Pub Date : 2017-10-01DOI: 10.1109/INES.2017.8118551
A. Libosvarova, P. Schreiber, L. Spendla
The main goal of this paper is to describe a created methodology for optimizing a complex technical system from the safety and economic aspect. The paper deals with two types of optimization — the maximizing reliability at fixed costs and minimizing costs at fixed reliability. For this purpose it was necessary to construct a fault tree of a suitably chosen technical system by using FTA analysis method. Subsequently, the event probability was assigned to each node of the fault tree by probable valuation, costs and dependence. Genetic algorithms are used as optimization tool The use of created methodology is demonstrated on the real system. The results and meaning of the methodology lie in the correct analysis, successful optimization of fault tree by genetic algorithm and processing a large number of results obtained by experiments. The conclusion summarizes the usability and benefits.
{"title":"Optimizing technical system from the safety and economic aspect by genetic algorithms","authors":"A. Libosvarova, P. Schreiber, L. Spendla","doi":"10.1109/INES.2017.8118551","DOIUrl":"https://doi.org/10.1109/INES.2017.8118551","url":null,"abstract":"The main goal of this paper is to describe a created methodology for optimizing a complex technical system from the safety and economic aspect. The paper deals with two types of optimization — the maximizing reliability at fixed costs and minimizing costs at fixed reliability. For this purpose it was necessary to construct a fault tree of a suitably chosen technical system by using FTA analysis method. Subsequently, the event probability was assigned to each node of the fault tree by probable valuation, costs and dependence. Genetic algorithms are used as optimization tool The use of created methodology is demonstrated on the real system. The results and meaning of the methodology lie in the correct analysis, successful optimization of fault tree by genetic algorithm and processing a large number of results obtained by experiments. The conclusion summarizes the usability and benefits.","PeriodicalId":344933,"journal":{"name":"2017 IEEE 21st International Conference on Intelligent Engineering Systems (INES)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115340282","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 development, operational control and evaluation of the events in the power system necessitate different network calculation methods. For load distribution and contingency analysis is used a stationary grid model. The classic load-flow algorithm is an iterative solution for equation system of thousands variables. For the efficient computation of networks containing huge number of nodes and branches some acceleration and simplification algorithms are used too (decoupled and DC load-flow) The emerging structures as the large non meshed radial networks, microgrids, power quality islands opens new frontiers instead of the exhaustive number-crunching techniques. The task can be rephrased and the application of many intelligent computation method can be relevant, as the artificial neural networks and several optimization solutions. The presentation introduces the on- and off-line tasks of the network calculations, the existing methods and the novel techniques Through examples we are getting acquainted with the • Applications of Simulated Annealing, Tabu Search and Genetic Algorithms for Transmission Network Expansion Planning • Heuristic Ant Colony Search algorithm in Constrained Load Flow problem (reactive power balance) • Optimal power dispatch based on linear decomposition • Optimization for bottle neck flow • Cost and/or loss minimization • Algorithms for power flow control by Flexible AC Transmission devices • Trading path optimization Finally an outlook is given about the new trends of the calculation demands and solutions.
