2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)最新文献_第7页

Q-increment deterministic annealing fuzzy c-means clsutering using Tsallis entropy 基于Tsallis熵的q增量确定性退火模糊c均值聚类

2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD) Pub Date : 2014-12-11 DOI: 10.1109/FSKD.2014.6980802

M. Yasuda

引用次数: 1

Adaptively incremental dictionary compression method for column-oriented database 面向列数据库的自适应增量字典压缩方法

2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD) Pub Date : 2014-12-11 DOI: 10.1109/FSKD.2014.6980907

Hui Liu, Zhijing Liu, Tong Yuan, Yong Yao

引用次数: 2

A MapReduce based parallel algorithm for CIM data verification 基于MapReduce的CIM数据验证并行算法

2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD) Pub Date : 2014-12-11 DOI: 10.1109/FSKD.2014.6980921

Yang Liu, Xiaodong Shen, Lixiong Xu, Maozhen Li

引用次数: 1

Online bidding system based on Cournot model using K-means clustering 基于k -均值聚类的古诺模型在线竞价系统

2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD) Pub Date : 2014-12-11 DOI: 10.1109/FSKD.2014.6980861

Jun Tan, Yan-Jiang Jia

引用次数: 3

Evaluating host-based anomaly detection systems: Application of the one-class SVM algorithm to ADFA-LD 评估基于主机的异常检测系统:一类SVM算法在ADFA-LD中的应用

2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD) Pub Date : 2014-12-11 DOI: 10.1109/FSKD.2014.6980972

Miao Xie, Jiankun Hu, J. Slay

引用次数: 73

A real-time trajectory indexing method based on MongoDB 基于MongoDB的实时轨迹索引方法

2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD) Pub Date : 2014-12-11 DOI: 10.1109/FSKD.2014.6980893

Yuxin Zhu, Jun Gong

{"title":"A real-time trajectory indexing method based on MongoDB","authors":"Yuxin Zhu, Jun Gong","doi":"10.1109/FSKD.2014.6980893","DOIUrl":"https://doi.org/10.1109/FSKD.2014.6980893","url":null,"abstract":"Aiming at the inefficiency problems of existing trajectory database techniques especially in real-time access to latest trajectories, a real-time trajectory indexing method based on MongoDB and mixed with spatio-temporal R-tree, hash table and B-tree for searching leaf nodes is proposed in this paper. Time in spatio-temporal R-tree is used as another dimension of equal status to space, and a leaf node can only involve a moving object's consecutive trajectory points. In order to solve the problem of frequent updates and lack of memory, hash table is divided into two kinds: one caches leaf nodes of spatio-temporal R-tree, which are not inserted into spatio-temporal R-tree until they are full or out-dated in the hash table. This improves generation efficiency of real-time trajectory index; the other one caches in-memory nodes which are loaded from external memory, it avoids frequent operations related to external memory. We build B-tree based on object identification and time in leaf nodes, which benefits trajectory queries for moving objects. In comparison to SETI, the experimental results show that our method has good update efficiency and query performance, and it meets the demand of common trajectory queries in present applications.","PeriodicalId":397095,"journal":{"name":"2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129430030","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: 4

Data locality in Hadoop cluster systems Hadoop集群系统中的数据局部性

2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD) Pub Date : 2014-12-11 DOI: 10.1109/FSKD.2014.6980924

Mukhtaj Khan, Yang Liu, Maozhen Li

引用次数: 11

A statistical learning approach to Chang'E microwave radiometer data calibration 基于统计学习的嫦娥微波辐射计数据定标方法

2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD) Pub Date : 2014-12-11 DOI: 10.1109/FSKD.2014.6980863

K. Tsang, S. Fu, Jingwen Gu, Min Zhou, K. Chan, Y. C. Zheng

{"title":"A statistical learning approach to Chang'E microwave radiometer data calibration","authors":"K. Tsang, S. Fu, Jingwen Gu, Min Zhou, K. Chan, Y. C. Zheng","doi":"10.1109/FSKD.2014.6980863","DOIUrl":"https://doi.org/10.1109/FSKD.2014.6980863","url":null,"abstract":"We have proposed a statistical learning model which accounts for the effect due to the Chinese Chang'E (CE) cold space calibration antenna may have been contaminated by thermal microwave radiation from the lunar surface because its field of view overlapped with the lunar surface instead of aiming just at the cold space. This effect can corrupt the simple two-point calibration procedure and lead to the discrepancy between the available microwave radiometer Level 2C data from CE1 & 2. An algorithm to implement the statistical learning model is developed. Recalibration of the Level 2C radiometer data from localized locations (around the Apollo 17 lunar mission landing site on the lunar surface) by regression analysis based on our statistical learning calibration model successfully removes the discrepancy between the two sets of microwave brightness temperatures data from CE1 and 2. Residual analysis on the combined dataset shows that that the residuals are normally distributed with a mean value equals to zero. This sophisticate statistical learning algorithm developed here may be considered as a recalibration effort to remove the systematic inconsistency between the two microwave brightness temperature datasets. The combined and enlarged CE radiometer dataset may potentially increase our understanding of the physical reality hidden behind.","PeriodicalId":397095,"journal":{"name":"2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)","volume":"111 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124369108","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

Image compression algorithm based on automatic extracted ROI 基于ROI自动提取的图像压缩算法

2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD) Pub Date : 2014-12-11 DOI: 10.1109/FSKD.2014.6980937

Peilong Zhao, Jiwen Dong, Lei Wang

引用次数: 3

Distributed clustering using distributed mixture of probabilistic PCA 使用分布混合概率PCA的分布式聚类

2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD) Pub Date : 2014-12-11 DOI: 10.1109/FSKD.2014.6980859

Hang Yin, Chunhong Zhang, Yang Ji

引用次数: 1