/10.1145/3424978.3425117","url":null,"abstract":"In this paper, we try to incorporate residual connection and Attention Gate block into medical image segmentation network. At first, we construct a 2D residual U-Net (a 2D V-Net) to incorporate residual connection for medical image segmentation. In order to incorporate Attention Gate block into the V-Net, we build up the Attention Residual Block which adds a shortcut into Attention Gate Block. The Attention Residual Block will be more adaptive than raw Attention Gate Block. We also insert the Attention Residul Block into the skip connection between the encoder and the decoder of 2D V-Net and create a new network called Attention V-Net. Then we train and evaluate the networks on the 16th CSTRO conference Lung OAR segmentation competition dataset. What's more, we find out when the mirrored OARs are segmented, the networks may mix up them together. Therefore, we use a postprocessing method to correct the result. Finally, we compare the model with the state-of-the-arts to show the superiority of the proposed network.","PeriodicalId":178822,"journal":{"name":"Proceedings of the 4th International Conference on Computer Science and Application Engineering","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130233559","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}
Data mining of students' scores can optimize teaching strategies and improve the teaching quality continuously. However, there are two problems in the current researches of teaching data mining. Firstly, most researchers focus on students' performance among multiple courses, but these data are relatively rough, and with little help for improving specific teaching strategies (e.g., using different teaching and assessment methods) of a single course. Secondly, students' performance not only depends on their efforts, but also is affected by the effectiveness of the assessment methods made by teachers, so it is impossible to have accurate improvement without considering factors from both teacher and students' sides. This paper takes the students' scores of computer network course as the sample, uses k-means to cluster students' scores from different assessment methods based on fine grained teaching contents, in order to get more accurate teaching improvement strategies later. In addition, an improved Apriori algorithm is proposed with the quality of assessment methods taken into consideration, for association rules selection and teaching strategies improvement. According to the experiments, our method can take into account the diversity of course assessment methods and the influence of both teaching and learning factors, and the accuracy of the improved rules is 18.8% higher than that current Apriori algorithm based on interest.
{"title":"Automatic Rules Generation for Teaching Strategies Improvement","authors":"Jing Zhan, Xue Fan, Yong Zhao","doi":"10.1145/3424978.3425079","DOIUrl":"https://doi.org/10.1145/3424978.3425079","url":null,"abstract":"Data mining of students' scores can optimize teaching strategies and improve the teaching quality continuously. However, there are two problems in the current researches of teaching data mining. Firstly, most researchers focus on students' performance among multiple courses, but these data are relatively rough, and with little help for improving specific teaching strategies (e.g., using different teaching and assessment methods) of a single course. Secondly, students' performance not only depends on their efforts, but also is affected by the effectiveness of the assessment methods made by teachers, so it is impossible to have accurate improvement without considering factors from both teacher and students' sides. This paper takes the students' scores of computer network course as the sample, uses k-means to cluster students' scores from different assessment methods based on fine grained teaching contents, in order to get more accurate teaching improvement strategies later. In addition, an improved Apriori algorithm is proposed with the quality of assessment methods taken into consideration, for association rules selection and teaching strategies improvement. According to the experiments, our method can take into account the diversity of course assessment methods and the influence of both teaching and learning factors, and the accuracy of the improved rules is 18.8% higher than that current Apriori algorithm based on interest.","PeriodicalId":178822,"journal":{"name":"Proceedings of the 4th International Conference on Computer Science and Application Engineering","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127170458","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}
The finite element analysis method is applied to optimize the shell structure of small four rotors UAV, and static analysis and natural mode analysis are carried out. The overall scheme of small four rotors UAV is designed and arranged. The four rotors UAV is preassembled by using SolidWorks and its structure are modeled in three dimensions. The finite element method is used to optimize and analyze the structure and natural state of the small four rotors UAV. The static numerical analysis and multimodal numerical analysis of the whole body and components of the four rotors UAV are carried out by using SolidWorks and workbench software, and the structural stress of the four rotors UAV is analyzed. Through analyzing the check results, it is shown that the strength and stiffness are qualified, the scheme is feasible and the design is reasonable; the overall structure design of the small four rotors UAV is reasonable without interference and meets the requirements of design strength and design stiffness.