{"title":"Non conventional network analysis","authors":"P. Kádár","doi":"10.24084/repqj16.004","DOIUrl":"https://doi.org/10.24084/repqj16.004","url":null,"abstract":"The development, operational control and evaluation of the events in the power system necessitate different network calculation methods. For load distribution and contingency analysis is used a stationary grid model. The classic load-flow algorithm is an iterative solution for equation system of thousands variables. For the efficient computation of networks containing huge number of nodes and branches some acceleration and simplification algorithms are used too (decoupled and DC load-flow) The emerging structures as the large non meshed radial networks, microgrids, power quality islands opens new frontiers instead of the exhaustive number-crunching techniques. The task can be rephrased and the application of many intelligent computation method can be relevant, as the artificial neural networks and several optimization solutions. The presentation introduces the on- and off-line tasks of the network calculations, the existing methods and the novel techniques Through examples we are getting acquainted with the • Applications of Simulated Annealing, Tabu Search and Genetic Algorithms for Transmission Network Expansion Planning • Heuristic Ant Colony Search algorithm in Constrained Load Flow problem (reactive power balance) • Optimal power dispatch based on linear decomposition • Optimization for bottle neck flow • Cost and/or loss minimization • Algorithms for power flow control by Flexible AC Transmission devices • Trading path optimization Finally an outlook is given about the new trends of the calculation demands and solutions.","PeriodicalId":344933,"journal":{"name":"2017 IEEE 21st International Conference on Intelligent Engineering Systems (INES)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115619948","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}
Pub Date : 2017-10-01DOI: 10.1109/INES.2017.8118575
B. Tusor, Gabriella Simon-Nagy, J. Tóth, A. Várkonyi-Kóczy
Nowadays, there are numerous types of diets that aim to improve the quality of life, health and longevity of people. However, these diets typically involve a strictly planned regime, which can be hard to get used to or even to follow through at all, due to the sudden nature of the change. In this paper, the framework for an Intelligent Space application is proposed that helps its users to achieve a healthier diet in the long term by introducing small, gradual changes into their consumption habits. The application observes the daily nutrition intake of its users, applies data mining in order to learn their personal tastes, and educates them about the effects of their current diet on their health. Then it analyzes the knowledge base to find different food or drink items that align with the perceived preferences, while also add to the balance of the daily nutrition of the users considering their physical properties, activities, and health conditions (e.g. diabetes, celiac disease, food allergies, etc). Finally, the system uses the findings to make suggestions about adding items from the consumption list, or change one item to another.
{"title":"Personalized dietary assistant — An intelligent space application","authors":"B. Tusor, Gabriella Simon-Nagy, J. Tóth, A. Várkonyi-Kóczy","doi":"10.1109/INES.2017.8118575","DOIUrl":"https://doi.org/10.1109/INES.2017.8118575","url":null,"abstract":"Nowadays, there are numerous types of diets that aim to improve the quality of life, health and longevity of people. However, these diets typically involve a strictly planned regime, which can be hard to get used to or even to follow through at all, due to the sudden nature of the change. In this paper, the framework for an Intelligent Space application is proposed that helps its users to achieve a healthier diet in the long term by introducing small, gradual changes into their consumption habits. The application observes the daily nutrition intake of its users, applies data mining in order to learn their personal tastes, and educates them about the effects of their current diet on their health. Then it analyzes the knowledge base to find different food or drink items that align with the perceived preferences, while also add to the balance of the daily nutrition of the users considering their physical properties, activities, and health conditions (e.g. diabetes, celiac disease, food allergies, etc). Finally, the system uses the findings to make suggestions about adding items from the consumption list, or change one item to another.","PeriodicalId":344933,"journal":{"name":"2017 IEEE 21st International Conference on Intelligent Engineering Systems (INES)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129877749","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}
Pub Date : 2017-10-01DOI: 10.1109/INES.2017.8118536
R. Roj
This paper presents a method for the automatical detection of similarities in CAD-models. The main concept is the possible transition of proprietary engineering parts of all kinds of software into the non-native VRML-file format that completely contains the geometrical information. The whole procedure can be divided in three subsections. At first an information extraction takes place. The geometry of the transferred VRML-model gets analyzed where especially the surface structure is extracted for the further processing in the next steps. The algorithm recognizes the shape of every involved face and delivers this information to the conditioning in the second step. There the gained data is used for the generation of graph-structure-like fingerprints that display all surface types as well as their in between connections. These can be considered as signatures, which contain the most important information in a condensed way. In the further steps it is intended to compare the CAD-parts with each other in order to find similarities, build clusters and form groups of topologically related geometries. For a powerful algorithmic comparison a further simplification is necessary. This is implemented by a translation of the graphical fingerprint into a text format and the removal of all smaller and non determining surfaces. Thus, topologically identical and also similar CAD-parts can be recognized and sorted into the same cluster. Due to the fact that the whole procedure is based on the analysis of text, it is qualified for a comparison of several engineering parts as well as for huge amounts of data, like for instance in construction companies.
