2015 IEEE International Conference on Evolving and Adaptive Intelligent Systems (EAIS)最新文献_第2页

A non-parametric hierarchical clustering model 非参数分层聚类模型

2015 IEEE International Conference on Evolving and Adaptive Intelligent Systems (EAIS) Pub Date : 2015-12-01 DOI: 10.1109/EAIS.2015.7368803

S. Mohamad, A. Bouchachia, M. S. Mouchaweh

引用次数: 4

Feature extractionand incremental learning to improve activity recognition on streaming data 特征提取和增量学习改进流数据的活动识别

2015 IEEE International Conference on Evolving and Adaptive Intelligent Systems (EAIS) Pub Date : 2015-12-01 DOI: 10.1109/EAIS.2015.7368787

Nawel Yala, B. Fergani, A. Fleury

引用次数: 5

An Agent-based framework for mitigating hazardous materials transport risk 减轻危险材料运输风险的基于代理的框架

2015 IEEE International Conference on Evolving and Adaptive Intelligent Systems (EAIS) Pub Date : 2015-12-01 DOI: 10.1109/EAIS.2015.7368791

H. Kanj, J. Flaus

{"title":"An Agent-based framework for mitigating hazardous materials transport risk","authors":"H. Kanj, J. Flaus","doi":"10.1109/EAIS.2015.7368791","DOIUrl":"https://doi.org/10.1109/EAIS.2015.7368791","url":null,"abstract":"Dangerous goods transportation (DGT) represents technological and environmental risks for exposed populations, infrastructures and environment. Historical evidence has shown that road-accidents in DGT can lead to various potential consequences characterized by fatalities, injuries, evacuation, property damage, environmental degradation, and traffic disruption. Due to the importance of these products in everyday civil life activities and the increase in demand for these materials, developing tools for risk analysis and mitigation becomes a strategic goal in particular in those countries, like France, in which the majority of goods are transported by road. Based on the complexity of the dangerous goods transportation system DGTS and its related risk (factors that characterized risks are time dependent as traffic conditions, weather conditions, incident probability and population exposure), this analysis can only be made via simulation. This paper describes a generic approach to use agent-based modeling, an interesting approach to modeling systems comprised of autonomous and interacting agents, for risk analysis. It presents a novel generic model facet for representing risk analysis and fault tree propagation in an agent model, where the goal is to analyze the risk related to a system and to simulate its behavior in normal and degraded mode by using multi-agents systems. This approach is used to analyze the risks related to dangerous goods transportation and to minimize these risks by using agent-based model (identifying the best road that having the minimum risk level for transport).","PeriodicalId":325875,"journal":{"name":"2015 IEEE International Conference on Evolving and Adaptive Intelligent Systems (EAIS)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123718456","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: 6

Automatic visual identification of correct matches in unmanned aerial vehicle images for visual-based attitude estimation 基于视觉姿态估计的无人机图像正确匹配的自动视觉识别

2015 IEEE International Conference on Evolving and Adaptive Intelligent Systems (EAIS) Pub Date : 2015-12-01 DOI: 10.1109/EAIS.2015.7368788

M. R. Tamjis, Samsung Lim

引用次数: 0

Hybridizing firefly algorithm with invasive weed optimization for engineering design problems 基于入侵杂草优化的萤火虫杂交算法求解工程设计问题

2015 IEEE International Conference on Evolving and Adaptive Intelligent Systems (EAIS) Pub Date : 2015-12-01 DOI: 10.1109/EAIS.2015.7368801

