2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)最新文献_第3页

Fuzzy community detection in social networks using a genetic algortihm 基于遗传算法的社交网络模糊社区检测

2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) Pub Date : 2014-07-06 DOI: 10.1109/FUZZ-IEEE.2014.6891611

Jianhai Su, T. Havens

{"title":"Fuzzy community detection in social networks using a genetic algortihm","authors":"Jianhai Su, T. Havens","doi":"10.1109/FUZZ-IEEE.2014.6891611","DOIUrl":"https://doi.org/10.1109/FUZZ-IEEE.2014.6891611","url":null,"abstract":"Community structure in a network usually is an indicator of some important hidden pattern, and thus can deepen our understandings of some phenomenon and also enable useful applications. Even though the introduction of Newman's modularity stimulates a magnitude of modularity-based community detection methods, only a few of them are designed for uncovering fuzzy overlapping communities in a network, which in practice are really common in social networks. Considering that modularity maximization is NP-hard and that a genetic algorithm's ability to find fairly good solutions of an NP-hard problem, an O (n2) genetic algorithm for fuzzy community detection (GAFCD) is proposed based on the generalized modularity, a one-step extension of Newman's modularity. Crossover in GAFCD works as an outer-layer search framework that statistically determines sub search spaces with which a novel mutation operator finds the best partition in each sub search space. We compare our proposed GAFCD method with an existing fuzzy community detection algorithm, MULTICUT spectral FCM (MSFCM), and GALS, one of the most effective disjoint (or crisp) community detection, on 10 real world data sets; it is observed that GAFCD outperforms the other algorithms in terms of finding max-modularity communities. Furthermore, GAFCD is able to find both fuzzy partitions and crisp partitions while MSFCM can only find fuzzy partitions and GALS can only find crisp partitions. This unique feature makes GAFCD the first genetic algorithm for finding truly fuzzy (i.e., inclusive of both fuzzy and crisp communities) max-modularity community structure in a network.","PeriodicalId":413342,"journal":{"name":"2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116881220","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: 27

Analytical solution for the linguistic weighted average problem 语言加权平均问题的解析解

2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) Pub Date : 2014-07-06 DOI: 10.1109/FUZZ-IEEE.2014.6891606

Xinwang Liu, Yong Xu, Tong Wu, Na Li

引用次数: 0

A modified EM algorithm for hand gesture segmentation in RGB-D data RGB-D数据中手势分割的改进EM算法

2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) Pub Date : 2014-07-06 DOI: 10.1109/FUZZ-IEEE.2014.6891777

Zhaojie Ju, Yuehui Wang, W. Zeng, Haibin Cai, Honghai Liu

引用次数: 11

Knowledge-leverage based TSK fuzzy system with improved knowledge transfer 基于知识杠杆的改进知识转移TSK模糊系统

2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) Pub Date : 2014-07-06 DOI: 10.1109/FUZZ-IEEE.2014.6891544

Zhaohong Deng, Yizhang Jiang, Longbing Cao, Shitong Wang

引用次数: 10

An improvement in forecasting interval based fuzzy time series 基于模糊时间序列预测区间的改进

2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) Pub Date : 2014-07-06 DOI: 10.1109/FUZZ-IEEE.2014.6891860

Shanoli Samui Pal, T. Pal, S. Kar

引用次数: 2

Tracking control for a non-holonomic car-like robot using dynamic feedback linearization based on piecewise bilinear models 基于分段双线性模型的动态反馈线性化非完整类车机器人跟踪控制

2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) Pub Date : 2014-07-06 DOI: 10.1109/FUZZ-IEEE.2014.6891788

T. Taniguchi, Luka Eciolaza, M. Sugeno

引用次数: 0

Stabilization analysis of single-input polynomial fuzzy systems using control Lyapunov functions 单输入多项式模糊系统的控制Lyapunov函数镇定分析

2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) Pub Date : 2014-07-06 DOI: 10.1109/FUZZ-IEEE.2014.6891740