{"title":"Transformation of VRML-files into graph structures in order to detect similarities and build clusters","authors":"R. Roj","doi":"10.1109/INES.2017.8118536","DOIUrl":"https://doi.org/10.1109/INES.2017.8118536","url":null,"abstract":"This paper presents a method for the automatical detection of similarities in CAD-models. The main concept is the possible transition of proprietary engineering parts of all kinds of software into the non-native VRML-file format that completely contains the geometrical information. The whole procedure can be divided in three subsections. At first an information extraction takes place. The geometry of the transferred VRML-model gets analyzed where especially the surface structure is extracted for the further processing in the next steps. The algorithm recognizes the shape of every involved face and delivers this information to the conditioning in the second step. There the gained data is used for the generation of graph-structure-like fingerprints that display all surface types as well as their in between connections. These can be considered as signatures, which contain the most important information in a condensed way. In the further steps it is intended to compare the CAD-parts with each other in order to find similarities, build clusters and form groups of topologically related geometries. For a powerful algorithmic comparison a further simplification is necessary. This is implemented by a translation of the graphical fingerprint into a text format and the removal of all smaller and non determining surfaces. Thus, topologically identical and also similar CAD-parts can be recognized and sorted into the same cluster. Due to the fact that the whole procedure is based on the analysis of text, it is qualified for a comparison of several engineering parts as well as for huge amounts of data, like for instance in construction companies.","PeriodicalId":344933,"journal":{"name":"2017 IEEE 21st International Conference on Intelligent Engineering Systems (INES)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129603207","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}
Pub Date : 2017-10-01DOI: 10.1109/INES.2017.8118579
A. Peterkova, G. Michalconok, M. Nemeth, A. Bohm
The aim of this article is to analyze the medical data using the data mining methods Under medical data or biomedical data in this article, we understand data that describe the health state of patients with the diagnosis of ischemic heart disease on the basis of results of underwent examinations. At the same time, we designed a suitable way of applying the data mining process when analyzing this data. The entire process is divided into several parts. The first part is devoted to the general identification of problems of acquiring knowledge from medical data, such as identification of the diagnosis or multiple diagnoses of the patient, or identification of the effect of medical parameters on the outcome of the patient's prognosis. The next part is focused on identifying and collecting medical data for the purpose of discovering new knowledge. During this phase, the method for medical data collection from hospital reports was designed. These reports indicated the patient's health status during the hospitalization or examination period. In the data mining phase, medical data was analyzed using selected data mining methods. At this stage, the degree of impact of individual parameters on the final prognosis was also determined.
{"title":"Using data mining methods for identification relationships between medical parameters","authors":"A. Peterkova, G. Michalconok, M. Nemeth, A. Bohm","doi":"10.1109/INES.2017.8118579","DOIUrl":"https://doi.org/10.1109/INES.2017.8118579","url":null,"abstract":"The aim of this article is to analyze the medical data using the data mining methods Under medical data or biomedical data in this article, we understand data that describe the health state of patients with the diagnosis of ischemic heart disease on the basis of results of underwent examinations. At the same time, we designed a suitable way of applying the data mining process when analyzing this data. The entire process is divided into several parts. The first part is devoted to the general identification of problems of acquiring knowledge from medical data, such as identification of the diagnosis or multiple diagnoses of the patient, or identification of the effect of medical parameters on the outcome of the patient's prognosis. The next part is focused on identifying and collecting medical data for the purpose of discovering new knowledge. During this phase, the method for medical data collection from hospital reports was designed. These reports indicated the patient's health status during the hospitalization or examination period. In the data mining phase, medical data was analyzed using selected data mining methods. At this stage, the degree of impact of individual parameters on the final prognosis was also determined.","PeriodicalId":344933,"journal":{"name":"2017 IEEE 21st International Conference on Intelligent Engineering Systems (INES)","volume":"98 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126094637","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}
Pub Date : 2017-10-01DOI: 10.1109/ines.2017.8118570
Stefan Dlugolinsky, Giang T. Nguyen, Martin Seleng, L. Hluchý
This paper presents a work in progress and initial design of a recommender system (RS) for active sale support within a large network of brick and mortar (or convenience) stores. There have been two datasets of historical transactional data provided for the pilot experiments. Each store consists of two kinds of shops; i.e., retail and cafeteria. Although these datasets contain various information about transactions, at our first experiment, they contain just a few information leading to customer identification and thus neither collaborative filtering nor content based techniques can be applied. Therefore, item co-occurrence approach and Naïve Bayes principle are chosen in order to build initial recommendation models with first promising results. Furthermore, discussions and solutions related to many real problems such as data sparsity, embedding of available features into recommendation models, benefits of item categorization, offline evaluation of proposed approaches over historical data, scalability and future personalization are presented in the work. Provided datasets are from real production and have larger sizes and required pre-processing and data transformation for efficient data manipulation and analysis. Various statistics and characteristics of transactional data are provided for practical view when working with similar kind of data, which can be interesting and useful for readers with similar research interests.
