发布求助
文献互助 智能选刊 最新文献

2020 2nd International Conference on Industrial Artificial Intelligence (IAI)最新文献

筛选
英文 中文
Optimization of the traffic measurement software in CDMA mobile telecommunication CDMA移动通信中流量测量软件的优化
2020 2nd International Conference on Industrial Artificial Intelligence (IAI) Pub Date : 2020-10-23 DOI: 10.1109/IAI50351.2020.9262161
Nan He, Ce Liang
{"title":"Optimization of the traffic measurement software in CDMA mobile telecommunication","authors":"Nan He, Ce Liang","doi":"10.1109/IAI50351.2020.9262161","DOIUrl":"https://doi.org/10.1109/IAI50351.2020.9262161","url":null,"abstract":"With the continuous development of mobile communication services, market departments and network optimization departments put forward a lot of new requirements for traffic statistics, such as zoning statistical traffic, the need for histograms and pie charts such as intuitive data presentation, etc., but the original manufacturers have been unable to provide traffic statistics software to meet these needs. Aiming at these requirements, this paper applies the object-oriented design idea, utilizes the visual programming method of VB programming language, the convenience of API function calling keyboard and mouse directly, and the powerful table operation function of Access database to transform and optimize the original traffic statistics software, so as to improve the work efficiency and reduce the error rate. At the same time, it also met the needs of various departments' traffic statistics and gained favorable comments.","PeriodicalId":137183,"journal":{"name":"2020 2nd International Conference on Industrial Artificial Intelligence (IAI)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126289785","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
Multi-LSTM Networks for Accurate Classification of Attention Deficit Hyperactivity Disorder from Resting-State fMRI Data 基于静息状态fMRI数据准确分类注意缺陷多动障碍的多lstm网络
2020 2nd International Conference on Industrial Artificial Intelligence (IAI) Pub Date : 2020-10-23 DOI: 10.1109/IAI50351.2020.9262176
Rui Liu, Zhi-an Huang, Min Jiang, K. Tan
{"title":"Multi-LSTM Networks for Accurate Classification of Attention Deficit Hyperactivity Disorder from Resting-State fMRI Data","authors":"Rui Liu, Zhi-an Huang, Min Jiang, K. Tan","doi":"10.1109/IAI50351.2020.9262176","DOIUrl":"https://doi.org/10.1109/IAI50351.2020.9262176","url":null,"abstract":"Attention deficit hyperactivity disorder (ADHD) is a widespread mental disorder among young children. Due to the complex pathological mechanisms and clinical symptoms, the diagnosis of ADHD is still challenging. In this paper, we propose a novel multi-network of long short term memory (multi-LSTM) for the identification of ADHD. The Gaussian mixture model (GMM) is introduced to cluster different regions of interests (ROIs) for feature selection. Then, the data augmentation and phenotypic information are used to further improve the classification performance. The simulation experiment demonstrates that the proposed model outperforms the state-of-the-art methods based on the multi-site ADHD-200 global competition dataset. It is anticipated that the proposed ROI-based clustering method and multi-LSTM model can provide valuable insights into the auxiliary diagnosis of ADHD from the rs-fMRI signal.","PeriodicalId":137183,"journal":{"name":"2020 2nd International Conference on Industrial Artificial Intelligence (IAI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121473196","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
Table of content 目录表
2020 2nd International Conference on Industrial Artificial Intelligence (IAI) Pub Date : 2020-10-23 DOI: 10.1109/iai50351.2020.9262180
Jdse Jdse
{"title":"Table of content","authors":"Jdse Jdse","doi":"10.1109/iai50351.2020.9262180","DOIUrl":"https://doi.org/10.1109/iai50351.2020.9262180","url":null,"abstract":"","PeriodicalId":137183,"journal":{"name":"2020 2nd International Conference on Industrial Artificial Intelligence (IAI)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120907932","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
A Novel Semi-Supervised Probabilistic Model of Fisher Discriminant Analysis for Data-Driven Fault Classification and Detection 基于Fisher判别分析的半监督概率模型在数据驱动故障分类与检测中的应用
2020 2nd International Conference on Industrial Artificial Intelligence (IAI) Pub Date : 2020-10-23 DOI: 10.1109/IAI50351.2020.9262199
Xudong Yin, Huangang Wang, Chao Shang, Dexian Huang
{"title":"A Novel Semi-Supervised Probabilistic Model of Fisher Discriminant Analysis for Data-Driven Fault Classification and Detection","authors":"Xudong Yin, Huangang Wang, Chao Shang, Dexian Huang","doi":"10.1109/IAI50351.2020.9262199","DOIUrl":"https://doi.org/10.1109/IAI50351.2020.9262199","url":null,"abstract":"Fault classification and detection is an important and challenging work to ensure the efficiency and safety of modern industrial processes. Data are being generated rapidly, but most of them are fetched in normal condition, and labeling abnormal data is a time consuming and costly job; therefore, semi-supervised learning is attracting more attention. Fisher discriminant analysis (FDA) is a prevalent supervised classification method, and there is an inherent connection between FDA and the well-known Gaussian mixture model. Motivated by such a connection, we proposed a new semi-supervised classification method based on FDA. In virtue of the expectation maximization algorithm, one can obtain projection directions, means and covariance matrices of all classes, and the predicted labels of unlabeled data simultaneously. Then these information can be utilized for fault analysis, classification and online detection. The method is guaranteed to converge with an acceptable computational cost. A numerical example and Tennessee Eastman case studies are carried out to demonstrate potential advantages of the proposed method.","PeriodicalId":137183,"journal":{"name":"2020 2nd International Conference on Industrial Artificial Intelligence (IAI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129496872","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
