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2022 4th International Conference on Intelligent Information Processing (IIP)最新文献

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Student Achievement Analysis and Prediction Based on Educational Data 基于教育数据的学生成绩分析与预测
2022 4th International Conference on Intelligent Information Processing (IIP) Pub Date : 2022-10-01 DOI: 10.1109/iip57348.2022.00057
Taoning Zhang, Qisheng Liu
{"title":"Student Achievement Analysis and Prediction Based on Educational Data","authors":"Taoning Zhang, Qisheng Liu","doi":"10.1109/iip57348.2022.00057","DOIUrl":"https://doi.org/10.1109/iip57348.2022.00057","url":null,"abstract":"With the continuous popularization of higher education and the continuous expansion of enrollment in colleges and universities, this has led to the increasing shortage of teaching resources in colleges and universities. On the other hand, the difficulty of higher education courses is relatively high, which leads to poor academic performance of some students. The so called student achievement analysis and prediction aims to analyze and predict the student’s academic performance in the future with the help of various information of the student, such as course grades, comprehensive academic performance and education data. In this regard, this paper analyzes a given educational data dataset containing student attributes of two schools in Portugal based on machine learning, predicts students’ performance in final exams, and evaluates the effect of different machine learning models.","PeriodicalId":412907,"journal":{"name":"2022 4th International Conference on Intelligent Information Processing (IIP)","volume":"20 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":"126282048","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 System Construction Method based on Smart Contract 基于智能合约的智能系统构建方法
2022 4th International Conference on Intelligent Information Processing (IIP) Pub Date : 2022-10-01 DOI: 10.1109/IIP57348.2022.00084
Tianxiang Xu, Chang Liu
{"title":"Intelligent System Construction Method based on Smart Contract","authors":"Tianxiang Xu, Chang Liu","doi":"10.1109/IIP57348.2022.00084","DOIUrl":"https://doi.org/10.1109/IIP57348.2022.00084","url":null,"abstract":"In recent research, improving the performance and guaranteeing the security of intelligent system is an essential issue for current system. High computation speed and co-construction systems has been developed by researchers to enhance the effectiveness of intelligent system. However, disposing numbers of data by utilizing a safe method is an important challenge for any intelligent system and current researchers focus on changing the system architecture and modeling methods, which ignore the security of developed mechanism and may cause serious system problems. In this article, we propose a novel intelligent mechanism can guarantee the security and high performance of the system. Through disposing the smart contract for data users, owners and processors, the intelligent system central units can utilize the data by a reliable method and other attackers will never access the data without any permission. From our extensively experimental analysis, proposed system can achieve high computation performance with reasonable calculation cost.","PeriodicalId":412907,"journal":{"name":"2022 4th International Conference on Intelligent Information Processing (IIP)","volume":"20 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":"128236264","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
DoS: Abstractive text summarization based on pretrained model with document sharing DoS:基于文档共享预训练模型的抽象文本摘要
2022 4th International Conference on Intelligent Information Processing (IIP) Pub Date : 2022-10-01 DOI: 10.1109/IIP57348.2022.00040
Xingxing Ding, Ruo Wang, Zhong Zheng, Xuan Liu, Quan Zhu, Ruiqun Li, Wanru Du, Siyuan Shen
{"title":"DoS: Abstractive text summarization based on pretrained model with document sharing","authors":"Xingxing Ding, Ruo Wang, Zhong Zheng, Xuan Liu, Quan Zhu, Ruiqun Li, Wanru Du, Siyuan Shen","doi":"10.1109/IIP57348.2022.00040","DOIUrl":"https://doi.org/10.1109/IIP57348.2022.00040","url":null,"abstract":"In this paper, an abstractive text summarization method with document sharing is proposed. It consists of a pretrained model and self-attention mechanism on multi-document. We call it DoS mechanism. By applying the mechanism to the single-document text summarization task, the model can absorb information from multiple documents, thus enhancing its effectiveness of the model. We compared the results with several models. The experimental results show that the pre-trained model with modified attention provides the best results, where the values of Rouge-l, Rouge-2, and Rouge-L are 41.3%, 27.4%, and 38.0%, respectively. Evaluations on the LCSTS demonstrate that our model outperforms the baseline model. Subsequent analysis showed that our model was able to generate higherquality summaries.","PeriodicalId":412907,"journal":{"name":"2022 4th International Conference on Intelligent Information Processing (IIP)","volume":"31 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":"129433726","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
Auxiliary Classifier Generative Adversarial Network Assisted Intrusion Detection System 辅助分类器生成对抗网络辅助入侵检测系统
2022 4th International Conference on Intelligent Information Processing (IIP) Pub Date : 2022-10-01 DOI: 10.1109/iip57348.2022.00070
Kejun Zhang, Haocong Qin, Yuhan Jin, Hangyu Wang, Xinying Yu
