2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT)最新文献_第3页

Design of Approval Workflow Engine Based on Flexible Transition 基于柔性转换的审批工作流引擎设计

2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT) Pub Date : 2022-09-16 DOI: 10.1109/AICIT55386.2022.9930213

Bing-Hsuan Wu, Guohong Yi, Jianting Li, Zhichao Cao, Xiaodong Xu

引用次数: 0

Prediction method of turbine engine RUL based on GA-SVR 基于GA-SVR的涡轮发动机RUL预测方法

2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT) Pub Date : 2022-09-16 DOI: 10.1109/AICIT55386.2022.9930303

Ye Zhu, Bo Xu, Zhenjie Luo, Zhiqiang Liu, Hao Wang, C. Du

{"title":"Prediction method of turbine engine RUL based on GA-SVR","authors":"Ye Zhu, Bo Xu, Zhenjie Luo, Zhiqiang Liu, Hao Wang, C. Du","doi":"10.1109/AICIT55386.2022.9930303","DOIUrl":"https://doi.org/10.1109/AICIT55386.2022.9930303","url":null,"abstract":"The remaining life prediction of turbine engine plays an indispensable role in engine health management, which is of great significance to ensure flight safety and improve maintenance efficiency. With the development of engine health management technology, the engine is terminated before failure or failure, which makes it difficult to collect enough data with failure information. In order to improve the prediction accuracy of engine remaining life with limited data samples, a joint algorithm based on genetic algorithm and support vector regression (GA-SVR) is proposed in this paper. Genetic algorithm (GA) is used to solve the hyperparametric optimization problem in support vector regression (SVR) model. Based on the C-MAPSS public data set provided by NASA, the data of 20 engines are randomly selected to construct a small sample data set to train the GA-SVR model, and compared with other existing algorithms. The experimental results show that the prediction error of GA-SVR model is smaller in the case of small samples, It is proved that the proposed model can accurately deal with the problem of turbine engine residual life prediction in the case of small samples.","PeriodicalId":231070,"journal":{"name":"2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122219546","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

An intelligent traffic control system based on sand table 基于沙盘的智能交通控制系统

2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT) Pub Date : 2022-09-16 DOI: 10.1109/AICIT55386.2022.9930209

Lianying Zou, Tao Yuan, Wenjie Liao, Yang Zhang, Xinli Cao, Yuxin Shang

{"title":"An intelligent traffic control system based on sand table","authors":"Lianying Zou, Tao Yuan, Wenjie Liao, Yang Zhang, Xinli Cao, Yuxin Shang","doi":"10.1109/AICIT55386.2022.9930209","DOIUrl":"https://doi.org/10.1109/AICIT55386.2022.9930209","url":null,"abstract":"With the continuous improvement of the combination of computer control technology and traffic flow theory, and the continuous enhancement of traffic management methods, it is an important task for researchers to greatly improve the level of intelligent transportation in China. In view of the current needs of the development of intelligent transportation, this paper simulates the specific traffic environment in real life in combination with the simulation environment in the laboratory, and builds a smart car that meets the environmental requirements for this environment, and sets the console host computer interface as the interface. The information exchange platform between smart cars can also control the start and stop of smart cars according to the needs of users.In order to realize the system, the system designs two schemes for the behavior of smart cars: for embedded development, it uses infrared to track and RFID radio frequency card for positioning of smart cars; for image recognition, it uses residual network. Virtual tracking, and smart car behavior using AlexNet’s marker recognition. The two behaviors are aimed at the same simulated environment, and the smart car can comprehensively consider the two behaviors, so that the response to the environment is more accurate and precise. Finally, a sand table-based intelligent traffic control system is formed.","PeriodicalId":231070,"journal":{"name":"2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125275285","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

SAR Image Water Extraction Based on Saliency Target Detection 基于显著性目标检测的SAR图像水分提取

2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT) Pub Date : 2022-09-16 DOI: 10.1109/AICIT55386.2022.9930251