Radian Furqon, Ying-Jen Chen, Motoyasu Tanaka, Kazuo Tanaka, Hua O. Wang

引用次数: 3

A fuzzy logic based Parkinson's Disease risk predictor 基于模糊逻辑的帕金森病风险预测器

2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) Pub Date : 2014-07-06 DOI: 10.1109/FUZZ-IEEE.2014.6891613

Siyuan Liu, Zhiqi Shen, M. McKeown, Cyril Leung, C. Miao

{"title":"A fuzzy logic based Parkinson's Disease risk predictor","authors":"Siyuan Liu, Zhiqi Shen, M. McKeown, Cyril Leung, C. Miao","doi":"10.1109/FUZZ-IEEE.2014.6891613","DOIUrl":"https://doi.org/10.1109/FUZZ-IEEE.2014.6891613","url":null,"abstract":"With the world population aging rapidly, improving the quality of life for senior citizens has become an important societal issue. Parkinson's Disease (PD) is one of the most debilitating neuro-degenerative disorders that seriously affect the seniors' quality of life. In recent years, video games have been shown to be a viable way through which partial rehabilitation for PD can be carried out in a fun and low cost manner. Earlier research has shown that both patients' physical and mental conditions can be improved by playing video games. However, so far, the available games developed for PD are mostly intended for rehabilitation purposes. PD diagnosis still depends on the traditional neurological exams and experience of doctors, which require the patients to become self-aware of the symptoms and are usually too late for the patients to delay the progression of PD. To support the early detection of PD symptoms, we propose a fuzzy logic based PD risk predictor that has been implemented in a tablet game platform. The player's behavior data in the game environment are captured unobtrusively and analyzed in real-time. The player's current risk of developing PD is estimated using the proposed fuzzy logic based approach, which will help the player to be aware of high risk of having PD at an earlier stage. A pilot evaluation has been conducted to demonstrate the effectiveness of the proposed approach.","PeriodicalId":413342,"journal":{"name":"2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121485905","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: 12

Uncertain Interval Algebra via fuzzy/probabilistic modeling 基于模糊/概率建模的不确定区间代数

2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) Pub Date : 2014-07-06 DOI: 10.1109/FUZZ-IEEE.2014.6891863

Keyvan Sadeghi, B. Goertzel

引用次数: 11

Fuzzy classification of orchard pest posture based on Zernike moments 基于Zernike矩的果园害虫姿态模糊分类

2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) Pub Date : 2014-07-06 DOI: 10.1109/FUZZ-IEEE.2014.6891612

Wen-Yong Li, Shang-Feng Du, Ming Li, Meixiang Chen, Chuanheng Sun

{"title":"Fuzzy classification of orchard pest posture based on Zernike moments","authors":"Wen-Yong Li, Shang-Feng Du, Ming Li, Meixiang Chen, Chuanheng Sun","doi":"10.1109/FUZZ-IEEE.2014.6891612","DOIUrl":"https://doi.org/10.1109/FUZZ-IEEE.2014.6891612","url":null,"abstract":"Identification and count of orchard pests is very important in monitoring orchard pest population. The pests trapped by high-voltage grid show different postures and incomplete bodies, which increase the difficulty of image automated identification. Currently, most researches of pest image identification focus on feature extraction based on standard posture samples, without considering the influence from multi-pose of pests in natural scene. Consequently, the identification rates of these methods are low in practical orchard application. Using Dichocrocis punctiferalis (Guenee) as research object, this paper is directed towards a posture classification method for the orchard target pest identification. It aims at intensifying the performance of multi-pose pest identification system by utilizing Zernike moments as descriptors of shape characteristics. The input image is cropped automatically and further subjected to a number of preprocessing stages. The outcome of preprocessing stage is one processed image containing scaled and translated target pest. Then, the template number is determined according to the posture of target pest and the corresponding template parameters are obtained from the cluster centers by fuzzy C-mean clustering method. Experiment results show that the proposed shape feature is robust to changes caused by pest image shape rotation, translation, and/or scaling. And the highest accuracy of posture classification is 92.3% for orchard target pest Dichocrocis punctiferalis (Guenee) with multiple postures. It outperforms the method in reference [2] where the highest accuracy is 86.6%.","PeriodicalId":413342,"journal":{"name":"2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124414922","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