{"title":"Structural Optimization Design and Natural Mode Analysis of Small Four Rotors UAV","authors":"Renbin Zhou, Zuxun Zhang","doi":"10.1145/3424978.3424992","DOIUrl":"https://doi.org/10.1145/3424978.3424992","url":null,"abstract":"The finite element analysis method is applied to optimize the shell structure of small four rotors UAV, and static analysis and natural mode analysis are carried out. The overall scheme of small four rotors UAV is designed and arranged. The four rotors UAV is preassembled by using SolidWorks and its structure are modeled in three dimensions. The finite element method is used to optimize and analyze the structure and natural state of the small four rotors UAV. The static numerical analysis and multimodal numerical analysis of the whole body and components of the four rotors UAV are carried out by using SolidWorks and workbench software, and the structural stress of the four rotors UAV is analyzed. Through analyzing the check results, it is shown that the strength and stiffness are qualified, the scheme is feasible and the design is reasonable; the overall structure design of the small four rotors UAV is reasonable without interference and meets the requirements of design strength and design stiffness.","PeriodicalId":178822,"journal":{"name":"Proceedings of the 4th International Conference on Computer Science and Application Engineering","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126445891","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}
Broad Learning System has been used in many applications. For example, face recognition, image classification and segmentation, time series prediction. A broad learning system algorithm based on nonlinear transformation and feedback adjustment proposed to improve the accuracy of the traditional broad learning system model. This paper analyzes the impact of data on the model from the perspective of probability statistics and feature mapping, and finds the best nonlinear mapping function from the angle of data tilt to accurate data sets. In terms of the accuracy of model training, fine-tuning the broad learning system in the form of a feedback model, set the appropriate number of fine-tuning and fine-tuning rates to improve the accuracy of the model training; In addition, combined with nonlinear transformation and feedback adjustment model, new algorithms and corresponding diagrams are given. In this paper, weather data sets are used to prove the rationality and effectiveness of the algorithm framework.
{"title":"Broad Learning System Based on Nonlinear Transformation and Feedback Adjustment","authors":"Shuangyun Sun, Hexiao Huang, Zhanquan Wang","doi":"10.1145/3424978.3424989","DOIUrl":"https://doi.org/10.1145/3424978.3424989","url":null,"abstract":"Broad Learning System has been used in many applications. For example, face recognition, image classification and segmentation, time series prediction. A broad learning system algorithm based on nonlinear transformation and feedback adjustment proposed to improve the accuracy of the traditional broad learning system model. This paper analyzes the impact of data on the model from the perspective of probability statistics and feature mapping, and finds the best nonlinear mapping function from the angle of data tilt to accurate data sets. In terms of the accuracy of model training, fine-tuning the broad learning system in the form of a feedback model, set the appropriate number of fine-tuning and fine-tuning rates to improve the accuracy of the model training; In addition, combined with nonlinear transformation and feedback adjustment model, new algorithms and corresponding diagrams are given. In this paper, weather data sets are used to prove the rationality and effectiveness of the algorithm framework.","PeriodicalId":178822,"journal":{"name":"Proceedings of the 4th International Conference on Computer Science and Application Engineering","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129046774","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}
Sea level rise is a slow-onset natural disaster, with cumulative and gradual nature. It has a considerable impact on human survival, economic development and cultural inheritance [1]. Coupled with the impact of land subsidence in many areas along the coast, sea level rise may reach 1 meter or even higher within a century [2]. In order to meet the increasingly severe energy policy challenges and protect the unique culture that is about to disappear, it is important to establish a model that can assess whether a country or region has migration risks. This article will build a neural network model to assess the risk of each island country and predict its possibility of becoming a climate refugee country, in order to help people around the world to take precautionary measures in advance, and help risky countries prepare for migrating nationals in advance. And through further analysis of the data of 11 countries that have been determined by the Office of the United Nations High Commissioner for Refugees in Syria, the model construction and model calculation are carried out [3]. Finally, according to the imbalanced population distribution index and population density concentration index of 11 countries [4], we can know that in Bosnia and Herzegovina the risk of losing the culture of Syrian refugees is relatively low.
