H
Huiping Cao
Researcher at New Mexico State University
Publications - 61
Citations - 1904
Huiping Cao is an academic researcher from New Mexico State University. The author has contributed to research in topics: Computer science & Graph (abstract data type). The author has an hindex of 15, co-authored 57 publications receiving 1580 citations. Previous affiliations of Huiping Cao include Arizona State University & University of California, Santa Barbara.
Papers
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Proceedings ArticleDOI
Mining frequent spatio-temporal sequential patterns
TL;DR: This paper proposes algorithms to find patterns by employing a newly proposed substring tree structure and improving a priori technique, and defines pattern elements as spatial regions around frequent line segments.
Proceedings ArticleDOI
Mining, indexing, and querying historical spatiotemporal data
TL;DR: This work defines the spatiotemporal periodic pattern mining problem and proposes an effective and fast mining algorithm for retrieving maximal periodic patterns, and devise a novel, specialized index structure that can benefit from the discovered patterns to support more efficient execution of spatiotsemporal queries.
Proceedings ArticleDOI
Characterizing and quantifying noise in PMU data
TL;DR: In this article, the probability distribution of measurement noise and its typical power are identified for voltage, current and frequency data recorded at three different voltage levels, and the PMU noise quantification can help in generation of experimental PMU data in close conformity with field PMUs.
Journal ArticleDOI
Discovery of Periodic Patterns in Spatiotemporal Sequences
TL;DR: This paper defines the problem of mining periodic patterns in spatiotemporal data and proposes an effective and efficient algorithm for retrieving maximal periodic patterns, and demonstrates how the mining technique can be adapted for two interesting variants of the problem.
Journal ArticleDOI
Real-Time Identification of Dynamic Events in Power Systems Using PMU Data, and Potential Applications—Models, Promises, and Challenges
Sukumar Brahma,Rajesh Kavasseri,Huiping Cao,Nilanjan Ray Chaudhuri,Theodoros Alexopoulos,Yinan Cui +5 more
TL;DR: Two underlying models for the task of real-time identification of dynamic events leading to a layer of situational awareness that can become a reality due to increased penetration of phasor measurement units in transmission systems are explored.