With the Internet and mobile communications becoming an indispensable part of people's daily lives, online transactions have become one of the most common payment methods. However, transaction fraud incidents also...
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The Locality-weight fuzzy c-means clustering method has been presented *** this approach can improve the clustering accuracies,it often gains the unstable clustering results because some random samples are employed fo...
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ISBN:
(纸本)9781467349970
The Locality-weight fuzzy c-means clustering method has been presented *** this approach can improve the clustering accuracies,it often gains the unstable clustering results because some random samples are employed for the initial *** this paper,an initialization method based on the core clusters is used for the locality-weight fuzzy c-means *** core clusters can be formed by constructing the σ-neighborhood graph and their centers are regarded as the initial centers of the locality-weight fuzzy c-means *** investigate the effectiveness of our approach,several experiments are done on three *** results show that our proposed method can improve the clustering performance compared to the previous locality-weight fuzzy c-means clustering.
In this paper, a single stator twin external rotors ironless AFPMSM for robot applications is studied. The design method of the motor is proposed. The magnetic circuit calculation and the main motor size equations are...
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Millimeter wave communication provides high data rates thanks to large arrays at the transmitter and receiver, coupled with large bandwidth channels. Exploiting the arrays is challenging due to the need to configure p...
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This paper proposes a method of the fault detection and diagnosis for the railway turnout based on the current curve of switch machine. Exact curve matching fault detection method and SVM-based fault diagnosis method ...
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Current semi-supervised learning-based sample selection methods for noisy label image classification typically utilize all clean and noisy samples for model training. However, not all noisy samples contribute positive...
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This essay introduces the concepts of knowledge granularity and information system. On this basis, we propose two new more general knowledge granularities: the combination granularity and polynomial granularity, which...
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Particle swarm optimization (PSO) is a widely-adopted optimization algorithm which is based on particles’ fitness evaluations and their swarm intelligence. However, it is difficult to obtain the exact fitness evaluat...
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Traffic flow forecasting is indispensable in modern urban life. Considering the complexity, variability and strong timeliness of traffic flow, traffic flow forecasting is a worth exploring but challenging research fie...
Skyline query processing has recently received a lot of attention in database *** a set of multi-dimensional objects,the skyline query finds the objects that are not dominated by *** the best of our knowledge,the exis...
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Skyline query processing has recently received a lot of attention in database *** a set of multi-dimensional objects,the skyline query finds the objects that are not dominated by *** the best of our knowledge,the existing researches mainly focus on how to efficiently return the whole skyline ***,as the cardinality and dimensionality of input dataset increase,the number of skylines grows exponentially,and hence this "huge" skyline set is completely useless to *** by the above fact,in this paper,we present a novel type of l-SkyDiv query,which only returns l skylines having maximum diversity,to improve the usefulness of skyline ***,we prove that the l-SkyDiv query belongs to the NP-Hard problem theoretically,and propose three efficient heuristic algorithms whose time complexities are polynomial to fast implement the proposed ***,we present detailed theoretical analyses and extensive experiments,demonstrating that our algorithms are both efficient and effective.
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