{"title":"Auxiliary Classifier Generative Adversarial Network Assisted Intrusion Detection System","authors":"Kejun Zhang, Haocong Qin, Yuhan Jin, Hangyu Wang, Xinying Yu","doi":"10.1109/iip57348.2022.00070","DOIUrl":"https://doi.org/10.1109/iip57348.2022.00070","url":null,"abstract":"Machine learning is applied widely in the field of intrusion detection at present, the existing intrusion detection algorithm is relatively mature, but how to solve the problem of unbalanced sample data still need further research. Aiming at the problem of detection accuracy and efficiency caused by sample data imbalance in the process of intrusion detection, this paper proposes an intrusion detection method based on the fusion of Auxiliary Classification Adversarial Network (ACGAN) and Graph Neural Network (GNN) (ACGAN-GNN). Firstly, ACGAN is used to expand minority samples in data preprocessing to optimize the dataset, and then the improved heterogeneous graph neural network algorithm is used to model the sample flow relationship in the classification process, so as to improve the detection robustness of minority attack samples and unknown attack samples. The model is evaluated by CICIDS2017 dataset. Compared with similar algorithms, ACGAN-GNN not only has better performance in terms of accuracy, precision, recall and F1-score, but also has higher accuracy against minority or unknown attack types.","PeriodicalId":412907,"journal":{"name":"2022 4th International Conference on Intelligent Information Processing (IIP)","volume":"205 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":"133233963","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
Fire Risk Assessment Based on SMOTE and Bayesian Network 基于SMOTE和贝叶斯网络的火灾风险评估
2022 4th International Conference on Intelligent Information Processing (IIP) Pub Date : 2022-10-01 DOI: 10.1109/iip57348.2022.00088
Yanlu Shi, Jianguo Gao
{"title":"Fire Risk Assessment Based on SMOTE and Bayesian Network","authors":"Yanlu Shi, Jianguo Gao","doi":"10.1109/iip57348.2022.00088","DOIUrl":"https://doi.org/10.1109/iip57348.2022.00088","url":null,"abstract":"Establishing fire historical data and index system is the key to solving the fire risk assessment problem. Based on this, this paper proposes a new fire risk assessment method. Firstly, aiming at the imbalance problem of fire history data, SMOTE algorithm is used to expand the small class of sample data and build an improved fire sample data set. Secondly, the improved fire data and expert knowledge are used to learn the structure and parameters of the Bayesian network. Finally, the risk assessment value is determined through the probabilistic inference of the Bayesian network. Applying this method to building fire risk assessment can effectively solve the problem of unbalanced fire data and improve the level of fire risk assessment.","PeriodicalId":412907,"journal":{"name":"2022 4th International Conference on Intelligent Information Processing (IIP)","volume":"20 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":"123824298","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
High-altitude parabolic detection method based on GMM model and SORT algorithm 基于GMM模型和SORT算法的高空抛物探测方法
2022 4th International Conference on Intelligent Information Processing (IIP) Pub Date : 2022-10-01 DOI: 10.1109/IIP57348.2022.00059
Yun-Tao Shi, Qi Luo, Zhang Tao, Cheng Yue Hao
{"title":"High-altitude parabolic detection method based on GMM model and SORT algorithm","authors":"Yun-Tao Shi, Qi Luo, Zhang Tao, Cheng Yue Hao","doi":"10.1109/IIP57348.2022.00059","DOIUrl":"https://doi.org/10.1109/IIP57348.2022.00059","url":null,"abstract":"With the accelerated urbanization process in China, the resident population is flocking to high-rise buildings. The number of high-altitude parabolic has increased significantly, resulting in many casualties and property damage accidents. To this end, a proposed technique for high-altitude parabolic detection based on Gaussian Mixture Model (GMM) and Simple Online and Realtime Tracking (SORT) is proposed. Firstly, the GMM-based background modelling method is used to separate the background and foreground from the image sequence to obtain the motion image of the dynamic target at the current moment. The image is subjected to mathematical morphological denoising to determine whether the dynamic target is a throwing object by SORT. Experimental results show that the proposed method can accurately detect the dynamic target of overhead throwing objects with good stability and can effectively reduce the false detection rate.","PeriodicalId":412907,"journal":{"name":"2022 4th International Conference on Intelligent Information Processing (IIP)","volume":"3 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":"124935502","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 ant colony algorithm in reconfiguration of power system distribution network 蚁群算法在配电网重构中的应用
2022 4th International Conference on Intelligent Information Processing (IIP) Pub Date : 2022-10-01 DOI: 10.1109/iip57348.2022.00056
Bo Wang, Yining Ma, Luyao Pei, Liang Sui, Cheng Xu
{"title":"Application of ant colony algorithm in reconfiguration of power system distribution network","authors":"Bo Wang, Yining Ma, Luyao Pei, Liang Sui, Cheng Xu","doi":"10.1109/iip57348.2022.00056","DOIUrl":"https://doi.org/10.1109/iip57348.2022.00056","url":null,"abstract":"In this paper, the ant colony search algorithm (ACSA) is utilized to solve the matching network reconstruction problem. the advantage of ACSA is the parallel search and optimization capability. This algorithm is inspired by the observation of ant colony behavior. Individual ants in the ant colony algorithm can communicate and collaborate through the perception of pheromones. The study of the distribution network reconfiguration problem by the ant colony algorithm is mainly based on the positive feedback property of the ant colony algorithm and the role of pheromones. The simulation model is used to obtain and study the change curve of the objective function value during the process of the ant colony algorithm, so as to achieve the purpose of reducing network loss and improving stability. The example shows the practicality and effectiveness of the ant colony algorithm for the reconfiguration of power system distribution networks.","PeriodicalId":412907,"journal":{"name":"2022 4th International Conference on Intelligent Information Processing (IIP)","volume":"22 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":"124610139","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
