2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)最新文献_第9页

Eddy Current Sensor (ECS) based Derailment Feature Analysis in Molten Iron Transportation 基于涡流传感器的铁水运输脱轨特征分析

2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) Pub Date : 2019-12-01 DOI: 10.1109/IAEAC47372.2019.8997784

Xianyong Zhang, Hongbin Yang, E. Sun

引用次数: 0

Relation Classification via CNNs with Attention Mechanism for Multi-Window-Sized Kernels 基于关注机制的多窗口核cnn关系分类

2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) Pub Date : 2019-12-01 DOI: 10.1109/IAEAC47372.2019.8997966

Xiao Huang, J. Lin, Wei Teng, Yanxiang Bao

{"title":"Relation Classification via CNNs with Attention Mechanism for Multi-Window-Sized Kernels","authors":"Xiao Huang, J. Lin, Wei Teng, Yanxiang Bao","doi":"10.1109/IAEAC47372.2019.8997966","DOIUrl":"https://doi.org/10.1109/IAEAC47372.2019.8997966","url":null,"abstract":"Relation classification is an important ingredient task in the construction of knowledge graph, question answering system and numerous other natural language processing (NLP) tasks. With the application of deep neural networks (DNNs) such as recurrent neural networks (RNNs) and convolutional neural networks (CNNs), relation classification task has achieved satisfactory results. However, many proposed models can not take well advantages of multiple window sizes for filters in CNNs and finally hurt the performance of this task. Moreover, unlike public and general dataset that has a large quantity of instances from natural languages or daily conversations, the performances of many deep neural networks with high complexity are not well enough for a small corpus in specific fields. To work out these problems, we propose a novel CNN model with attention mechanism for multi-window-sized kernels to capture the most important information and test our system not only on a general dataset of SemEval 2010 but also on a small dataset built from Chinese fundamentals of electric circuits textbook artificially. The experimental results show that our system outperforms the baseline systems for the SemEval 2010 relation classification task and validate the effectiveness of CNN on the specific Chinese small corpus relation classification task.","PeriodicalId":164163,"journal":{"name":"2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126356515","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

Towards Computer-Aided Sign Language Recognition Technique: A Directional Review 计算机辅助手语识别技术:方向综述

2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) Pub Date : 2019-12-01 DOI: 10.1109/IAEAC47372.2019.8997571

Liwei Yang, Yiduo Zhu, Tao Li

引用次数: 4

Application of Discrete Whale Optimization Hybrid Algorithm in Multiple Travelling Salesmen Problem 离散鲸鱼优化混合算法在多重旅行推销员问题中的应用

2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) Pub Date : 2019-12-01 DOI: 10.1109/IAEAC47372.2019.8997568

Jingnan Li, Meilong Le

引用次数: 3

Adaptive back-stepping tracking control of the hypersonic vehicle with input saturation 输入饱和的高超声速飞行器自适应反演跟踪控制

2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) Pub Date : 2019-12-01 DOI: 10.1109/IAEAC47372.2019.8997697

Chuanming Li, Jing-Guang Sun, Yong Guo

引用次数: 1

MetroNet: A Novel Data-Driven Fault Diagnosis Method Applied to Wheel Bearings of Metro Trains MetroNet:一种应用于地铁列车车轮轴承的数据驱动故障诊断方法

2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) Pub Date : 2019-12-01 DOI: 10.1109/IAEAC47372.2019.8997576

Hongchao Wang, Hongsheng Chen, D. Gao, Weiting Zhang

{"title":"MetroNet: A Novel Data-Driven Fault Diagnosis Method Applied to Wheel Bearings of Metro Trains","authors":"Hongchao Wang, Hongsheng Chen, D. Gao, Weiting Zhang","doi":"10.1109/IAEAC47372.2019.8997576","DOIUrl":"https://doi.org/10.1109/IAEAC47372.2019.8997576","url":null,"abstract":"The wheel bearing is a vital component of metro train, therefore, the fault diagnosis of wheel bearing is essential to ensure the reliability and safety. In recent years, some intelligent fault diagnosis algorithms have been proposed and achieved great success. However, to validate the performance of the proposed model, most researches only focus on several public datasets because of the limitation of data acquisition, which easily leads to inconsistent diagnosis after transferring the trained model to the real industrial scene. Therefore, this paper proposes an excellent method to implement data acquisition in industrial scenes. Based on data augmentation, we totally created the dataset with 40000 samples. Aiming at the training data, this paper proposes a novel data-driven fault diagnosis model named MetroNet that is applied to wheel bearings of metro trains. Notably, MetroNet is mainly constructed by CNN and RNN, and it can capture temporal correlation and spatial correlation of raw sensor data. Furthermore, the CNN adopts an innovation method of convolution over height and pooling over weight. The performance of MetroNet is evaluated on the testing dataset, and the optimal accuracy of fault diagnosis can be increased to 97.20%.","PeriodicalId":164163,"journal":{"name":"2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116112754","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 Intelligent Question Answering System Based on Medical Knowledge Graph 基于医学知识图的智能问答系统研究

2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) Pub Date : 2019-12-01 DOI: 10.1109/IAEAC47372.2019.8997728

Qianjun Shuai, Mingjie Wei, Fang Miao, Libiao Jin

引用次数: 3

Research on the Method of Convolutional Neural Network in Oil Well Drawing 卷积神经网络在油井绘图中的应用研究

2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) Pub Date : 2019-12-01 DOI: 10.1109/IAEAC47372.2019.8997616

Yu Chai, Ning Yin, Zhigang Tang, Dailu Zhang

引用次数: 0

A RRT*FN Based Path Replanning Algorithm 基于RRT*FN的路径重规划算法

2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) Pub Date : 2019-12-01 DOI: 10.1109/IAEAC47372.2019.8997746

Baiming Tong, Qingbao Liu, Chaofan Dai

引用次数: 7

The Improvement Research of Gyroscope Temperature Control Based on self-Adaptive ANN 基于自适应神经网络的陀螺仪温度控制改进研究

2019 IEEE 4th Advanced Information Technology, Electronic and Automation Control Conference (IAEAC) Pub Date : 2019-12-01 DOI: 10.1109/IAEAC47372.2019.8997717

Weilun Chen, Gongcai Xin

引用次数: 2