High operations and maintenance costs for wind turbines reduce their overall cost effectiveness. One of the biggest drivers of maintenance cost is unscheduled maintenance due to unexpected failures. Continuous monitoring of wind turbine health using automated failure detection algorithms can improve turbine reliability and reduce maintenance costs by detecting failures before they reach a catastrophic stage and by eliminating unnecessary scheduled maintenance. A SCADA-based condition monitoring system uses data already collected at the wind turbine controller. It is a cost-effective way to monitor wind turbines for early warning of failures and performance issues. In this paper, we develop three tests on power curve, rotor speed curve and pitch angle curve of individual turbine. To monitor the turbine performance better in daily base, it is critical to recognize different patterns of turbine health condition by fusing all the test results. We apply particle swarm optimization algorithm to determine the fusion rules more objectively and optimally. This novel approach gains a qualitative understanding of turbine health condition to detect faults at an early stage, and also provides explanations on what has happened for detailed diagnostics.
{"title":"Using SCADA Data Fusion by Swarm Intelligence for Wind Turbine Condition Monitoring","authors":"Xiang Ye, Li-hui Zhou","doi":"10.1109/GCIS.2013.40","DOIUrl":"https://doi.org/10.1109/GCIS.2013.40","url":null,"abstract":"High operations and maintenance costs for wind turbines reduce their overall cost effectiveness. One of the biggest drivers of maintenance cost is unscheduled maintenance due to unexpected failures. Continuous monitoring of wind turbine health using automated failure detection algorithms can improve turbine reliability and reduce maintenance costs by detecting failures before they reach a catastrophic stage and by eliminating unnecessary scheduled maintenance. A SCADA-based condition monitoring system uses data already collected at the wind turbine controller. It is a cost-effective way to monitor wind turbines for early warning of failures and performance issues. In this paper, we develop three tests on power curve, rotor speed curve and pitch angle curve of individual turbine. To monitor the turbine performance better in daily base, it is critical to recognize different patterns of turbine health condition by fusing all the test results. We apply particle swarm optimization algorithm to determine the fusion rules more objectively and optimally. This novel approach gains a qualitative understanding of turbine health condition to detect faults at an early stage, and also provides explanations on what has happened for detailed diagnostics.","PeriodicalId":366262,"journal":{"name":"2013 Fourth Global Congress on Intelligent Systems","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123887538","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}
With more companies doing businesses on social media, how can a company stand out from the increasingly crowded social space to find prospective customers from the audience in social media? It remains a challenge to sift through the huge amount of social media data, integrate the information and correlate among the different keywords or entities to form a more comprehensive view. The proposed solution aims to combine social media data and semantic linked data to extract relevant information and capture the relationship among the entities from content shared by the audience. With a targeted audience profiling, company is able to spend marketing dollars more effectively by sending the right offers to the right audience and hence maximize marketing efficiency and improve return of investment (ROI).
{"title":"Use of Semantic Co-relation in Target Audience Profiling","authors":"S. L. Lo, Dong Mei Shan, Viridis Liew","doi":"10.1109/GCIS.2013.44","DOIUrl":"https://doi.org/10.1109/GCIS.2013.44","url":null,"abstract":"With more companies doing businesses on social media, how can a company stand out from the increasingly crowded social space to find prospective customers from the audience in social media? It remains a challenge to sift through the huge amount of social media data, integrate the information and correlate among the different keywords or entities to form a more comprehensive view. The proposed solution aims to combine social media data and semantic linked data to extract relevant information and capture the relationship among the entities from content shared by the audience. With a targeted audience profiling, company is able to spend marketing dollars more effectively by sending the right offers to the right audience and hence maximize marketing efficiency and improve return of investment (ROI).","PeriodicalId":366262,"journal":{"name":"2013 Fourth Global Congress on Intelligent Systems","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124202850","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}
Many effective methods have been proposed to solve the problem of image compression. Fractal image code can compress an image in a higher compress ratio level, the fundamental idea of fractal image compression is based on the iteration function system (IFS). In this paper, we proposed a novel method based on IFS with probabilities can be used in image compression and image retrieval, we obtain enlightenment from fractal no search methods, our method also no need to carried out searching stage when compress the image, so the consuming time with image compression is less than traditional methods. We utilized the image code as index file, and apply our method in image retrieval, experiment results indicate that our method is effective in image retrieval.