H. Kasdirin, N. M. Yahya, M. Tokhi

{"title":"Hybridizing firefly algorithm with invasive weed optimization for engineering design problems","authors":"H. Kasdirin, N. M. Yahya, M. Tokhi","doi":"10.1109/EAIS.2015.7368801","DOIUrl":"https://doi.org/10.1109/EAIS.2015.7368801","url":null,"abstract":"This study presents a hybrid invasive weed firefly optimization (HIWFO) algorithm to solve engineering optimization design problems. The unconstrained and engineering constrained design problems with continuous design variables are used to illustrate the effectiveness and robustness of the proposed algorithm. Firefly algorithm (FA) has deficit on getting trapped at local optimum and invasive weed optimization (IWO) is effective with accurate global search ability. Therefore, the idea of hybridization between IWO and FA has obtained a more robust optimization technique, especially trying to compensate for the deficiencies of the individual algorithms. In the proposed algorithm, the firefly method is embedded into the invasive weed optimization to enhance the local search capability of IWO algorithm that already has very good exploration capability. The performance and evaluation of the proposed method are tested with four well-known unconstrained problems and two engineering design problems. A comparative assessment with the original FA and IWO carried out on the unconstrained problem clearly demonstrates the effectiveness of the hybrid algorithm. Moreover, in dealing with the practical design problems, the HIWFO algorithm is also compared to other algorithm methods to illustrate its effectiveness. From the simulation results, it can be concluded that the HIWFO algorithm has superior searching quality and robustness than other mentioned approaches.","PeriodicalId":325875,"journal":{"name":"2015 IEEE International Conference on Evolving and Adaptive Intelligent Systems (EAIS)","volume":"133 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116323759","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

Drift detection in data stream classification without fully labelled instances 无完全标记实例的数据流分类中的漂移检测

2015 IEEE International Conference on Evolving and Adaptive Intelligent Systems (EAIS) Pub Date : 2015-12-01 DOI: 10.1109/EAIS.2015.7368802

E. Lughofer, Eva Weigl, Wolfgang Heidl, C. Eitzinger, Thomas Radauer

{"title":"Drift detection in data stream classification without fully labelled instances","authors":"E. Lughofer, Eva Weigl, Wolfgang Heidl, C. Eitzinger, Thomas Radauer","doi":"10.1109/EAIS.2015.7368802","DOIUrl":"https://doi.org/10.1109/EAIS.2015.7368802","url":null,"abstract":"Drift detection is an important issue in classification-based stream mining in order to be able to inform the operators in case of unintended changes in the system. Usually, current detection approaches rely on the assumption to have fully supervised labeled streams available, which is often a quite unrealistic scenario in on-line real-world applications. We propose two ways to improve economy and applicability of drift detection: 1.) a semi-supervised approach employing single-pass active learning filters for selecting the most interesting samples for supervising the performance of classifiers and 2.) a fully unsupervised approach based on the overlap degree of classifier's output certainty distributions. Both variants rely on a modified version of the Page-Hinkley test, where a fading factor is introduced to outweigh older samples, making it more flexible to detect successive drift occurrences in a stream. The approaches are compared with the fully supervised variant (SoA) on two real-world on-line applications: the semi-supervised approach is able to detect three real-occurring drifts in these streams with an even lower than resp. the same delay as the supervised variant of about 200 (versus 300) resp. 70 samples, and this by requiring only 20% labelled samples.","PeriodicalId":325875,"journal":{"name":"2015 IEEE International Conference on Evolving and Adaptive Intelligent Systems (EAIS)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133395727","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

Online person identification and new person discovery using appearance features 利用外表特征进行在线人物识别和新人发现

2015 IEEE International Conference on Evolving and Adaptive Intelligent Systems (EAIS) Pub Date : 2015-12-01 DOI: 10.1109/EAIS.2015.7368794

Yanyun Lu, A. Fleury, J. Boonaert, S. Lecoeuche, S. Ambellouis

引用次数: 5

Multi-Word-Co-occurrence collection from texts for health-problem diagnosis 用于健康问题诊断的文本多词共现集

2015 IEEE International Conference on Evolving and Adaptive Intelligent Systems (EAIS) Pub Date : 2015-12-01 DOI: 10.1109/EAIS.2015.7368786

Onuma Moolwat, C. Pechsiri

引用次数: 0

ANFIS data driven modeling and real-time Fuzzy Logic Controller test for a Two Tanks Hydraulic System 双油箱液压系统的ANFIS数据驱动建模与实时模糊控制器试验

2015 IEEE International Conference on Evolving and Adaptive Intelligent Systems (EAIS) Pub Date : 2015-12-01 DOI: 10.1109/EAIS.2015.7368778

L. A. Torres-Salomao, J. Anzurez-Marín, J. M. Orozco-Sixtos, S. Ramirez-Zavala

引用次数: 2

Acoustic sensor based activity recognition using ensemble of one-class classifiers 基于单类分类器集成的声传感器活动识别

2015 IEEE International Conference on Evolving and Adaptive Intelligent Systems (EAIS) Pub Date : 2015-12-01 DOI: 10.1109/EAIS.2015.7368798

A. Tripathi, Diganta Baruah, R. Baruah

引用次数: 7