2020 IEEE 3rd International Conference on Automation, Electronics and Electrical Engineering (AUTEEE)最新文献_第10页

Research on Optimal Selection of FSC Racing Muffler FSC赛车消声器的优选研究

2020 IEEE 3rd International Conference on Automation, Electronics and Electrical Engineering (AUTEEE) Pub Date : 2020-11-20 DOI: 10.1109/AUTEEE50969.2020.9315562

Liang Yi, Chang Li, Shudao Wang, Tianyi Song, Jierong Huang

引用次数: 1

Drug-protein Interaction Prediction based on Improved AdaBoost Algorithm 基于改进AdaBoost算法的药物-蛋白相互作用预测

2020 IEEE 3rd International Conference on Automation, Electronics and Electrical Engineering (AUTEEE) Pub Date : 2020-11-20 DOI: 10.1109/AUTEEE50969.2020.9315654

Wanrong Gu, Xianfen Xie, Ziye Zhang, Yijun Mao, Zaoqing Liang, Yichen He

{"title":"Drug-protein Interaction Prediction based on Improved AdaBoost Algorithm","authors":"Wanrong Gu, Xianfen Xie, Ziye Zhang, Yijun Mao, Zaoqing Liang, Yichen He","doi":"10.1109/AUTEEE50969.2020.9315654","DOIUrl":"https://doi.org/10.1109/AUTEEE50969.2020.9315654","url":null,"abstract":"The drug-protein interaction prediction can be used in the discovery of new drug effects. Recent studies often focus on the prediction with an independent matrix filling algorithm. The single-model matrix-filling algorithm has low accuracy, so it is difficult to obtain satisfactory results in the prediction of drug-protein research. The AdaBoost algorithm is an algorithm framework of a powerful classifier composed of multiple subclassifiers. Its usefulness and effectiveness has been proved in the research field of classification. The prediction of drug-protein is a matrix filling problem, which is a process of scoring prediction. Therefore, we improved the algorithm of AdaBoost. To transform the matrix filling problem into a classification problem with improved AdaBoost algorithm. The AdaBoost algorithm framework could be fully utilized to integrate multiple weak classifiers to improve prediction performance. Then we can make an accurate prediction of the drug-protein interaction. The experimental results based on the public data set show that the proposed algorithm outperforms most classical and recent algorithms in predicting accuracy. The limitation of single algorithm based on machine learning is overcome well. Our method improves the accuracy of prediction by mining the hidden factors better.","PeriodicalId":6767,"journal":{"name":"2020 IEEE 3rd International Conference on Automation, Electronics and Electrical Engineering (AUTEEE)","volume":"27 1","pages":"166-170"},"PeriodicalIF":0.0,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84348196","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

Geometric Match Filter and It’s Response to Dense Fake Signal 几何匹配滤波器及其对密集假信号的响应

2020 IEEE 3rd International Conference on Automation, Electronics and Electrical Engineering (AUTEEE) Pub Date : 2020-11-20 DOI: 10.1109/AUTEEE50969.2020.9315605

Liang Pu, Wang Min, Fan Hongqi

引用次数: 0

Output characteristics simulation analysis of PEMFC PEMFC输出特性仿真分析

2020 IEEE 3rd International Conference on Automation, Electronics and Electrical Engineering (AUTEEE) Pub Date : 2020-11-20 DOI: 10.1109/AUTEEE50969.2020.9315571

Chen Xi, Wan Qian, Peng Peipei, Chen Junhui, Yang Yajie

{"title":"Output characteristics simulation analysis of PEMFC","authors":"Chen Xi, Wan Qian, Peng Peipei, Chen Junhui, Yang Yajie","doi":"10.1109/AUTEEE50969.2020.9315571","DOIUrl":"https://doi.org/10.1109/AUTEEE50969.2020.9315571","url":null,"abstract":"Clean energy is the key to the sustainable development of society. Among various clean energy sources, the Proton Exchange Membrane Fuel Cell (PEMFC) with advantages in cleanliness and high energy conversion efficiency is attracting more and more attention. In this paper, the mathematical model of PEMFC is established based on a semiempirical method to study the influence of key parameters and phenomenon, namely membrane water content, air pressure intensity, reaction temperature, and “charged double layer” phenomenon, on the output characteristics of PEMFC. The dynamic and steady-state simulation of PEMFC output characteristics is carried out under Matlab/Simulink Simulation results show that the output characteristics of a single fuel cell model built in this paper are consistent with the products of Powercell Company, which verifies the correctness of the modeling method in this paper. Furthermore, analysis shows the fuel cell performance can significantly improve by improving the external operating conditions. More importantly, the PEMFC model and output characteristics analysis can provide theoretical guidance for the design of control strategy.","PeriodicalId":6767,"journal":{"name":"2020 IEEE 3rd International Conference on Automation, Electronics and Electrical Engineering (AUTEEE)","volume":"94 1","pages":"253-258"},"PeriodicalIF":0.0,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74240964","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

Optimal Planning of Battery Storage for Flexible HVDC Network with Pumped Storage Hydropower Plants 带抽水蓄能电站的柔性高压直流电网电池储能优化规划

2020 IEEE 3rd International Conference on Automation, Electronics and Electrical Engineering (AUTEEE) Pub Date : 2020-11-20 DOI: 10.1109/AUTEEE50969.2020.9315700

