2018 5th International Conference on Systems and Informatics (ICSAI)最新文献_第7页

Multi-Step wind power forecasting model Using LSTM networks, Similar Time Series and LightGBM 基于LSTM网络、相似时间序列和LightGBM的多步风电预测模型

2018 5th International Conference on Systems and Informatics (ICSAI) Pub Date : 2018-11-01 DOI: 10.1109/ICSAI.2018.8599498

Yukun Cao, Liai Gui

引用次数: 20

Cultivating Computational Thinking Among Students Of Liberal Art In Basic Computer Courses 在计算机基础课程中培养文科学生的计算思维

2018 5th International Conference on Systems and Informatics (ICSAI) Pub Date : 2018-11-01 DOI: 10.1109/ICSAI.2018.8599435

Li Chen, Jiaoxiong Xia, Jie Tao

引用次数: 0

A Nonintersecting Multipath Routing Protocol for Wireless Sensor Networks 无线传感器网络的非相交多路径路由协议

2018 5th International Conference on Systems and Informatics (ICSAI) Pub Date : 2018-11-01 DOI: 10.1109/ICSAI.2018.8599450

Fu Wang, Qinggang Su

引用次数: 3

Analysis of the Health Status of Railway Vehicle Bearings Based on Improved HDP-HMM 基于改进HDP-HMM的轨道车辆轴承健康状态分析

2018 5th International Conference on Systems and Informatics (ICSAI) Pub Date : 2018-11-01 DOI: 10.1109/ICSAI.2018.8599488

Zaidong Sun, Ning Zhang

{"title":"Analysis of the Health Status of Railway Vehicle Bearings Based on Improved HDP-HMM","authors":"Zaidong Sun, Ning Zhang","doi":"10.1109/ICSAI.2018.8599488","DOIUrl":"https://doi.org/10.1109/ICSAI.2018.8599488","url":null,"abstract":"In order to solve the problem that state number of the hidden Markov model (HMM) must be specified in advance and the convergence result of HDP-HMM is sensitive to hyperparameters, a bearing health status analysis model based on improved HDP-HMM is proposed in this paper. Based on the Hierarchical Dirichlet Process (HDP) and Hidden Markov Models, the model uses the nonparametric properties of the hierarchical Dirichlet process to infer the number of hidden states, compensates for the defects of HMM, and utilizes Bayesian Optimization and Mann-Kendall criteria optimize its hyperparameters. At the same time, considering the ergodic topology of the traditional HDP-HMM is not suitable for the timing monitoring data of the bearings, we convert the HDPHMM topology into a left-to-right mode, which is more suitable for the needs of health status analysis. In addition, taking the nonlinear characteristics of the performance degradation process of railway vehicle bearings into consideration, we use GKPCA (greedy kernel principal components analysis) to extract features of bearing degradation. Finally, the model is verified by using the monitoring data collected during the train running such as the bearing temperatures. The experimental results show that the proposed HDP-HMM can effectively identify multiple health status of the railway vehicle bearings and has reliable performance. It provides an important basis for the state repair of the railway vehicles bearings under actual conditions.","PeriodicalId":375852,"journal":{"name":"2018 5th International Conference on Systems and Informatics (ICSAI)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115668785","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

The Role of Agent Technologies in Personalized Medicine 代理技术在个性化医疗中的作用

2018 5th International Conference on Systems and Informatics (ICSAI) Pub Date : 2018-11-01 DOI: 10.1109/ICSAI.2018.8599421