Traffic signs recognition model over data augmentation based on Yolov5 基于Yolov5的数据增强交通标志识别模型
2022 4th International Conference on Intelligent Information Processing (IIP) Pub Date : 2022-10-01 DOI: 10.1109/iip57348.2022.00017
Shuang Shan, Gong Chen
{"title":"Traffic signs recognition model over data augmentation based on Yolov5","authors":"Shuang Shan, Gong Chen","doi":"10.1109/iip57348.2022.00017","DOIUrl":"https://doi.org/10.1109/iip57348.2022.00017","url":null,"abstract":"Due to the long time consuming of data collection, it is difficult to label small targets of data samples, the amount of data is small, and the sample distribution is uneven. At the same time, the proportion of small targets is small, the missed detection rate is high, and the model feature fusion is insufficient. In order to pay more attention to the detection target and improve the feature extraction ability of the algorithm. In this regard, this paper proposes a method to generate a new sample dataset by expanding the existing dataset samples, and integrates the Convolutional Block Attention Module (CBAM) into the backbone feature extraction network. The scale feature fusion module, combined with the yolov5 target detection model, achieves the purpose of improving the detection rate of individual identification and enhancing the generalization ability of the target detection model. This data augmentation method enriches the traffic sign dataset and improves the robustness of the model, making it more suitable for practical scenarios. Taking the TTIOOK dataset as an example, its experimental results demonstrate the effectiveness and superiority of the proposed method compared with the unimproved method.","PeriodicalId":412907,"journal":{"name":"2022 4th International Conference on Intelligent Information Processing (IIP)","volume":"1 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":"129962590","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
Research on key technology of substation integrated self-monitoring management System 变电站综合自监控管理系统关键技术研究
2022 4th International Conference on Intelligent Information Processing (IIP) Pub Date : 2022-10-01 DOI: 10.1109/iip57348.2022.00047
Q. Jin, Fengyuan Zheng, Xutong Xie, Zhi Xun
{"title":"Research on key technology of substation integrated self-monitoring management System","authors":"Q. Jin, Fengyuan Zheng, Xutong Xie, Zhi Xun","doi":"10.1109/iip57348.2022.00047","DOIUrl":"https://doi.org/10.1109/iip57348.2022.00047","url":null,"abstract":"In order to break the traditional monitoring method of substation and promote the intelligent process of substation, this paper took BZ substation as the research object, studied the key technologies of its integrated monitoring management system and tested the performance of the integrated monitoring management system. It was found that the average throughput of the system was 1649583KB/s, and the average response time was 0. 25ms. The maximum response time is 1. 735s, and the results can meet the actual requirements, which confirms the performance of the integrated self-monitoring management system and can improve the intelligent process of the substation.","PeriodicalId":412907,"journal":{"name":"2022 4th International Conference on Intelligent Information Processing (IIP)","volume":"1 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":"129632709","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
License plate recognition based on YOLOv5-LPRNet 基于YOLOv5-LPRNet的车牌识别
2022 4th International Conference on Intelligent Information Processing (IIP) Pub Date : 2022-10-01 DOI: 10.1109/IIP57348.2022.00020
Yun-Tao Shi, Hongfei Zhang, Zhang Tao, Wei Guo
{"title":"License plate recognition based on YOLOv5-LPRNet","authors":"Yun-Tao Shi, Hongfei Zhang, Zhang Tao, Wei Guo","doi":"10.1109/IIP57348.2022.00020","DOIUrl":"https://doi.org/10.1109/IIP57348.2022.00020","url":null,"abstract":"In recent years, the number of domestic vehicles has been increasing, the fine management of vehicles has become more difficult, and the importance of license plate recognition technology has become increasingly prominent. The traditional license plate recognition algorithm can be effectively applied to ordinary life scenes, but it is difficult to show strong robustness in the face of complex scenes such as image distortion and blurring, and often fails to recognize the phenomenon. This paper uses YOLOv5 and LPRNet deep learning models to recognize license plates in complex scenes in real-time. The main task of the former is to locate the license plate position within the image and crop the detection frame, while the main task of the latter is to recognize the license plate characters in the detection frame. Compared with traditional license plate recognition algorithms, this method using deep learning improves the accuracy of license plate recognition. In contrast, the method has the advantages of a small model, high precision, and embeddability.","PeriodicalId":412907,"journal":{"name":"2022 4th International Conference on Intelligent Information Processing (IIP)","volume":"115 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":"121477086","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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