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2020 IEEE 9th Joint International Information Technology and Artificial Intelligence Conference (ITAIC)最新文献

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Noise Signal Simulation Method of Underwater Mobile Vehicle 水下移动机器人噪声信号仿真方法
2020 IEEE 9th Joint International Information Technology and Artificial Intelligence Conference (ITAIC) Pub Date : 2020-12-11 DOI: 10.1109/ITAIC49862.2020.9339079
Gang Yang, Zhizhong Li, Xianwen He
{"title":"Noise Signal Simulation Method of Underwater Mobile Vehicle","authors":"Gang Yang, Zhizhong Li, Xianwen He","doi":"10.1109/ITAIC49862.2020.9339079","DOIUrl":"https://doi.org/10.1109/ITAIC49862.2020.9339079","url":null,"abstract":"In the conventional matched field processing, the influence of sound source motion is usually ignored, but in fact, the motion of sound source will cause the change of amplitude and phase of multi receiving sound field. If the simulation of simulation field can be improved to take into account the time relationship between signal, source velocity and displacement, the influence of motion on sound field can be introduced into MFP. On the basis of predecessors, this paper presents a simulation method of underwater vehicle noise signal when the receiving and transmitting points have relative motion, which provides a new idea for copy field calculation in passive location of moving sound source matching field.","PeriodicalId":300389,"journal":{"name":"2020 IEEE 9th Joint International Information Technology and Artificial Intelligence Conference (ITAIC)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115694886","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
Thinking on the Application of Big Data in Fault Diagnosis of Military Equipment 大数据在军事装备故障诊断中的应用思考
2020 IEEE 9th Joint International Information Technology and Artificial Intelligence Conference (ITAIC) Pub Date : 2020-12-11 DOI: 10.1109/ITAIC49862.2020.9339172
Ting Wang, Xueke Wang, Hongwei Qu, Jingtao Zhang
{"title":"Thinking on the Application of Big Data in Fault Diagnosis of Military Equipment","authors":"Ting Wang, Xueke Wang, Hongwei Qu, Jingtao Zhang","doi":"10.1109/ITAIC49862.2020.9339172","DOIUrl":"https://doi.org/10.1109/ITAIC49862.2020.9339172","url":null,"abstract":"In recent years, the updating speed of military is accelerating, and the level of technology and complexity is improving, the traditional fault diagnosis technology has been unable to meet the needs of fault diagnosis for large complex military. With the development of big data technology, the application of big data technology to the fault diagnosis of military equipment is of great significance to the maintenance of military equipment. First, the paper introduces the concept and application of big data, then analyzes the problems faced by the fault diagnosis of military equipment are analyzed, and the advantages of fault diagnosis based on big data, as well as the technical methods of big data used in military equipment fault diagnosis. Finally, puts forward the problems that need to be saved in big data application.","PeriodicalId":300389,"journal":{"name":"2020 IEEE 9th Joint International Information Technology and Artificial Intelligence Conference (ITAIC)","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114677585","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
Analysis of Efficiency of Inductively Coupled Wireless Power Transfer Structures 感应耦合无线电力传输结构效率分析
2020 IEEE 9th Joint International Information Technology and Artificial Intelligence Conference (ITAIC) Pub Date : 2020-12-11 DOI: 10.1109/ITAIC49862.2020.9339028
Qingpu Meng, Fuguang Huo, Song Teng, Zushan Ding, Tun Gu, Chuang Cao
{"title":"Analysis of Efficiency of Inductively Coupled Wireless Power Transfer Structures","authors":"Qingpu Meng, Fuguang Huo, Song Teng, Zushan Ding, Tun Gu, Chuang Cao","doi":"10.1109/ITAIC49862.2020.9339028","DOIUrl":"https://doi.org/10.1109/ITAIC49862.2020.9339028","url":null,"abstract":"The inductively coupled wireless power transfer (WPT) resonance compensation structure includes four basic structures. In this paper, the efficiency characteristics of the inductively coupled wireless power transfer system are studied from the perspective of the equivalent circuit model of the resonant compensation structure. The equivalent circuit models of the four compensation structures are established respectively. The influences of four structures coupling coefficients and quality factors on the transmission efficiency are analyzed. Theoretical analysis shows that the secondary side