Fixed point theorems for a class of nonlinear sum-type operators and its application to fractional q-difference equations* 一类非线性和型算子的不动点定理及其在分数阶q差分方程中的应用*
2020 2nd International Conference on Industrial Artificial Intelligence (IAI) Pub Date : 2020-10-23 DOI: 10.1109/IAI50351.2020.9262212
Xiaoxia Yang, Lingling Zhang
{"title":"Fixed point theorems for a class of nonlinear sum-type operators and its application to fractional q-difference equations*","authors":"Xiaoxia Yang, Lingling Zhang","doi":"10.1109/IAI50351.2020.9262212","DOIUrl":"https://doi.org/10.1109/IAI50351.2020.9262212","url":null,"abstract":"In this paper, we investigate the operator equation $A(x, x)+B(x, x)+C(x, x)+Dx+Ex=x$, in which A, B, C are three mixed monotone operators with different characters, D is an increasing operator, and E is a decreasing operator. The main difficulty in dealing with the sum of five operators is the proving of concavity of the sum-type operator, which produces more complexities than the sum of two or three operators. Our goal is to obtain the unique existence of positive solutions under some appropriate conditions by virtue of a fixed point theorem for mixed monotone operators. At last, we give an application to demonstrate the efficiency of our abstract result.","PeriodicalId":137183,"journal":{"name":"2020 2nd International Conference on Industrial Artificial Intelligence (IAI)","volume":"120 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132755553","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
Fuzzy adaptive integral sliding mode synchronization of a class of chaotic systems 一类混沌系统的模糊自适应积分滑模同步
2020 2nd International Conference on Industrial Artificial Intelligence (IAI) Pub Date : 2020-10-23 DOI: 10.1109/IAI50351.2020.9262181
Chunzhi Yang, Yeguo Sun, Xiangyu Wei, Hui Lv
{"title":"Fuzzy adaptive integral sliding mode synchronization of a class of chaotic systems","authors":"Chunzhi Yang, Yeguo Sun, Xiangyu Wei, Hui Lv","doi":"10.1109/IAI50351.2020.9262181","DOIUrl":"https://doi.org/10.1109/IAI50351.2020.9262181","url":null,"abstract":"Synchronization between two uncertain different chaotic systems is investigated by using adaptive fuzzy integral terminal sliding mode control. The proposed method can guarantee the convergence of the synchronization errors in some finite time. In addition, the singular problem which usually occurs in traditional sliding mode control, can also be avoided. Finally, some simulation studies are presented to show the effectiveness of the proposed method.","PeriodicalId":137183,"journal":{"name":"2020 2nd International Conference on Industrial Artificial Intelligence (IAI)","volume":"111 1-3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132042589","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
Sensitiveness Based Strategy for Network Compression 基于灵敏度的网络压缩策略
2020 2nd International Conference on Industrial Artificial Intelligence (IAI) Pub Date : 2020-10-23 DOI: 10.1109/IAI50351.2020.9262195
Yihe Lu, Kaiyuan Feng, Hao Li, Yue Wu, Maoguo Gong, Yaoting Xu
{"title":"Sensitiveness Based Strategy for Network Compression","authors":"Yihe Lu, Kaiyuan Feng, Hao Li, Yue Wu, Maoguo Gong, Yaoting Xu","doi":"10.1109/IAI50351.2020.9262195","DOIUrl":"https://doi.org/10.1109/IAI50351.2020.9262195","url":null,"abstract":"The success of convolutional neural networks has contributed great improvement on various tasks. Typically, larger and deeper networks are designed to increase performance on classification works, such as AlexNet, VGGNets, GoogleNet and ResNets, which are composed by enormous convolutional filters. However, these complicated structures constrain models to be deployed into real application due to limited computational resources. In this paper, we propose a simple method to sort the importance of each convolutional layer, as well as compressing network by removing redundant filters. There are two implications in our work: 1) Downsizing the width of unimportant layers will lead to better performance on classification tasks. 2) The random-pruning in each convolutional layer can present similar results as weight-searching algorithm, which means that structure of the network dominates its ability of representation. As a result, we reveal the property of different convolutional layers for VGG-16, customized VGG-4 and ResNet-18 on different datasets. Consequently, the importance of different convolutional layers is described as sensitiveness to compress these networks greatly.","PeriodicalId":137183,"journal":{"name":"2020 2nd International Conference on Industrial Artificial Intelligence (IAI)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129101795","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