{"title":"Image Encode Method Based on IFS with Probabilities Applying in Image Retrieval","authors":"Haipeng Li, F. Li","doi":"10.1109/GCIS.2013.53","DOIUrl":"https://doi.org/10.1109/GCIS.2013.53","url":null,"abstract":"Many effective methods have been proposed to solve the problem of image compression. Fractal image code can compress an image in a higher compress ratio level, the fundamental idea of fractal image compression is based on the iteration function system (IFS). In this paper, we proposed a novel method based on IFS with probabilities can be used in image compression and image retrieval, we obtain enlightenment from fractal no search methods, our method also no need to carried out searching stage when compress the image, so the consuming time with image compression is less than traditional methods. We utilized the image code as index file, and apply our method in image retrieval, experiment results indicate that our method is effective in image retrieval.","PeriodicalId":366262,"journal":{"name":"2013 Fourth Global Congress on Intelligent Systems","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116812631","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}
In this paper, we study neural network ensembles (NNE) classifier with regularized negative correlation learning (RNCL) and its application to pattern classification. In RNCL algorithm, the regularization parameter is used to control the trade off between mean square error and regularization, and to improve the ensemble's generalization ability. We propose an automatic RNCL algorithm based on gradient descent (RNCLgd) to optimize the regularization parameter while evolving the neural network ensemble's weights. The effectiveness of the NNE classifier is demonstrated on a number of benchmark data sets. Compared with back-propagation algorithm multilayer perception (BP-MLP) classifier, it has shown that the NNE classifier with RNCLgd algorithm has better pattern classification performance.
{"title":"Pattern Classification Based on Neural Network Ensembles with Regularized Negative Correlation Learning","authors":"Xiaoyang Fu, Shuqing Zhang","doi":"10.1109/GCIS.2013.24","DOIUrl":"https://doi.org/10.1109/GCIS.2013.24","url":null,"abstract":"In this paper, we study neural network ensembles (NNE) classifier with regularized negative correlation learning (RNCL) and its application to pattern classification. In RNCL algorithm, the regularization parameter is used to control the trade off between mean square error and regularization, and to improve the ensemble's generalization ability. We propose an automatic RNCL algorithm based on gradient descent (RNCLgd) to optimize the regularization parameter while evolving the neural network ensemble's weights. The effectiveness of the NNE classifier is demonstrated on a number of benchmark data sets. Compared with back-propagation algorithm multilayer perception (BP-MLP) classifier, it has shown that the NNE classifier with RNCLgd algorithm has better pattern classification performance.","PeriodicalId":366262,"journal":{"name":"2013 Fourth Global Congress on Intelligent Systems","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128696600","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}
Association rule mining is one of the most important data mining techniques. Typical association rules consider only items enumerated in transactions. Such rules are referred to as positive association rules. Negative association rules also consider the same items, but in addition consider negated items (i.e. absent from transactions). Negative association rules are useful in market-basket analysis to identify products that conflict with each other or products that complement each other. All of the literature on negative association mining, to our best knowledge, is confined to the traditional, relatively static database environment, no research work has been conducted on mining negative associations over data streams. In this paper, we propose an algorithm for mining negative associations over data streams. Experiments on the synthetic data stream are performed to show the effectiveness and efficiency of the proposed approach.
{"title":"Mining Positive and Negative Association Rules in Data Streams with a Sliding Window","authors":"Weimin Ouyang","doi":"10.1109/GCIS.2013.39","DOIUrl":"https://doi.org/10.1109/GCIS.2013.39","url":null,"abstract":"Association rule mining is one of the most important data mining techniques. Typical association rules consider only items enumerated in transactions. Such rules are referred to as positive association rules. Negative association rules also consider the same items, but in addition consider negated items (i.e. absent from transactions). Negative association rules are useful in market-basket analysis to identify products that conflict with each other or products that complement each other. All of the literature on negative association mining, to our best knowledge, is confined to the traditional, relatively static database environment, no research work has been conducted on mining negative associations over data streams. In this paper, we propose an algorithm for mining negative associations over data streams. Experiments on the synthetic data stream are performed to show the effectiveness and efficiency of the proposed approach.","PeriodicalId":366262,"journal":{"name":"2013 Fourth Global Congress on Intelligent Systems","volume":"93 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128022818","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}
In this paper, we propose a novel approach of protocol reverse engineering to extract protocol keywords of unknown application from raw network traffic data without a prior knowledge about the application based on compression theory, entropy and variance analysis. We also present an efficient method to generate statistic signature of unknown application leveraging machine learning and probabilistic models. The experiment results show that our approach extract protocol keywords of application in high accuracy, the false positive and false negative of application identification using our method are very low. Our technique can also discover new application in unknown traffic.