resonance compensation structure has greater influence on the efficiency characteristics of the system. Compared with the secondary side series resonance compensation mode, the system has a wider high transmission efficiency range when the secondary side employs parallel resonance compensation. The experimental platform of the secondary side series and parallel resonance compensation structure are built respectively. The efficiency characteristics of the two secondary side compensation structures are compared experimentally to verify the theoretical analysis and simulation results.","PeriodicalId":300389,"journal":{"name":"2020 IEEE 9th Joint International Information Technology and Artificial Intelligence Conference (ITAIC)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116678127","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
Earthquake prediction based on Bi-LSTM+CRF model and Spatio-Temporal Data 基于Bi-LSTM+CRF模型和时空数据的地震预测
2020 IEEE 9th Joint International Information Technology and Artificial Intelligence Conference (ITAIC) Pub Date : 2020-12-11 DOI: 10.1109/ITAIC49862.2020.9339192
Zhittong Su, Qian Zhang
{"title":"Earthquake prediction based on Bi-LSTM+CRF model and Spatio-Temporal Data","authors":"Zhittong Su, Qian Zhang","doi":"10.1109/ITAIC49862.2020.9339192","DOIUrl":"https://doi.org/10.1109/ITAIC49862.2020.9339192","url":null,"abstract":"The destructiveness of earthquakes is self-evident. An earthquake not only brought irreversible disasters to the local people, but also brought great economic losses to the country. Therefore, earthquake prediction is a very necessary task. This study uses multiple Bi-LSTM models to predict different information of an earthquake from multiple dimensions: including time information, latitude and longitude information, magnitude information, etc., and finally integrated them together, so as to avoid displaying only one dimension of earthquake information. It can show the earthquake situation more comprehensively. For every two adjacent earthquake information, we use the method of taking the difference to train and predict the model, so that the model can extract the law between the data more correctly.","PeriodicalId":300389,"journal":{"name":"2020 IEEE 9th Joint International Information Technology and Artificial Intelligence Conference (ITAIC)","volume":"56 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120810888","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
Image Recognition based on Convolution Neural Network 基于卷积神经网络的图像识别
2020 IEEE 9th Joint International Information Technology and Artificial Intelligence Conference (ITAIC) Pub Date : 2020-12-11 DOI: 10.1109/ITAIC49862.2020.9339197
Xin Hu, Hua Ouyang, Yang-hua Yin
{"title":"Image Recognition based on Convolution Neural Network","authors":"Xin Hu, Hua Ouyang, Yang-hua Yin","doi":"10.1109/ITAIC49862.2020.9339197","DOIUrl":"https://doi.org/10.1109/ITAIC49862.2020.9339197","url":null,"abstract":"This paper introduces the development of image recognition technology, summarizes several classic traditional algorithms, and then introduces the use of convolution neural network for image recognition, and summarizes the application and development of CNN in various fields in recent years, and proposes to recognize images by deep learning in complex or high-risk environment similar to substation Don’t take the place of manpower to detect the working state of instruments and equipment, which has a development prospect. In the end, it puts forward some suggestions on the direction of image recognition using deep learning. In the future, we need to improve and optimize the model, intelligent algorithm and data set.","PeriodicalId":300389,"journal":{"name":"2020 IEEE 9th Joint International Information Technology and Artificial Intelligence Conference (ITAIC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121338434","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: 5
Noise Reduction Algorithm for Communication based on Improved Generative Adversarial Network 基于改进生成对抗网络的通信降噪算法
2020 IEEE 9th Joint International Information Technology and Artificial Intelligence Conference (ITAIC) Pub Date : 2020-12-11 DOI: 10.1109/ITAIC49862.2020.9338888
Gang Liu, Yuzhong Jiang, Sicheng Yang