NOMA based Efficient Spectrum Sharing for Underwater UAV System with Multi-agent Reinforcement Learning 基于多智能体强化学习的NOMA水下无人机系统高效频谱共享
2020 2nd International Conference on Industrial Artificial Intelligence (IAI) Pub Date : 2020-10-23 DOI: 10.1109/IAI50351.2020.9262162
Zhaowei Wang, Fei Qin
{"title":"NOMA based Efficient Spectrum Sharing for Underwater UAV System with Multi-agent Reinforcement Learning","authors":"Zhaowei Wang, Fei Qin","doi":"10.1109/IAI50351.2020.9262162","DOIUrl":"https://doi.org/10.1109/IAI50351.2020.9262162","url":null,"abstract":"The underwater communications have been challenged by the long propagation delay as well as the limited utilizable bandwidth. As a result, although the underwater UAV system can benefit many applications, the communication performance still works as a barrier for its wide adoption. This paper proposes the utilization of non-orthogonal frequency division multiple access to increase the efficiency of underwater UAV networks, which will ideally avoid the negative effect from long propagation time, but rise multiuser interference problem. To solve this problem, this paper model the multi-user interference as a non-cooperative game, and resort the multiagent reinforcement learning to approach the Nash Equilibrium. This method can avoid the a priori constraint of scenario information, which usually cannot be obtained in the underwater UAV communications. A simple but descriptive simulation has validated the feasibility of proposed method.","PeriodicalId":137183,"journal":{"name":"2020 2nd International Conference on Industrial Artificial Intelligence (IAI)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127693005","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
Forgetting factor multi-error stochastic gradient algorithm based on minimum error entropy 基于最小误差熵的遗忘因子多误差随机梯度算法
2020 2nd International Conference on Industrial Artificial Intelligence (IAI) Pub Date : 2020-10-23 DOI: 10.1109/IAI50351.2020.9262232
Shaoxue Jing
{"title":"Forgetting factor multi-error stochastic gradient algorithm based on minimum error entropy","authors":"Shaoxue Jing","doi":"10.1109/IAI50351.2020.9262232","DOIUrl":"https://doi.org/10.1109/IAI50351.2020.9262232","url":null,"abstract":"Entropy has been widely applied in system identification in the last decade. In this paper, a novel stochastic gradient algorithm based on minimum entropy is proposed. Though needing less computation than the mean squares error algorithm, traditional stochastic gradient algorithm converges quite slowly. To fasten the algorithm, a multi-error method and a forgetting factor are integrated into the algorithm. Firstly, the scalar error is replaced by a vector error with different error length. Secondly, a forgetting factor is adopted to calculate the step size. The proposed algorithm is utilized to estimate the parameters of a finite impulse response model. Estimation results indicate that the proposed algorithm can obtain more accurate estimates than traditional gradient algorithm and has a faster converge speed.","PeriodicalId":137183,"journal":{"name":"2020 2nd International Conference on Industrial Artificial Intelligence (IAI)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131053446","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
Consensus Control of Leader-following Multi-agent System in Partial Directed Topology 部分有向拓扑下leader -follow多智能体系统的一致性控制
2020 2nd International Conference on Industrial Artificial Intelligence (IAI) Pub Date : 2020-10-23 DOI: 10.1109/IAI50351.2020.9262229
Chunsheng Yan, Yongjian Zheng, Chuan-Guey Huang, Simeng Xue, Hongwei Sun, Xin Wang, Qinglai Wei
{"title":"Consensus Control of Leader-following Multi-agent System in Partial Directed Topology","authors":"Chunsheng Yan, Yongjian Zheng, Chuan-Guey Huang, Simeng Xue, Hongwei Sun, Xin Wang, Qinglai Wei","doi":"10.1109/IAI50351.2020.9262229","DOIUrl":"https://doi.org/10.1109/IAI50351.2020.9262229","url":null,"abstract":"In this paper, the consensus control of linear multi-agent system in partial directed topology is discussed. The key innovation of this paper is that we propose a novel consensus control by using partial directed topology with the external stochastic disturbance. Since the noise inference is unavoidable in real life, the external disturbance produced by the Gauss white noise through Brown motion is taken into account when the states of the leader and followers are described. To settle this kind of problem, a distributed controller based on Riccati inequalities with an adaptive law is designed for leader-following multi-agent systems. We give proof through Lyapunov function and get the result which is the same as the theory. Finally, a simulation example is given to support the Theorems.","PeriodicalId":137183,"journal":{"name":"2020 2nd International Conference on Industrial Artificial Intelligence (IAI)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123258303","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
首页 上一页 下一页 尾页
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整，为了账户安全，请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们：info@booksci.cn Book学术提供免费学术资源搜索服务，方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号：604180095
Book学术官方微信