2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)最新文献_第3页

IFSDA: An intuitionistic fuzzy set-based data aggregation approach for software maintainability evaluation IFSDA:一种基于直觉模糊集的软件可维护性评价方法

2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD) Pub Date : 2014-12-11 DOI: 10.1109/FSKD.2014.6980839

Yan Nan, Hengshan Zhang, Q. Zheng, Di Wang, Ting Liu, B. Feng

{"title":"IFSDA: An intuitionistic fuzzy set-based data aggregation approach for software maintainability evaluation","authors":"Yan Nan, Hengshan Zhang, Q. Zheng, Di Wang, Ting Liu, B. Feng","doi":"10.1109/FSKD.2014.6980839","DOIUrl":"https://doi.org/10.1109/FSKD.2014.6980839","url":null,"abstract":"The software maintainability which is an important part of software quality and trustworthiness has always been a hot topic in software engineering domain. The measurements of the software are multi-source and heterogeneous data, which result in big challenges on data aggregation for software maintainability evaluation. In this paper, an Intuitionistic Fuzzy Set-based Data Aggregation (IFSDA) approach is developed to evaluate the software maintainability. In order to unify the heterogeneous measurements, a Grade Mapping method is proposed to transform them to the membership function and the non-membership function based on Intuitionistic Fuzzy Set (IFS). The Einstein operation-based aggregation algorithm is applied to aggregate the measurements from the lower level to the higher level under the software maintainability index system. In the experiments, 880 versions of Linux kernels are collected and evaluated to test the IFSDA approach and the maintainability evolution of the Linux kernels can be studied from the experiment results and analysis.","PeriodicalId":397095,"journal":{"name":"2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)","volume":"41 8 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":"121582385","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

Delay synchronization controller for Chua's chaotic circuits 蔡氏混沌电路的延迟同步控制器

2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD) Pub Date : 2014-12-11 DOI: 10.1109/FSKD.2014.6980952

Liping Zhang, Shulin Wu, Kelin Li

引用次数: 1

Several classes of polynomial-time solvable fuzzy relational inequalities 若干类多项式时间可解模糊关系不等式

2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD) Pub Date : 2014-12-11 DOI: 10.1109/FSKD.2014.6980803

Fangfang Guo, Yong-gong Ren

引用次数: 0

A new approach for mining deep order-preserving submatrices 一种挖掘深度保序子矩阵的新方法

2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD) Pub Date : 2014-12-11 DOI: 10.1109/FSKD.2014.6980857

Zhengling Liao, Jie Luo, Meihang Li, Yun Xue, TieChen Li, Xiaohui Hu

引用次数: 0

Parameter estimation of K model of radar cross section for synthetic aperture radar images based on second-kind statistics 基于第二类统计量的合成孔径雷达图像雷达截面K模型参数估计

2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD) Pub Date : 2014-12-11 DOI: 10.1109/FSKD.2014.6980941

Zengguo Sun, Zhihua Zhang

引用次数: 0

Research on distributed computing of EAI platform system EAI平台系统的分布式计算研究

2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD) Pub Date : 2014-12-11 DOI: 10.1109/FSKD.2014.6980954

Jun Tao

引用次数: 0

A decision support system based on fuzzy specialized rules for the Alzheimer disease 基于模糊专门化规则的老年痴呆症决策支持系统

2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD) Pub Date : 2014-12-11 DOI: 10.1109/FSKD.2014.6980883

Firas Zekri, Hanen Ghorbel, R. Bouaziz

引用次数: 5

ARAS: Efficient generation of Association Rules Using Antecedent Support ARAS:使用先行支持的高效关联规则生成

2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD) Pub Date : 2014-12-11 DOI: 10.1109/FSKD.2014.6980848

S. B. Bajaj

引用次数: 4

A common-subsequence-based approach for mining deep order preserving submatrix 基于公共子序列的深度保序子矩阵挖掘方法

2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD) Pub Date : 2014-12-11 DOI: 10.1109/FSKD.2014.6980856

Yun Xue, TieChen Li, Zhiwen Liu, Zhengling Liao, Hua Xiao, Hongya Zhao, Xiaohui Hu

{"title":"A common-subsequence-based approach for mining deep order preserving submatrix","authors":"Yun Xue, TieChen Li, Zhiwen Liu, Zhengling Liao, Hua Xiao, Hongya Zhao, Xiaohui Hu","doi":"10.1109/FSKD.2014.6980856","DOIUrl":"https://doi.org/10.1109/FSKD.2014.6980856","url":null,"abstract":"As an effective biclustering model, order-preserving submatrix (OPSM) has been widely applied to biological gene expression data mining. Recently, biologists hope to find deep OPSMs with long patterns and comparatively few support rows, which are not only useful on the interpretation of gene regulatory networks but also have essential biological significance. Unfortunately, the traditional exact mining algorithms based on Apriori principle could not deal with the deep OPSM problem, since they often take a large minimum support threshold for pattern pruning, and inevitably miss some significant deep OPSMs. Therefore, this paper proposes a new exact algorithm for mining deep OPSMs, which obtain all the deep OPSMs by finding the common subsequences shared by every two rows. Experiments have been done in both real and synthetic data sets, and the results show that our algorithm is suitable for the full mining of deep OPSMs with a small support, which could even find all the deep OPSMs with a minimum support threshold of 2. Compared with the traditional sequential pattern mining algorithms which depend on relatively large support threshold, our algorithm is an effective one to solve the deep OPSM problem.","PeriodicalId":397095,"journal":{"name":"2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)","volume":"2 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":"124355184","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

Predict user interest with respect to global interest popularity 根据全球兴趣流行度预测用户兴趣

2014 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD) Pub Date : 2014-12-11 DOI: 10.1109/FSKD.2014.6980958

Wenhao Zhu, Kan Niu, Guannan Hu, Jiaoxiong Xia

引用次数: 3