{"title":"Decision influence and proactive sale support in a chain of convenience stores","authors":"Stefan Dlugolinsky, Giang T. Nguyen, Martin Seleng, L. Hluchý","doi":"10.1109/ines.2017.8118570","DOIUrl":"https://doi.org/10.1109/ines.2017.8118570","url":null,"abstract":"This paper presents a work in progress and initial design of a recommender system (RS) for active sale support within a large network of brick and mortar (or convenience) stores. There have been two datasets of historical transactional data provided for the pilot experiments. Each store consists of two kinds of shops; i.e., retail and cafeteria. Although these datasets contain various information about transactions, at our first experiment, they contain just a few information leading to customer identification and thus neither collaborative filtering nor content based techniques can be applied. Therefore, item co-occurrence approach and Naïve Bayes principle are chosen in order to build initial recommendation models with first promising results. Furthermore, discussions and solutions related to many real problems such as data sparsity, embedding of available features into recommendation models, benefits of item categorization, offline evaluation of proposed approaches over historical data, scalability and future personalization are presented in the work. Provided datasets are from real production and have larger sizes and required pre-processing and data transformation for efficient data manipulation and analysis. Various statistics and characteristics of transactional data are provided for practical view when working with similar kind of data, which can be interesting and useful for readers with similar research interests.","PeriodicalId":344933,"journal":{"name":"2017 IEEE 21st International Conference on Intelligent Engineering Systems (INES)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121514900","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}
Pub Date : 2017-10-01DOI: 10.1109/ines.2017.8118545
B. Filip, L. Dolga, F. Frigura-Iliasa, P. Andea
Increasing the safety of a navigation lock, by creating a modern and efficient communication between the human operator and the machine, for prompt and accurate information offered to the operator, about the status of the equipment it serves, it is a requirement of today navigation worldwide. This paper aims to describe the implementation of modern and efficient centralized tracking equipment for both operation and preparation of informative reports on operating activities, applied to a Danube Hydro Power Dam and its Locks. An up to date solution for all these issues consists in a SCADA system disposed on several hierarchical levels. The system thus gains greater reliability, increased modularity, and flexibility in operation. A simplified human-machine interface (interface between user and system) is one of the fundamental characteristics of these applications. Dedicated software development has led to an effective dialogue between the human user and the system implemented.
{"title":"Human machine interface for the sluice of a Hydro Power complex","authors":"B. Filip, L. Dolga, F. Frigura-Iliasa, P. Andea","doi":"10.1109/ines.2017.8118545","DOIUrl":"https://doi.org/10.1109/ines.2017.8118545","url":null,"abstract":"Increasing the safety of a navigation lock, by creating a modern and efficient communication between the human operator and the machine, for prompt and accurate information offered to the operator, about the status of the equipment it serves, it is a requirement of today navigation worldwide. This paper aims to describe the implementation of modern and efficient centralized tracking equipment for both operation and preparation of informative reports on operating activities, applied to a Danube Hydro Power Dam and its Locks. An up to date solution for all these issues consists in a SCADA system disposed on several hierarchical levels. The system thus gains greater reliability, increased modularity, and flexibility in operation. A simplified human-machine interface (interface between user and system) is one of the fundamental characteristics of these applications. Dedicated software development has led to an effective dialogue between the human user and the system implemented.","PeriodicalId":344933,"journal":{"name":"2017 IEEE 21st International Conference on Intelligent Engineering Systems (INES)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131079292","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}
Pub Date : 2017-10-01DOI: 10.1109/INES.2017.8118578
M. Takács, A. Szakál, Igor Baganj
The paper gives a possible step-by-step building of a Fuzzy Cognitive Map (FCM), underlying the steps, where the aggregation operators plan an important role in the process. The investigation focuses on the preliminary phase of the FCM learning process, where the adjusting process of the FCM comes off without external additional information about the system model parameters.
