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Authors: Bernardo Bastien-Olvera and Carlos Gay-Garcia

Affiliation: National University of Mexico, Mexico

Keyword(s): Cimate Change, Global Temperature, Carbon Emissions, Fuzzy Inference Systems, Neural Networks.

Abstract: In this research, a model that projects the mean global temperature as a function of anthropogenic carbon emissions was generated with two fuzzy inference systems, sugeno type. We propose that the climatic system is energetically balanced, and the albedo, solar constant and atmospheric transparency are all constants. Nevertheless, we assume that the surface temperature varies when the CO2 concentration changes and depends on the system temperature itself. The second assertion states that any change in atmospheric CO2 concentration depends on anthropogenic carbon emissions and the system actual concentration. The fuzzy inference systems were optimized using artificial neural networks that adjust the parameters according to a different data base that the one that was used to create the initial system. So that, we assure to find the hidden patterns and avoid overfitting. The principal results of this work are the temperature projections under IPCC scenarios and the discovering of the hi storical data hidden patterns. (More)

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Paper citation in several formats:
Bastien-Olvera, B. and Gay-Garcia, C. (2015). Global Surface Temperature Model using Coupled Sugeno Type Fuzzy Inference Systems and Neural Network Optimization. In Proceedings of the 5th International Conference on Simulation and Modeling Methodologies, Technologies and Applications (SIMULTECH 2015) - MSCCES; ISBN 978-989-758-120-5; ISSN 2184-2841, SciTePress, pages 519-525

@conference{mscces15,
author={Bernardo Bastien{-}Olvera. and Carlos Gay{-}Garcia.},
title={Global Surface Temperature Model using Coupled Sugeno Type Fuzzy Inference Systems and Neural Network Optimization},
booktitle={Proceedings of the 5th International Conference on Simulation and Modeling Methodologies, Technologies and Applications (SIMULTECH 2015) - MSCCES},
year={2015},
pages={519-525},
publisher={SciTePress},
organization={INSTICC},
doi={},
isbn={978-989-758-120-5},
issn={2184-2841},
}

TY - CONF

JO - Proceedings of the 5th International Conference on Simulation and Modeling Methodologies, Technologies and Applications (SIMULTECH 2015) - MSCCES
TI - Global Surface Temperature Model using Coupled Sugeno Type Fuzzy Inference Systems and Neural Network Optimization
SN - 978-989-758-120-5
IS - 2184-2841
AU - Bastien-Olvera, B.
AU - Gay-Garcia, C.
PY - 2015
SP - 519
EP - 525
DO -
PB - SciTePress

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