Matrix clustering algorithms are among the oldest approaches to the vertical partitioning problem. They can be summarized as follows: (1) given a workload, construct an Attribute Usage Matrix (AUM), (2) apply some kin...
详细信息
Matrix clustering algorithms are among the oldest approaches to the vertical partitioning problem. They can be summarized as follows: (1) given a workload, construct an Attribute Usage Matrix (AUM), (2) apply some kind of a row and column permutation algorithm and (3) extract the resulting clusters which define the required fragments. This naive approach holds some promise for a number of contemporary applications: (1) dynamization of vertical partitioning (2) big data applications and other cases of resource constraints (3) tuning of multistores. In this paper we examine a number of existing matrix clustering algorithms used for vertical partitioning. We study these algorithms and assess the quality of the solutions. The experiments are run on the TPC-H workload using the PostgreSQL DBMS.
Traffic Road accidents have always been a significant cause of death in the Country. Many solutions have been developed over the years to reduce the problem of traffic and road accidents, but not much success has been...
详细信息
This paper presents a new approach designed to reduce the computational load of the existing clustering algorithms by trimming down the documents size using fingerprinting methods. Thorough evaluation was performed ov...
详细信息
In this paper, we investigate the problem of quality analysis of clustering results using semantic annotations given by experts. In previous work we proposed a novel approach to construction of evaluation measure, cal...
详细信息
clustering is one of the most important data analysis tasks. It is used to organize data points into groups or clusters. Each cluster has similar instances, which are dissimilar to instances belonging to other cluster...
详细信息
The topology of the distributed cognitive radio network is volatile as influenced by the behavior of primary users, and this condition leads to the large communication overhead and low utilization of spectrum resource...
详细信息
High dimensional data analysis poses some interesting and counter intuitive problems. One of this problems is, that some clustering algorithms do not work or work only very poorly if the dimensionality of the feature ...
详细信息
Load forecasting is one of the critical activities in electric power system planning. This paper presents clustering algorithms and their usage in load forecasting on a case study in Zagreb, Croatia. Load data acquisi...
详细信息
The interaction between electric vehicles (EV) and the future energy system is subject of current research in the field of energy system analysis. EVs represent an additional electrical load on the one hand and a pote...
详细信息
ISBN:
(纸本)9781839536793
The interaction between electric vehicles (EV) and the future energy system is subject of current research in the field of energy system analysis. EVs represent an additional electrical load on the one hand and a potential flexibility provider through smart charging on the other. Feedback effects on the energy system and potential benefits of intelligently charged EVs depend on a variety of technical parameters as well as the individual driving behavior of vehicle owners. Since no sufficient data on EV users driving behavior is currently available, synthetic profiles have to be used. In this paper we propose a methodological approach that combines the mobility data of the two main household travel surveys in Germany - the Mobility in Germany 2017 and the German Mobility panel - to synthesize annual mobility profiles that represent the German mobility behavior. To guarantee statistical soundness, the methodology requires a large number of individual profiles used for further evaluations. Computational power however limits the maximum number of usable profiles. In the context of this paper, we assess and compare potential revenues of a price optimized unidirectional and bidirectional charging strategy. Those evaluations are carried out for 10,000 profiles with the linear optimization model eFLAME. Resulting revenues and vehicle-specific indicators such as equivalent full cycles (EFC) and charging/discharging hours serve as a reference for further evaluations with a reduced number of profiles. To reduce that number, we compare two distinct methodological approaches. The first approach is based on randomly drawing an increasing number of profiles, while the second is based on applying various clustering algorithms to specifically identify representative profiles. In the context of clustering algorithms, we test and compare distinct feature definitions, preanalysis methods and include a principal component analysis (PCA) to identify the best cluster of representative pro
In wireless self-organized network (WSON), AOW clustering algorithms can achieve better performance and high adaptability, but having limitations in certain circumstances. In this paper, working procedure and shortcom...
详细信息
暂无评论