MSCCES 2015 Abstracts

Full Papers

Paper Nr:	1
Title:	Global Surface Temperature Model using Coupled Sugeno Type Fuzzy Inference Systems and Neural Network Optimization
Authors:	Bernardo Bastien-Olvera and Carlos Gay-Garcia
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 historical data hidden patterns.
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Paper Nr:	2
Title:	Stabilizing Global Temperature Through a Fuzzy Control on CO2 Emissions
Authors:	Carlos Gay-Garcia and Bernardo Bastien
Abstract:	In this research, we generated a fuzzy control of carbon emissions that acts increasing or decreasing the representative concentration pathway emissions proposed by the IPCC, in order to obtain a CO2 path that would stabilize the global average surface temperature to a desired level. We used a simple linear climate model that is driven primary by the Carbon emissions. We made simulations under the four RCPs activating the control at different times, which give us a broad knowledge on when is possible to stabilize the temperature, based in the current emissions path. We conclude that taking action earlier (via fuzzy control) will lead not only to reach stabilization, but also, in some cases, to have economic growth allowing to increase emissions at some points in time. Activating the control very late will initiate an oscillation on temperature which will include not only a reduction of emissions but also a necessary anthropogenic net carbon sequestration. This instrument is a common ground where specialists in diverse areas of climate change could contribute in order to set the parameters that we should explore and simulate so that the we can make the best decisions.
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Paper Nr:	3
Title:	Tackling Non-linearity in Seismic Risk Estimation using Fuzzy Methods
Authors:	J. Rubén González Cárdenas, Àngela Nebot, Francisco Mugica and Helen Crowley
Abstract:	Traditional approaches to measure risk to natural hazards considers the use of composite indices. However, most of the times such indices are built assuming linear interrelations (interdependencies) between the aggregated components in such a way that the final index value is based only on an accumulative or scalable structure. In this paper we propose the use of Fuzzy Inference Systems type Mamdami in order to aggregate physical seismic risk and social vulnerability indicators. The aggregation is made by establishing rules (ifthen type) over the indicators in order to get an index. Finally a quantitative seismic risk estimation is made though the convolution of these two main factors by means of fuzzy inferences, in such a way that no linear assumptions are used along the estimation. We applied the fuzzy model over the city of Bogota Colombia. We consider that this approach is a useful way to estimate a measure of an intangible reality such as seismic risk, by assuming the urban settlement’s complexity where the interrelations between the associated risk components are inherently non-linear. The proposed model possess a practical use over the risk management field, since the design of the logic rules uses a smooth application of risk management knowledge following a multidisciplinary approach, thus making the model easily adapted to a particular circumstance or context regardless the background of the final user.
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Paper Nr:	4
Title:	Term-frequency Inverse Document Frequency for the Assessment of Similarity in Central and State Climate Change Programs: An Example for Mexico
Authors:	Iván Paz-Ortiz, Diego García-Olano and Carlos Gay-García
Abstract:	In the present work we present a preliminary approach intended for the assessment of the development of the climate change programs. Particularly we are interested in policies that are develop top-to-bottom by following specific central guidelines. To this end, the numerical statistic “term frequency-inverse document frequency” is used to compare the similarity between the action plans on climate change at national and state level in the case of Mexico. The results allow us to construct a similarity matrix to extract information about how these plans capture local level characteristics and their degree of attachment to the central policy.
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