{"title":"Noise Reduction Algorithm for Communication based on Improved Generative Adversarial Network","authors":"Gang Liu, Yuzhong Jiang, Sicheng Yang","doi":"10.1109/ITAIC49862.2020.9338888","DOIUrl":"https://doi.org/10.1109/ITAIC49862.2020.9338888","url":null,"abstract":"There are many researches on noise suppression of traditional noise suppression algorithms, and the suppression effect has reached the bottleneck. Now the widely studied artificial intelligence algorithm provides a new idea for very low frequency (VLF) communication noise reduction in ocean navigation. The generative adversarial network is introduced into the noise interference suppression algorithm.Based on the improved generative adversarial network model, the VLF noise interference suppression algorithm is studied. The generation model with strong learning ability is used to improve the accuracy of expected signal frequency estimation in the spectrum of noisy signal, and further improve the signal-to-noise (SNR) ratio in the signal bandwidth. The experimental results show that, by training the generative adversarial network, the received signals in the direction of - 45° to 45° of the receiving antenna show good noise reduction effect, and the accuracy rate can reach above 90%.","PeriodicalId":300389,"journal":{"name":"2020 IEEE 9th Joint International Information Technology and Artificial Intelligence Conference (ITAIC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121342233","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 relationship between Covid-19 epidemic and gold price trend based on Linear Regression Model 基于线性回归模型的新冠肺炎疫情与金价走势关系研究
2020 IEEE 9th Joint International Information Technology and Artificial Intelligence Conference (ITAIC) Pub Date : 2020-12-11 DOI: 10.1109/ITAIC49862.2020.9338828
Yu Jianyi, W. Chenyang, He Yupeng, L. Zicheng
{"title":"Research on the relationship between Covid-19 epidemic and gold price trend based on Linear Regression Model","authors":"Yu Jianyi, W. Chenyang, He Yupeng, L. Zicheng","doi":"10.1109/ITAIC49862.2020.9338828","DOIUrl":"https://doi.org/10.1109/ITAIC49862.2020.9338828","url":null,"abstract":"Under the influence of COVID-19, the stock market had a huge shock, and the US stock market had been blown up many times, and the Dow Jones index once fell by 3000 points. Global investors’ concerns about economic and political uncertainties continue to rise. There was a strong risk aversion sentiment in the market, and risk assets such as the stock market and crude oil were sold off by a large margin. The influx of safe-haven funds into the gold market has pushed gold prices higher. At the same time, central banks have launched monetary easing policies to stimulate the economy, which has led to the devaluation of paper money, pushing the gold price to its historical high since 2011. In disaster-prone 2020, studying the trend of gold price can provide strong support for correctly judging the world situation. As the biggest black swan event in 2020, the Covid-19 epidemic has a direct and important impact on the trend of gold prices. Therefore, it is extremely necessary to explore the relationship between the new crown epidemic and the trend of gold price. In this paper, the trend of the gold price, the daily cumulative number of confirmed cases, the cumulative number of deaths, and the cumulative number of cures during the period from 1/22 to 9/23 are selected as data sets. From the existing data and demand, it is not difficult to see that each characteristic data of the new epidemic situation and the trend of the gold prices are available, which is a regression problem to predict the continuous value. Therefore, this paper chooses a linear regression model to fit the relationship between COVID-19 and gold price trends.","PeriodicalId":300389,"journal":{"name":"2020 IEEE 9th Joint International Information Technology and Artificial Intelligence Conference (ITAIC)","volume":"2243 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127471075","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: 2
Power entity identification method in cloud environment 云环境下电力实体识别方法
2020 IEEE 9th Joint International Information Technology and Artificial Intelligence Conference (ITAIC) Pub Date : 2020-12-11 DOI: 10.1109/ITAIC49862.2020.9338956
Wanwan Cao, Mengchen Cai, Hang Cheng, Shang Wu