{"title":"Generating Statistic Application Signatures for Inference of Unknown Applications","authors":"Jianlin Luo, Shunzheng Yu","doi":"10.1109/GCIS.2013.45","DOIUrl":"https://doi.org/10.1109/GCIS.2013.45","url":null,"abstract":"In this paper, we propose a novel approach of protocol reverse engineering to extract protocol keywords of unknown application from raw network traffic data without a prior knowledge about the application based on compression theory, entropy and variance analysis. We also present an efficient method to generate statistic signature of unknown application leveraging machine learning and probabilistic models. The experiment results show that our approach extract protocol keywords of application in high accuracy, the false positive and false negative of application identification using our method are very low. Our technique can also discover new application in unknown traffic.","PeriodicalId":366262,"journal":{"name":"2013 Fourth Global Congress on Intelligent Systems","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133687165","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}
In order to recognize and control effectively dynamic information, the paper proposes the concept of F̅-recursive genetic information by introducing the concept of heredity in biology and using P-sets, including the concepts of F̅-recursive dominant inheritance information and -F̅-recursive recessive inheritance information. Meanwhile, the structure and characteristics about the F̅-recursive genetic information are provided. The paper gives the identification theorem and identification criterion as well as the reduction method for the F̅-recursive genetic information. Finally, the application of computer vision recognition of F-recursive genetic information is provided. The research indicates that the generated F̅-recursive genetic information is identifiable and the proposed recursive reduction method is more reliable than the non-recursive reduction method. The-recursive genetic information is a new tool to discover information, to forecast information and to control information.
{"title":"Identification and Reduction of F-Recursive Genetic Information","authors":"Yuying Li, Huannli Zhang, Kaiquan Shi, Weirong Chen","doi":"10.1109/GCIS.2013.42","DOIUrl":"https://doi.org/10.1109/GCIS.2013.42","url":null,"abstract":"In order to recognize and control effectively dynamic information, the paper proposes the concept of F̅-recursive genetic information by introducing the concept of heredity in biology and using P-sets, including the concepts of F̅-recursive dominant inheritance information and -F̅-recursive recessive inheritance information. Meanwhile, the structure and characteristics about the F̅-recursive genetic information are provided. The paper gives the identification theorem and identification criterion as well as the reduction method for the F̅-recursive genetic information. Finally, the application of computer vision recognition of F-recursive genetic information is provided. The research indicates that the generated F̅-recursive genetic information is identifiable and the proposed recursive reduction method is more reliable than the non-recursive reduction method. The-recursive genetic information is a new tool to discover information, to forecast information and to control information.","PeriodicalId":366262,"journal":{"name":"2013 Fourth Global Congress on Intelligent Systems","volume":"111 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134356474","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}
The land use structure and biological service function of Dian-chi lake watershed are being changed by the rapid development of social economy and urbanization, which finally leads to the generation and aggravation of agriculture and urban non-point source pollution in whole basin. Thereby, it is necessary to study the relationship and spatiotemporal process between human activities and land use/cover change (LUCC) of watershed, which is hopeful to offer the scientific decision support for reasonable land planning and land use. Through being combined with GIS technologies of spatial analysis and using the artificial intelligence algorithm called Ant Colony Optimization(ACO) for optimizing, this paper has applied the method of Agent-based modeling to establish the spatiotemporal process model of LUCC in order to simulating the dynamic change of land use in whole watershed. Generally, what has been explored is as fellows. Firstly, make a choice and evaluation for impact factors of land dynamic use, and then create the classes of Agents and their rules in LUCC process. Based on the Java language and Repast platform of modeling, the program design, implementation and simulation of model are given in detail. And finally, the validation for model and analysis for the simulating results are also discussed clearly. We could infer three conclusions from the results of experience. Ant colony algorithm is effective to promote the science express for moving and decision of agents, and the simulating results have better accuracy in both mathematics and geometry than no using it. And the highest accuracy reaches 78.6% in numbers and 68.5% in shape similarity.
