Michael Peter Angus

Works (2)

Updated: July 5th, 2023 15:42

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.

By: D. Gonzalez n, M. Angus n, I. Tetteh n, G. Bello n, K. Padmanabhan n, S. Pendse n, S. Srinivas n, J. Yu  n ...

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.

By: D. Gonzalez n, S. Pendse n, K. Padmanabhan n, M. Angus n, I. Tetteh n, S. Srinivas n, A. Villanes n, F. Semazzi n, V. Kumar *, N. Samatova n

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

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