{"title":"Power entity identification method in cloud environment","authors":"Wanwan Cao, Mengchen Cai, Hang Cheng, Shang Wu","doi":"10.1109/ITAIC49862.2020.9338956","DOIUrl":"https://doi.org/10.1109/ITAIC49862.2020.9338956","url":null,"abstract":"The power industry is accelerating the migration of business systems to the cloud. The knowledge graph in the cloud environment can describe the concepts, entities and relationships in massive data in a structured form, and has the ability to understand, organize and manage massive amounts of information more efficiently. The recognition of named entities is a basic technology. This paper proposes an entity recognition method. This method is based on a two-way long and short-term memory neural network, learns the long-term dependence information of the word vector sequence with the help of part of speech features, and then inputs a conditional random field to generate the global optimal sequence. Experiments show that this method is better than many traditional methods when performing named entity recognition on power corpus data. This method can not only lay a foundation for further construction of knowledge graphs and data mining systems, but also has certain reference significance for researchers and engineers in other fields.","PeriodicalId":300389,"journal":{"name":"2020 IEEE 9th Joint International Information Technology and Artificial Intelligence Conference (ITAIC)","volume":"332 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124685768","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
GLAGAN image inpainting algorithm based on global and local consistency 基于全局和局部一致性的GLAGAN图像绘制算法
2020 IEEE 9th Joint International Information Technology and Artificial Intelligence Conference (ITAIC) Pub Date : 2020-12-11 DOI: 10.1109/ITAIC49862.2020.9339126
Xiaoli Li, Shuailing Zhou
{"title":"GLAGAN image inpainting algorithm based on global and local consistency","authors":"Xiaoli Li, Shuailing Zhou","doi":"10.1109/ITAIC49862.2020.9339126","DOIUrl":"https://doi.org/10.1109/ITAIC49862.2020.9339126","url":null,"abstract":"Image inpainting is an important part in the field of image processing, and its purpose is to complete the damaged area according to the pixel information not lost in the image. At present, although the image inpainting algorithm based on deep learning can repair the missing area, there are still problems that the effective information of the far area cannot be obtained, and the edge of the repair area is blurred or even distorted. In view of the above problems, this paper proposes a GLAGAN image inpainting algorithm based on global and local consistency, so that the repaired image can be semantically consistent globally and locally. In the generation network, the dilated convolution is used to initially repair the missing area, and the cross attention module is used to obtain the correlation between the repaired area and the known area, and the feature weight is calculated to further repair the damaged image. Then through the global discriminator and local discriminator to conduct adversarial training to improve the consistency of the image repair results. Experimental results show that the repair effect of the algorithm is more real and natural, and it has been further improved in both subjective evaluation and objective evaluation.","PeriodicalId":300389,"journal":{"name":"2020 IEEE 9th Joint International Information Technology and Artificial Intelligence Conference (ITAIC)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124888237","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
Research on Network Topology Model of Tactical Communication System 战术通信系统网络拓扑模型研究
2020 IEEE 9th Joint International Information Technology and Artificial Intelligence Conference (ITAIC) Pub Date : 2020-12-11 DOI: 10.1109/ITAIC49862.2020.9339000
Yuan Wei, Fan Wu
{"title":"Research on Network Topology Model of Tactical Communication System","authors":"Yuan Wei, Fan Wu","doi":"10.1109/ITAIC49862.2020.9339000","DOIUrl":"https://doi.org/10.1109/ITAIC49862.2020.9339000","url":null,"abstract":"In this paper, the characteristics of tactical communication system’s network topology structure are analyzed firstly, such as flexible node networking, multiplechannel transmission and hierarchical distribution mode, which are taken as the basic requirements of network topology model construction. And then the system connection matrix and network path function, which form the network topology model of tactical communication system, are constructed by graph theory. It can effectively solve the problem of designing optimal routing tactical communications business. Finally the feasibility of the model is verified item by item according to the network topology characteristics, which provides reference for the establishment of simulation model of tactical communication system.","PeriodicalId":300389,"journal":{"name":"2020 IEEE 9th Joint International Information Technology and Artificial Intelligence Conference (ITAIC)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123255721","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: 3
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