Works (3)

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

2008 conference paper

Finite difference formulation to calculate the induced current density profile inside the retina by a microcoil array

2008 IEEE International Symposium on Antennas and Propagation and USNC/URSI National Radio Science Meeting, 3074–3077. [Piscataway, NJ]: IEEE.

By: S. Srinivas, J. George & G. Lazzi

Source: NC State University Libraries
Added: August 6, 2018

Citation Index includes data from a number of different sources. If you have questions about the sources of data in the Citation Index or need a set of data which is free to re-distribute, please contact us.

Certain data included herein are derived from the Web of Science© and InCites© (2024) of Clarivate Analytics. All rights reserved. You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.