MSCCEC 2012 Abstracts


Full Papers
Paper Nr: 2
Title:

Use of Fuzzy Cognitive Maps for Climate System Stability Analysis

Authors:

Carlos Gay García and Iván Paz Ortiz

Abstract: In the present work we use fuzzy cognitive maps for the qualitative analysis of the earth’s climate system dynamics. First of all, we identify the subsystems which determine, as a hole, the stability of the climatic system. Later we develop cognitive maps (knowledge networks) based on the documented relationships between the subsystems (nodes of the network). The relationships between the nodes can be precise (quantifiable) or fuzzy (not quantifiable). Once the map is built, we use the state vector and adjacent matrix technique to assess the response of the system (the system converges or diverges) to the changes in the input node values in order to identify the possibles feedback. Then the Min-Max criteria is used to evaluate the effect of the network over the nodes, according to the fuzzy weights assigned to the edges (causal relations between nodes). Finally, we discuss some possible changes in the network in order to show how the system dynamic can be modified and can lead the system into a desired equilibrium state.

Paper Nr: 3
Title:

Simple Fuzzy Logic Models to Estimate the Global Temperature Change Due to GHG Emissions

Authors:

Carlos Gay García, Oscar Sánchez Meneses, Benjamín Martínez-López, Àngela Nebot and Francisco Estrada

Abstract: Future scenarios (through 2100) developed by the Intergovernmental Panel on Climate Change (IPCC) indicate a wide range of concentrations of greenhouse gases (GHG) and aerosols, and the corresponding range of temperatures. These data, allow inferring that higher temperature increases are directly related to higher emission levels of GHG and to the increase in their atmospheric concentrations. It is evident that lower temperature increases are related to smaller amounts of emissions and, to lower GHG concentrations. In this work, simple linguistic rules are extracted from results obtained through the use of simple linear scenarios of emissions of GHG in the Magicc model. These rules describe the relations between the GHG, their concentrations, the radiative forcing associated with these concentrations, and the corresponding temperature changes. These rules are used to build a fuzzy model, which uses concentration values of GHG as input variables and gives, as output, the temperature increase projected for year 2100. A second fuzzy model is presented on the temperature increases obtained from the same model but including a second source of uncertainty: climate sensitivity. Both models are very attractive because their simplicity and capability to integrate the uncertainties to the input (emissions, sensitivity) and the output (temperature).

Paper Nr: 4
Title:

Prediction of PM2.5 Concentrations using Fuzzy Inductive Reasoning in Mexico City

Authors:

Àngela Nebot and Francisco Mugica

Abstract: The research presented in this paper is focused on the study and development of fuzzy inductive reasoning models that allow the forecasting of daily particulate matter with diameter of 2.5 micrometres or less (PM2.5). FIR offers a model-based approach to modelling and predicting either univariate or multivariate time series. In this research, predictions of PM2.5 concentration at hour 12 of the next day, in the downtown of Mexico City Metropolitan Area, are performed. The data were registered every hour and include missing values. In this work the hourly modelling perspective is analyzed. The results are compared with the ones obtained using persistence models showing that the FIR models are able to predict PM2.5 concentrations more accurately than persistence models.

Paper Nr: 5
Title:

Rings in the Gulf of Mexico and Stochastic Resonance

Authors:

Benjamín Martínez-López, Jorge Zavala-Hidalgo and Carlos Gay García

Abstract: In this work, we used a nonlinear, reduced gravity model of the Gulf of Mexico to study the effect of a seasonal variation of the reduced gravity parameter on ring-shedding behaviour. When small amplitudes of the seasonal variation are used, the distributions of ring-shedding periods are bi-modal. When the amplitude of the seasonal variation is large enough, the ring-shedding events shift to a regime with a constant, yearly period. If the seasonal amplitude of the reduce gravity parameter is small but a noise term is included, then a yearly regime is obtained, suggesting that stochastic resonance could play a role in the ring-shedding process taking place in the Gulf of Mexico.