Works (4)
Updated: July 5th, 2023 15:44
2015 journal article
On the data-driven inference of modulatory networks in climate science: an application to West African rainfall
NONLINEAR PROCESSES IN GEOPHYSICS, 22(1), 33–46.
www.nonlin-processes-geophys.net (publisher PDF)
UN Sustainable Development Goal Categories
13. Climate Action
(Web of Science; OpenAlex)
Source: Web Of Science
Added: August 6, 2018
2013 article
Coupled Heterogeneous Association Rule Mining (CHARM): Application toward Inference of Modulatory Climate Relationships
2013 IEEE 13TH INTERNATIONAL CONFERENCE ON DATA MINING (ICDM), pp. 1055–1060.
author keywords: association rules; climate; data coupling; discovery
TL;DR:
Coupled Heterogeneous Association Rule Mining (CHARM), a computationally efficient methodology that mines higher-order relationships between these subsystems' anomalous temporal phases with respect to their effect on the system's response, is presented.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
13. Climate Action
(Web of Science; OpenAlex)
Source: Web Of Science
Added: August 6, 2018
2013 journal article
Discovery of extreme events-related communities in contrasting groups of physical system networks
DATA MINING AND KNOWLEDGE DISCOVERY, 27(2), 225–258.
author keywords: Spatio-temporal data mining; Complex network analysis; Community detection; Comparative analysis; Networkmotif detection; Extreme event prediction
TL;DR:
This paper forms a novel problem—detection of predictive and phase-biased communities in contrasting groups of networks, and proposes an efficient and effective machine learning solution for finding such anomalous communities.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
13. Climate Action
(Web of Science; OpenAlex)
Source: Web Of Science
Added: August 6, 2018
2012 article
Hierarchical Classifier-Regression Ensemble for Multi-Phase Non-Linear Dynamic System Response Prediction: Application to Climate Analysis
12TH IEEE INTERNATIONAL CONFERENCE ON DATA MINING WORKSHOPS (ICDMW 2012), pp. 781–788.
TL;DR:
This paper proposes a hybrid approach that first predicts the phase the system is in, and then estimates the magnitude of the system's response using the regression model optimized for this phase, designed for systems that could be characterized by multi-variate spatio-temporal data from observations, simulations, or both.
(via Semantic Scholar)
UN Sustainable Development Goal Categories
13. Climate Action
(Web of Science)
Source: Web Of Science
Added: August 6, 2018
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