COMPUTING RESEARCH HIGHLIGHT OF THE WEEK [September 26 - October 2]
Researchers Devise More Accurate Method For Predicting Hurricane Activity
The latent behavior of a physical system that can exhibit extreme events such as hurricanes or rainfalls is complex. Recently, a very promising means for studying complex systems has emerged through the concept of complex networks. Networks representing relationships between individual objects usually exhibit community dynamics. Conventional community detection methods mainly focus on either mining frequent subgraphs in a network or detecting stable communities in time-varying networks. In this paper, we formulate a novel problem—detection of predictive and phase-biased communities in contrasting groups of networks, and propose an efficient and effective machine learning solution for finding such anomalous communities. We build different groups of networks corresponding to different system’s phases, such as higher or low hurricane activity, discover phase-related system components as seeds to help bound the search space of community generation in each network, and use the proposed contrast-based technique to identify the changing communities across different groups. The detected anomalous communities are hypothesized (1) to play an important role in defining the target system’s state(s) and (2) to improve the predictive skill of the system’s states when used collectively in the ensemble of predictive models. When tested on the two important extreme event problems—identification of tropical cyclone-related and of African Sahel rainfall-related climate indices—our algorithm demonstrated the superior performance in terms of various skill and robustness metrics, including 8–16 % accuracy increase, as well as physical interpretability of detected communities. The experimental results also show the efficiency of our algorithm on synthetic datasets.
Full Article...
Source: NC State University
Researchers:
Zhengzhang Chen
Dr. Fredrick Semazzi
William Hendrix
Isaac K. Tetteh
Nagiza Samatova
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Computing Research Highlight of the Week is a service of the Computing Community Consortium and the Computing Research Association designed to highlight some of the exciting and important recent research results in the computing fields. Each week a new highlight is chosen by CRA and CCC staff and volunteers from submissions from the computing community. Want your research featured? Submit it!.