Minjian Cao, Huan Xie, Yifan Song, F. Cai, Shanying Li, X. Xia, Zechun Hu

{"title":"Optimal Planning of Battery Storage for Flexible HVDC Network with Pumped Storage Hydropower Plants","authors":"Minjian Cao, Huan Xie, Yifan Song, F. Cai, Shanying Li, X. Xia, Zechun Hu","doi":"10.1109/AUTEEE50969.2020.9315700","DOIUrl":"https://doi.org/10.1109/AUTEEE50969.2020.9315700","url":null,"abstract":"With the development of energy storage technology, battery energy storage system (BESS) and pumped storage hydropower plants (PSHP) with variable-speed units are promising technologies to provide flexibility for the power system with increasing renewable power generation. This paper proposes an approach for optimal siting and sizing of BESS to further promote the renewable energy accommodation and reduce the total investment and operation cost in a flexible high voltage direct current (HVDC) network with a PSHP. To consider the uncertainties of renewable energy generation and load at the planning stage, typical scenarios are generated by the K-means clustering method. Thereafter, the BESS planning problem is formulated as an optimization problem considering the typical scenarios. Then, the optimization problem is relaxed into a mixed-integer second-order cone programming (MISOCP) model. The proposed method is applied to calculate the optimal BESS allocation scheme for the 4-bus flexible HVDC network in North, China. Sensitivity analysis is performed to investigate the influence of the BESS cost and the electricity price on the optimal planning results.","PeriodicalId":6767,"journal":{"name":"2020 IEEE 3rd International Conference on Automation, Electronics and Electrical Engineering (AUTEEE)","volume":"20 1","pages":"233-238"},"PeriodicalIF":0.0,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82880555","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

The epoxy packaging materials modified by flexible monohydroxy polyether chain for high frequency power transformer 柔性单羟基聚醚链改性的高频电力变压器用环氧封装材料

2020 IEEE 3rd International Conference on Automation, Electronics and Electrical Engineering (AUTEEE) Pub Date : 2020-11-20 DOI: 10.1109/AUTEEE50969.2020.9315631

Kun Wang, Wei Yang, Yun Chen, Chong Zhang, L. Yin, Xin Chen, Yushun Zhao, Yu He

引用次数: 0

Research on Lamb wave resonator and its applications 兰姆波谐振器及其应用研究

2020 IEEE 3rd International Conference on Automation, Electronics and Electrical Engineering (AUTEEE) Pub Date : 2020-11-20 DOI: 10.1109/AUTEEE50969.2020.9315594

Leyi Wang

引用次数: 0

The Experimental Technique and Practical Scheme of Intelligent Switch in Power Distribution IoT 配电物联网中智能开关的实验技术与实现方案

2020 IEEE 3rd International Conference on Automation, Electronics and Electrical Engineering (AUTEEE) Pub Date : 2020-11-20 DOI: 10.1109/AUTEEE50969.2020.9315687

Zhi Li, Haihong Li, Shaofeng Yu, Gang Wu, Yibo Gao, Yifang Su

引用次数: 2

Algorithms for Basis Sparsity Non-negative Matrix Factorization 基稀疏性非负矩阵分解算法

2020 IEEE 3rd International Conference on Automation, Electronics and Electrical Engineering (AUTEEE) Pub Date : 2020-11-20 DOI: 10.1109/AUTEEE50969.2020.9315568

Dan Zhou, Qiaochan Yu, Jie Wen

引用次数: 0

Multi-Scale Hybrid Attention Cascade Network for Pancreas Segmentation 胰腺分割的多尺度混合注意级联网络

2020 IEEE 3rd International Conference on Automation, Electronics and Electrical Engineering (AUTEEE) Pub Date : 2020-11-20 DOI: 10.1109/AUTEEE50969.2020.9315540

Xirui Zhang, Jun Wu, Shangyong Fan, Ming Li, Gang Yuan, Yin Zhang, Zhaobang Liu

{"title":"Multi-Scale Hybrid Attention Cascade Network for Pancreas Segmentation","authors":"Xirui Zhang, Jun Wu, Shangyong Fan, Ming Li, Gang Yuan, Yin Zhang, Zhaobang Liu","doi":"10.1109/AUTEEE50969.2020.9315540","DOIUrl":"https://doi.org/10.1109/AUTEEE50969.2020.9315540","url":null,"abstract":"The shape of pancreas in different patients is very different and the boundary is fuzzy, so the reliable automatic segmentation of pancreas is an important and difficult task. In this paper, we propose a multi-scale hybrid attention cascade network for challenging pancreas segmentation. First, the original CT images are coarsely segmented through the first-level network, then, the coarse segmentation results are clipped and sent to the second-level network for further training to obtain the fine segmentation results. The network adopts full convolutional network (FCN) integrating multi-scale mixed attention. The cut CT image eliminates the irrelevant background interference and reduces the input size of the secondary network, thus improving the segmentation accuracy. An extensive evaluation of 82 open data sets was performed by quadruple cross validation. The experimental results showed that the Dice coefficient was 84.62±4.20% compared with several advanced methods. In addition, this method has excellent performance in three measurement indexes of precision, Jaccard and recall.","PeriodicalId":6767,"journal":{"name":"2020 IEEE 3rd International Conference on Automation, Electronics and Electrical Engineering (AUTEEE)","volume":"9 1","pages":"277-281"},"PeriodicalIF":0.0,"publicationDate":"2020-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81174498","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