{"title":"The rule of the aggregation operators in fuzzy cognitive maps","authors":"M. Takács, A. Szakál, Igor Baganj","doi":"10.1109/INES.2017.8118578","DOIUrl":"https://doi.org/10.1109/INES.2017.8118578","url":null,"abstract":"The paper gives a possible step-by-step building of a Fuzzy Cognitive Map (FCM), underlying the steps, where the aggregation operators plan an important role in the process. The investigation focuses on the preliminary phase of the FCM learning process, where the adjusting process of the FCM comes off without external additional information about the system model parameters.","PeriodicalId":344933,"journal":{"name":"2017 IEEE 21st International Conference on Intelligent Engineering Systems (INES)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134070120","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}
Pub Date : 2017-10-01DOI: 10.1109/INES.2017.8118544
J. Lipina, V. Krys, P. Mec
The Department of Robotics has been in a long-term research of additive technology from the point of view of printing final products. This relates to the issue of mechanical properties of the used materials. Detailed knowledge in the design phase of material properties and structure of parts produced by the Rapid Prototyping Technology (hereinafter as RP) contribute to correct application of such parts. It is valid both for expected directions of impacting forces and long life of the parts. The paper follows up previous publications dealing with material properties during load in tensile stress and bend, and it supplements them with findings from the area of shear tests.
{"title":"Shear test on samples produced by rapid prototyping technology","authors":"J. Lipina, V. Krys, P. Mec","doi":"10.1109/INES.2017.8118544","DOIUrl":"https://doi.org/10.1109/INES.2017.8118544","url":null,"abstract":"The Department of Robotics has been in a long-term research of additive technology from the point of view of printing final products. This relates to the issue of mechanical properties of the used materials. Detailed knowledge in the design phase of material properties and structure of parts produced by the Rapid Prototyping Technology (hereinafter as RP) contribute to correct application of such parts. It is valid both for expected directions of impacting forces and long life of the parts. The paper follows up previous publications dealing with material properties during load in tensile stress and bend, and it supplements them with findings from the area of shear tests.","PeriodicalId":344933,"journal":{"name":"2017 IEEE 21st International Conference on Intelligent Engineering Systems (INES)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124168003","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}
Pub Date : 2017-10-01DOI: 10.1109/ines.2017.8118563
Attila Egri, I. Horváth, Ferenc Kovács, Roland Molontay, K. Varga
In this paper, we investigate dimension reduction possibilities of multidimensional time series data and we introduce a graph based clustering approach using the cross-correlation between time series. The proposed solution consists of two main steps: introducing a novel similarity measure for measuring cross-correlations and a graph-based clustering technique. These two parts are both compared to existing techniques, including noise tolerance and our solution performs better in a noisy environment. The proposed solution is applied to performance metrics of a specific data processing system in order to identify and efficiently visualize connections among the collected metrics. The introduced method provides a more balanced clustering than classic ones, and it is suitable to reveal dependencies and connections among performance metrics time series data.
{"title":"Cross-correlation based clustering and dimension reduction of multivariate time series","authors":"Attila Egri, I. Horváth, Ferenc Kovács, Roland Molontay, K. Varga","doi":"10.1109/ines.2017.8118563","DOIUrl":"https://doi.org/10.1109/ines.2017.8118563","url":null,"abstract":"In this paper, we investigate dimension reduction possibilities of multidimensional time series data and we introduce a graph based clustering approach using the cross-correlation between time series. The proposed solution consists of two main steps: introducing a novel similarity measure for measuring cross-correlations and a graph-based clustering technique. These two parts are both compared to existing techniques, including noise tolerance and our solution performs better in a noisy environment. The proposed solution is applied to performance metrics of a specific data processing system in order to identify and efficiently visualize connections among the collected metrics. The introduced method provides a more balanced clustering than classic ones, and it is suitable to reveal dependencies and connections among performance metrics time series data.","PeriodicalId":344933,"journal":{"name":"2017 IEEE 21st International Conference on Intelligent Engineering Systems (INES)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114619949","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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