Peng Wang, Haibo Zhang, Qiwen Lv, Shuwei Zhao, Lei Wang

{"title":"SAR Image Water Extraction Based on Saliency Target Detection","authors":"Peng Wang, Haibo Zhang, Qiwen Lv, Shuwei Zhao, Lei Wang","doi":"10.1109/AICIT55386.2022.9930251","DOIUrl":"https://doi.org/10.1109/AICIT55386.2022.9930251","url":null,"abstract":"Synthetic aperture radar (SAR) image water extraction has important research significance in water resources monitoring and other applications. In SAR images, the scattering properties of some land cover types with low backscattering coefficients, such as broad roads and mountain shadows, are very close to the scattering properties of water. Most water extraction methods are easy to identify those false water targets as water. Meanwhile, the water area in the scene is very small, and the proportion of water and background in the training concentration is extremely unbalanced. The imbalance of water samples affects the water extraction performance. Traditional machine learning water extraction methods require manual extraction of effective features, which are time-consuming and inefficient. Therefore, we decided to introduce the deep learning-based salient object detection network Pool-Net into SRA image water extraction. To overcome the effect of class imbalance, we introduce the focus loss function into the Pool-Net network. Experimental results show that the proposed method achieves good water extraction results on water class imbalanced SAR images. The water extraction accuracy of the proposed method is 2% higher than Pool-Net and also surpasses some well-known image segmentation methods.","PeriodicalId":231070,"journal":{"name":"2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131467221","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 Integration of Large-scale Grid-connected Alkaline Electrolyzers for the Carbon-neutral Energy Systems 面向碳中和能源系统的大型并网碱性电解槽智能集成

2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT) Pub Date : 2022-09-16 DOI: 10.1109/AICIT55386.2022.9930224

Jinhui Yu, Bei Lu, Wenjing Su, Y. Zong

引用次数: 0

An Action Recgonition System Based on WiFi 基于WiFi的动作识别系统

2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT) Pub Date : 2022-09-16 DOI: 10.1109/AICIT55386.2022.9930165

Xianggang Zhang, Meina Dong, Ting Zhang

引用次数: 0

Underground Tunnel Detection in Mountainous Environment 山地环境下的地下隧道探测

2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT) Pub Date : 2022-09-16 DOI: 10.1109/AICIT55386.2022.9930295

Kechao Wang, Xiaotai Liu, Wenbing Deng, Hanyu Liu, Tianxu Zhang, Gong Wei

{"title":"Underground Tunnel Detection in Mountainous Environment","authors":"Kechao Wang, Xiaotai Liu, Wenbing Deng, Hanyu Liu, Tianxu Zhang, Gong Wei","doi":"10.1109/AICIT55386.2022.9930295","DOIUrl":"https://doi.org/10.1109/AICIT55386.2022.9930295","url":null,"abstract":"At present, most of the research on detection methods of strip-shaped underground tunnels in mountainous areas using infrared imaging technology at home and abroad adopts the method of analyzing the time-varying law of target signals based on multi-temporal infrared images. And establish a mathematical model to calculate and solve the tunnel position. Or use the microwave infrared enhancement technology to enhance the infrared image according to the mathematical model of microwave power transmission to highlight the contrast of target/background signal strength, so as to realize the detection of the location of the belt-shaped underground tunnel in the mountains. We use the heat between the mountain and the air layer. The radiation model combines the DEM data to calculate the solar radiation energy, and iteratively filters out the background heat flow field energy of the mountain. Combined with hyperspectral data, the background heat propagation energy of the mountain is calculated; the infrared remote sensing image is filtered out using the underground target inversion model. The optimal altitude and disturbance signal distribution map of the belt-shaped underground tunnel in the mountain are obtained from the background heat flow field energy of each layer of the mountain","PeriodicalId":231070,"journal":{"name":"2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129678708","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

TCNet: Temporal Consistency Network for Semisupervised Change Detection 半监督变化检测的时间一致性网络

2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT) Pub Date : 2022-09-16 DOI: 10.1109/AICIT55386.2022.9930313

Qidi Shu, Jiarui Hu, Jun Pan, Yuchuan Bai, Zhuoer Zhang, Zongrui Li

{"title":"TCNet: Temporal Consistency Network for Semisupervised Change Detection","authors":"Qidi Shu, Jiarui Hu, Jun Pan, Yuchuan Bai, Zhuoer Zhang, Zongrui Li","doi":"10.1109/AICIT55386.2022.9930313","DOIUrl":"https://doi.org/10.1109/AICIT55386.2022.9930313","url":null,"abstract":"Change detection is a challenging task in earth observation. In recent years, deep learning techniques have been widely applied in change detection and achieved impressive progress. However, deep learning based change detection methods heavily rely on a large amount of annotated samples. Labeling for change detection is a time-consuming and labor-intensive task. In order to solve this problem, we propose a novel temporal consistency network (TCNet) for semisupervised change detection. Motivated by the fact that different input sequences have no effect on the prediction results of change detection, our method learns the distribution of unlabeled data by enforce the consistency of the prediction obtained with different input sequences. Specifically, for labeled samples, two segmentation networks with the same structure are trained with two different input sequences. For the unlabeled samples, we perform the forward prediction on the two segmentation networks with corresponding input sequence to obtain two results of change detection. Then, the supervised signals can be generated by minimizing the difference between two predicted results. In this way, the distribution of unlabeled data can be fully explored thus enhancing the generalization of change detection. Experiments on google dataset show the effectiveness of the proposed method.","PeriodicalId":231070,"journal":{"name":"2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128425549","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 Intelligent Question Answering System for Chemical Safety Based on Knowledge Graph 基于知识图谱的化工安全智能问答系统研究