{"title":"Simulation for Land Use Dynamic Change of Dian-Chi Lake Watershed Using Agent-Based Modeling","authors":"Quanli Xu, Kun Yang, Jun-hua Yi, G. Wang","doi":"10.1109/GCIS.2013.13","DOIUrl":"https://doi.org/10.1109/GCIS.2013.13","url":null,"abstract":"The land use structure and biological service function of Dian-chi lake watershed are being changed by the rapid development of social economy and urbanization, which finally leads to the generation and aggravation of agriculture and urban non-point source pollution in whole basin. Thereby, it is necessary to study the relationship and spatiotemporal process between human activities and land use/cover change (LUCC) of watershed, which is hopeful to offer the scientific decision support for reasonable land planning and land use. Through being combined with GIS technologies of spatial analysis and using the artificial intelligence algorithm called Ant Colony Optimization(ACO) for optimizing, this paper has applied the method of Agent-based modeling to establish the spatiotemporal process model of LUCC in order to simulating the dynamic change of land use in whole watershed. Generally, what has been explored is as fellows. Firstly, make a choice and evaluation for impact factors of land dynamic use, and then create the classes of Agents and their rules in LUCC process. Based on the Java language and Repast platform of modeling, the program design, implementation and simulation of model are given in detail. And finally, the validation for model and analysis for the simulating results are also discussed clearly. We could infer three conclusions from the results of experience. Ant colony algorithm is effective to promote the science express for moving and decision of agents, and the simulating results have better accuracy in both mathematics and geometry than no using it. And the highest accuracy reaches 78.6% in numbers and 68.5% in shape similarity.","PeriodicalId":366262,"journal":{"name":"2013 Fourth Global Congress on Intelligent Systems","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115555046","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}
Yuanyuan Chen, Shuqin Guo, Biaobiao Zhang, Ke-Lin Du
Pedestrian detection and tracking are widely applied to intelligent video surveillance, intelligent transportation, automotive autonomous driving or driving-assistance systems. We select OpenCV as the development tool for implementation of pedestrian detection, tracking, counting and risk warning in a video segment. We introduce a low-dimensional soft-output SVM pedestrian classifier to implement precise pedestrian detection. Experiments indicate that the system has high recognition accuracy, and can operate in real time.
{"title":"A Pedestrian Detection and Tracking System Based on Video Processing Technology","authors":"Yuanyuan Chen, Shuqin Guo, Biaobiao Zhang, Ke-Lin Du","doi":"10.1109/GCIS.2013.17","DOIUrl":"https://doi.org/10.1109/GCIS.2013.17","url":null,"abstract":"Pedestrian detection and tracking are widely applied to intelligent video surveillance, intelligent transportation, automotive autonomous driving or driving-assistance systems. We select OpenCV as the development tool for implementation of pedestrian detection, tracking, counting and risk warning in a video segment. We introduce a low-dimensional soft-output SVM pedestrian classifier to implement precise pedestrian detection. Experiments indicate that the system has high recognition accuracy, and can operate in real time.","PeriodicalId":366262,"journal":{"name":"2013 Fourth Global Congress on Intelligent Systems","volume":"30 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120895564","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}
Ji Xu, Zhen Zhang, Qingqing Zhang, Jielin Pan, Yonghong Yan
Korean is an agglutinative language, in which pronunciations are affected by long-term context. In this paper, the long-time temporal information is investigated to improve Korean LVCSR. TRAP-based MLP features, which are able to utilize the scattered acoustic information over several hundred milliseconds, are employed to obtain additional information besides the conventional cepstral features. In contrast to the traditional Korean phoneme set, in which consonants in the initial and final positions are taken as the same, a more specific phoneme set is constructed via taking consonants as position dependent. In the Korean broadcast news speech recognition task, experiments show that with these improvements the character error rate has been reduced by 25.3% relatively over the baseline system.
{"title":"Improving Korean LVCSR with Long-Time Temporal Patterns and an Extended Phoneme Set","authors":"Ji Xu, Zhen Zhang, Qingqing Zhang, Jielin Pan, Yonghong Yan","doi":"10.1109/GCIS.2013.60","DOIUrl":"https://doi.org/10.1109/GCIS.2013.60","url":null,"abstract":"Korean is an agglutinative language, in which pronunciations are affected by long-term context. In this paper, the long-time temporal information is investigated to improve Korean LVCSR. TRAP-based MLP features, which are able to utilize the scattered acoustic information over several hundred milliseconds, are employed to obtain additional information besides the conventional cepstral features. In contrast to the traditional Korean phoneme set, in which consonants in the initial and final positions are taken as the same, a more specific phoneme set is constructed via taking consonants as position dependent. In the Korean broadcast news speech recognition task, experiments show that with these improvements the character error rate has been reduced by 25.3% relatively over the baseline system.","PeriodicalId":366262,"journal":{"name":"2013 Fourth Global Congress on Intelligent Systems","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124951023","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}
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