M. Ivanović, M. Semnic

{"title":"The Role of Agent Technologies in Personalized Medicine","authors":"M. Ivanović, M. Semnic","doi":"10.1109/ICSAI.2018.8599421","DOIUrl":"https://doi.org/10.1109/ICSAI.2018.8599421","url":null,"abstract":"Enormous rapid development of Information Communication Technologies (ICT), but also other closely related domains essentially and immensely changed human society and everyday life especially in last decade. Comparing to 20 or 30 years ago life in modern, highly developed societies almost has been completely changed influenced by technological and science innovations and applications in all domains of human life. Supported by ICT, especially fast developing rather new technologies and concepts like Internet of Things (IoT), Internet of Everything (IoE), Smart environments SE), Smart and mobile devices, and soon, Medicine, Healthcare and medical areas faced essential shift ahead. On the other hand, society goes toward an ageing global population caused by remarkable gains in life expectancy. Also, there exist wide range of different activities and unpredictable situations that cause, even within young population, a significant number of disabled people who needs adequate medical support and treatment. Aa a consequence of such situation wide range of stakeholders, research communities, governments, and policy makers invest serious efforts to support development of smart and intelligent environments, ambient assisted living to facilitate independent living of old and disabled population. One of extremely promising Artificial Intelligence (AI) fields that can offer numerous solutions for solving these problems is Agent Technology.","PeriodicalId":375852,"journal":{"name":"2018 5th International Conference on Systems and Informatics (ICSAI)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115388372","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: 9

Research on Sequential Prediction Model for Gas Pipeline Pressure Value Based on Spatial Correlation 基于空间相关性的输气管道压力值序列预测模型研究

2018 5th International Conference on Systems and Informatics (ICSAI) Pub Date : 2018-11-01 DOI: 10.1109/ICSAI.2018.8599449

Haoran Sun, Zhanquan Wang, Jiechao Yu

{"title":"Research on Sequential Prediction Model for Gas Pipeline Pressure Value Based on Spatial Correlation","authors":"Haoran Sun, Zhanquan Wang, Jiechao Yu","doi":"10.1109/ICSAI.2018.8599449","DOIUrl":"https://doi.org/10.1109/ICSAI.2018.8599449","url":null,"abstract":"Pipeline failure is the most common condition in gas pipeline networks. It is directly reflected in the abnormal pressure values in pipelines. To solve this problem, it is very important to scientifically predict the abnormal pressure of the gas network in a certain period of time in the future. This paper presents a sequential prediction model for gas pipeline pressure using Gradient Boosting Regression Tree as its primary function, which is termed as sequential GBRT(SGBRT). In SGBRT, a series of GBRTs are connected sequentially to extend the lead time of forecast, each of them taking a forecast value from an immediate preceding GBRT as input. The output of each GBRT is modified by adding an expected value of error so that the residual variance of the forecast series is minimized. In addition, through the spatial correlation analysis of the pipeline network, the study excavates the dependence between pressure value of different parts of the pipeline, so that the input features of the model are extended. The experimental results show that the prediction model is correct and effective, which improves the prediction accuracy of gas pipeline pressure value.","PeriodicalId":375852,"journal":{"name":"2018 5th International Conference on Systems and Informatics (ICSAI)","volume":"2019 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114661735","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

Prediction of Passive Sonar Detection Range in Different Detection Probability 不同探测概率下被动声呐探测距离的预测

2018 5th International Conference on Systems and Informatics (ICSAI) Pub Date : 2018-11-01 DOI: 10.1109/ICSAI.2018.8599352

Yinghua Guo, R. Ai, Yingchun Chen, Yali Qi

引用次数: 4

A Convolutional Encoder-Decoder Architecture for Retinal Blood Vessel Segmentation in Fundus Images 眼底图像中视网膜血管分割的卷积编解码器结构

2018 5th International Conference on Systems and Informatics (ICSAI) Pub Date : 2018-11-01 DOI: 10.1109/ICSAI.2018.8599380

Yiqin Lu, Yeping Zhou, Jiancheng Qin

引用次数: 2

A System for Measuring the Printing and Coating Thickness of Iron Sheet Based on Eddy Current Sensor 一种基于涡流传感器的铁皮印刷和涂层厚度测量系统

2018 5th International Conference on Systems and Informatics (ICSAI) Pub Date : 2018-11-01 DOI: 10.1109/ICSAI.2018.8599494

Yang Bo

引用次数: 0

Design and Realization of Counterbore Inspection System Based on Machine Vision 基于机器视觉的顶孔检测系统的设计与实现

2018 5th International Conference on Systems and Informatics (ICSAI) Pub Date : 2018-11-01 DOI: 10.1109/ICSAI.2018.8599335

J. Sa, Feng Ye, Yue Shao, Yilun An, Shaogang Wan

引用次数: 1