2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT) Pub Date : 2022-09-16 DOI: 10.1109/AICIT55386.2022.9930319

Zhenzhen Liu, Sheng Zheng, Xi Shi

{"title":"Research on Intelligent Question Answering System for Chemical Safety Based on Knowledge Graph","authors":"Zhenzhen Liu, Sheng Zheng, Xi Shi","doi":"10.1109/AICIT55386.2022.9930319","DOIUrl":"https://doi.org/10.1109/AICIT55386.2022.9930319","url":null,"abstract":"In recent years, the chemical industry has developed rapidly, and the production usage of chemical has continued to increase. In the face of variety of chemicals and ever-changing chemical reactions, people’s cognition of knowledge and damage characteristics lags behind, leading to frequent chemical accidents. For facilitating and assisting people to make reasonable judgments in daily work or when accidents happen, this paper utilizes the existing structured data of chemical safety constructs an intelligent question answering system based on knowledge graph, which is applied to chemical safety for the first time. Firstly, to deal with the problem of user intent understanding in question answering system, a multi-classifier combining NB (Naive Bayes) algorithm and Bert-BiLSTM-CRF model is constructed to complete the task of question classification. Secondly, according to the classification result, the most similar question template is matched. Finally, the semantic information of the template and the intention words in the question are mapped to the chemical safety knowledge graph to retrieve the answers. In addition, this paper utilizes SVM (Support Vector Machines) to compare the effect of question classification, and utilizes BiLSTM-CRF model to compare the effect of feature words recognition. The experimental results demonstrate that 91% of the questions are answered correctly, indicating that question answering system can answer the questions related to chemical safety in real time and accurately.","PeriodicalId":231070,"journal":{"name":"2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124797902","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 the detection of ferromagnetic objects based on the phase characteristics of industrial frequency electromagnetic fields 基于工频电磁场相位特性的铁磁物体检测研究

2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT) Pub Date : 2022-09-16 DOI: 10.1109/AICIT55386.2022.9930330

Cheng Yang, Qinghui Zhang, Tianxu Zhang

{"title":"Research on the detection of ferromagnetic objects based on the phase characteristics of industrial frequency electromagnetic fields","authors":"Cheng Yang, Qinghui Zhang, Tianxu Zhang","doi":"10.1109/AICIT55386.2022.9930330","DOIUrl":"https://doi.org/10.1109/AICIT55386.2022.9930330","url":null,"abstract":"At present, the common detection technology pathways about underwater ferromagnetic objects such as underwater cruisers, shipwrecks, submarine metallic minerals, cave banks, etc. are sonar detection, laser/radar detection, geomagnetic anomaly detection, etc. Among them, the underwater target / object echoes due to the development of silencing technology and the sea background noise is very close, so the sonar detection means face serious challenges; because of seawater has a shielding effect on high-frequency electromagnetic waves, so the laser / radar and other active emission of high-frequency electromagnetic wave detection method for deep water layer object detection is more difficult. All over the world are erected with large transmission networks of different scales, can be radiated to the surrounding space stable 50Hz/60Hz frequency electromagnetic field (wave), and the frequency of frequency electromagnetic waves by seawater and other environmental media attenuation impact is very small. Therefore, in the detection and positioning of underwater ferromagnetic objects, the industrial frequency electromagnetic field (wave) detection means will play an important role. This paper analyzes and studies the characteristics of the phase change of the interaction between the industrial frequency electromagnetic field and ferromagnetic objects, and the results show that when the industrial frequency electromagnetic field acts on the ferromagnetic object, its phase will change significantly, producing local industrial frequency electromagnetic field anomalous signal, which provides a theoretical basis for the industrial frequency electromagnetic field detection of ferromagnetic objects.","PeriodicalId":231070,"journal":{"name":"2022 International Conference on Artificial Intelligence and Computer Information Technology (AICIT)","volume":"56 12","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120907338","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