{"title":"Research on Migration Risk of Island Countries Based on Neural Network","authors":"Yong Gan, Fei Xue, Boqiao Zeng, Yuhua He, Q. Zhang, Jianghao Yu","doi":"10.1145/3424978.3425024","DOIUrl":"https://doi.org/10.1145/3424978.3425024","url":null,"abstract":"Sea level rise is a slow-onset natural disaster, with cumulative and gradual nature. It has a considerable impact on human survival, economic development and cultural inheritance [1]. Coupled with the impact of land subsidence in many areas along the coast, sea level rise may reach 1 meter or even higher within a century [2]. In order to meet the increasingly severe energy policy challenges and protect the unique culture that is about to disappear, it is important to establish a model that can assess whether a country or region has migration risks. This article will build a neural network model to assess the risk of each island country and predict its possibility of becoming a climate refugee country, in order to help people around the world to take precautionary measures in advance, and help risky countries prepare for migrating nationals in advance. And through further analysis of the data of 11 countries that have been determined by the Office of the United Nations High Commissioner for Refugees in Syria, the model construction and model calculation are carried out [3]. Finally, according to the imbalanced population distribution index and population density concentration index of 11 countries [4], we can know that in Bosnia and Herzegovina the risk of losing the culture of Syrian refugees is relatively low.","PeriodicalId":178822,"journal":{"name":"Proceedings of the 4th International Conference on Computer Science and Application Engineering","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120974888","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}
Shengnan Zhang, Jiaxing Xuan, Zitong Lyu, Yuchen Fu
Disadvantages like cumbersome verification and data centralization are involved in the application and transaction process of Renewable Energy Certificates in China. We realize that blockchain technology has been successfully applied in many fields with its features of decentralization, immutability, and traceability. As a result, we in this article aim to introduce blockchain into the current Renewable Energy Certificates trading system to solve the above problems. Firstly, this article gives an overview of blockchain technology, including its architecture and technical advantages. Secondly, it describes China's Renewable Energy Certificates transaction process and analyzes the potential challenges faced by it. Finally, it proposes a Renewable Energy Certificates trading system based on blockchain technology and analyzes its operation mode, advantages, and potential problems.
{"title":"Application Prospect of Blockchain in Renewable Energy Certificates","authors":"Shengnan Zhang, Jiaxing Xuan, Zitong Lyu, Yuchen Fu","doi":"10.1145/3424978.3425016","DOIUrl":"https://doi.org/10.1145/3424978.3425016","url":null,"abstract":"Disadvantages like cumbersome verification and data centralization are involved in the application and transaction process of Renewable Energy Certificates in China. We realize that blockchain technology has been successfully applied in many fields with its features of decentralization, immutability, and traceability. As a result, we in this article aim to introduce blockchain into the current Renewable Energy Certificates trading system to solve the above problems. Firstly, this article gives an overview of blockchain technology, including its architecture and technical advantages. Secondly, it describes China's Renewable Energy Certificates transaction process and analyzes the potential challenges faced by it. Finally, it proposes a Renewable Energy Certificates trading system based on blockchain technology and analyzes its operation mode, advantages, and potential problems.","PeriodicalId":178822,"journal":{"name":"Proceedings of the 4th International Conference on Computer Science and Application Engineering","volume":"17 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120992821","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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