2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)最新文献_第10页

Gompertz fuzzy model for plant disease evolution 植物病害进化的Gompertz模糊模型

2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) Pub Date : 2017-07-01 DOI: 10.1109/FUZZ-IEEE.2017.8015399

N. Clara, X. Bertran

引用次数: 0

Soft querying of sensorial data 感知数据的软查询

2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) Pub Date : 2017-07-01 DOI: 10.1109/FUZZ-IEEE.2017.8015400

C. Coulon-Leroy, L. Lietard

引用次数: 0

Acoustic event classification using Cauchy Non-negative matrix factorization and fuzzy rule-based classifier 基于柯西非负矩阵分解和模糊规则分类器的声学事件分类

2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) Pub Date : 2017-07-01 DOI: 10.1109/FUZZ-IEEE.2017.8015584

A. Tripathi, R. Baruah

{"title":"Acoustic event classification using Cauchy Non-negative matrix factorization and fuzzy rule-based classifier","authors":"A. Tripathi, R. Baruah","doi":"10.1109/FUZZ-IEEE.2017.8015584","DOIUrl":"https://doi.org/10.1109/FUZZ-IEEE.2017.8015584","url":null,"abstract":"Identification of presence of target acoustic sound or event from a single channel mixture is a challenging task of automatic sound recognition system. In presence of background noise, the detection and classification of target acoustic event becomes more difficult. Various methods have been proposed that extract features from spectrogram of sound and then the extracted features are used with traditional non negative matrix factorization for separation of overlapping sound. In his paper, we propose an approach to separate and classify single channel acoustic events. The method combines Common Fate Transformation and Cauchy Non-negative Matrix Factorization for feature extraction and finally fuzzy rule-based classifier is developed for classification. The proposed method, when applied to real data, gave high true positive rate. The method also gave better results in terms of true positive rate when compared to widely used support vector machine using the same real data. Moreover, the proposed approach is fast and can be used for the efficient separation of acoustic events from overlapping sounds.","PeriodicalId":408343,"journal":{"name":"2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129374661","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

Standard completeness for extensions of IMTL IMTL扩展的标准完备性

2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) Pub Date : 2017-07-01 DOI: 10.1109/FUZZ-IEEE.2017.8015625

P. Baldi, A. Ciabattoni, Francesca Gulisano

引用次数: 4

A controller for a class of T-S fuzzy models with uncertainty using Nussbaum-type function 一类具有不确定性的T-S模糊模型的nussbaum型函数控制器

2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) Pub Date : 2017-07-01 DOI: 10.1109/FUZZ-IEEE.2017.8015512

Hugang Han

引用次数: 1

Credit risk profiling using a new evaluation of interval-valued fuzzy sets based on alpha-cuts 基于区间值模糊集评价的信用风险分析

2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) Pub Date : 2017-07-01 DOI: 10.1109/FUZZ-IEEE.2017.8015613

L. Anzilli, G. Facchinetti, T. Pirotti

引用次数: 3

LMI-based fault detection and isolation of nonlinear descriptor systems 基于lmi的非线性广义系统故障检测与隔离

2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) Pub Date : 2017-07-01 DOI: 10.1109/FUZZ-IEEE.2017.8015715

F. López‐Estrada, H. H. Leon, V. Estrada-Manzo, M. Bernal

引用次数: 1

B-properties of fuzzy relations in aggregation process — the “converse problem” 聚集过程中模糊关系的b -性质——“逆问题”

2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) Pub Date : 2017-07-01 DOI: 10.1109/FUZZ-IEEE.2017.8015574

Urszula Bentkowska

引用次数: 3

Predicting activity occurrence time in smart homes with evolving fuzzy models 利用进化模糊模型预测智能家居中的活动发生时间

2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) Pub Date : 2017-07-01 DOI: 10.1109/FUZZ-IEEE.2017.8015728

R. Baruah, Manish Singh, Diganta Baruah, I. S. Misra

引用次数: 3

A fuzzy-based process mining approach for dynamic malware detection 一种基于模糊过程挖掘的动态恶意软件检测方法

2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE) Pub Date : 2017-07-01 DOI: 10.1109/FUZZ-IEEE.2017.8015490

M. Bernardi, Marta Cimitile, F. Martinelli, F. Mercaldo

{"title":"A fuzzy-based process mining approach for dynamic malware detection","authors":"M. Bernardi, Marta Cimitile, F. Martinelli, F. Mercaldo","doi":"10.1109/FUZZ-IEEE.2017.8015490","DOIUrl":"https://doi.org/10.1109/FUZZ-IEEE.2017.8015490","url":null,"abstract":"Mobile systems have become essential for communication and productivity but are also becoming target of continuous malware attacks. New malware are often obtained as variants of existing malicious code. This work describes an approach for dynamic malware detection based on the combination of Process Mining (PM) and Fuzzy Logic (FL) techniques. The firsts are used to characterize the behavior of an application identifying some recurring execution expressed as a set of declarative constraints between the system calls. Fuzzy logic is used to classify the analyzed malware applications and verify their relations with the existing malware variants. The combination of the two techniques allows to obtain a fingerprint of an application that is used to verify its maliciousness/trustfulness, establish if it belongs from a known malware family and identify the differences between the detected malware behavior and the other variants of the some malware family. The approach is applied on a dataset of 3000 trusted and malicious applications across twelve malware families and has shown a very good discrimination ability that can be exploited for malware detection and family identification.","PeriodicalId":408343,"journal":{"name":"2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121728558","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