MSCCEC 2014 Abstracts


Full Papers
Paper Nr: 1
Title:

Price Responses of Grain Market under Climate Change in Pre-industrial Western Europe by ARX Modelling

Authors:

Qing Pei, David D. Zhang and Jingjing Xu

Abstract: In academia, there are few studies adopted ARX modelling on historical datasets. Recently, the studies on notable effects of climatic changes upon past agrarian economy are paid by more attention. Here, this study first time seriously explores the relationship between climatic change and the grain market at a macro-scale in pre-industrial Western Europe by ARX modelling. The results show that a cold phase would raise grain price through lowering the supply in the grain market. Furthermore, according to the simulations on shortand long-term climate change, the long lasting climate change could be more disastrous to society than short-term change. Last, the application in the study proves ARX modelling is also a feasible choice in the field of historical research.

Paper Nr: 2
Title:

Global Temperature Fuzzy Model as a Function of Carbon Emissions - A Fuzzy ‘Regression’ from Historical Data

Authors:

Carlos G. Gay and Bernardo O. Bastien

Abstract: There are several models that correlate global mean temperature with Carbon emissions using statistical analysis; in this study we approach the problem using fuzzy logic analysis and inference systems, which is a pioneer method in climate modelling. The process in which anthropogenic activity affects the atmospheric Carbon and therefore the global mean temperature, has been well studied but there are still a lot of unknown factors that play an important role in the process, e.g. punctual Carbon sequestration processes, economyled emissions’ fluctuations, etcetera. That way the process take no clear path and is when fuzzy logic is ideal to approach the system understanding. In this study a Fuzzy Inference System is developed, which model the problem using historical data from 1959 to present. Our model has good results quite comparable with statistical models and it can be used to project the future global mean temperature. The model was developed using SIMULINK extension from matlab.

Paper Nr: 3
Title:

Ocean Remote Sensing Data Predicts Trajectory of Oil Spill - An Analytical Model for SAR Polarimetric Scattering Matrix

Authors:

Bo wang, Bertrand Chapron and Rene Garello

Abstract: The ocean surface is part of the upper ocean which directly interacts with the overlying atmosphere and sea ice. Once oil spill happened due to an accident such as the oil rig pipe leaking and exploring, it would be unimaginable disaster to the oceanic environment, especially in the coastal area. If we can predict the direction along which the oil films floats over the marginal sea surface, the damage would be controlled within a pre-knowledge level. Under these knowledge, we analysed the polarimetric SAR (Synthetic Aperture Radar) data with an analytical model to separate backscattered contributions by different sea surface scatterers. Furthermore, it provides a possible prediction of the local wind direction by using the separated backscattered signal. With this direction, it is ready to predict the direction of oil film’s floating.

Paper Nr: 4
Title:

A Holistic Seismic Risk Scheme Using Fuzzy Sets - Part One: The Social System Fragility

Authors:

Rubén González, Àngela Nebot, Francisco Mugica, Martha-Liliana Carreño and Alex H. Barbat

Abstract: Hazard related Risk is a strange concept since its represents something that has not happened yet, something which is blur and randomness related. Along its estimation, social vulnerability aspects come to arise. Such aspects are even more difficult to define in part because there is still missing a robust way to quantify them and, therefore, to establish a clear analytic framework useful to understand inherent complexities of a human society. In this paper, we build a social aggravation coefficient fuzzy model considering Cardona-Carre˜no aggravation descriptors. By reducing the number of aggravation descriptors and establishing fuzzy logic rules between them, we found similar results in tendency and spatial distribution for seismic resilience and fragility at Barcelona, Spain. We used a classical Mamdani fuzzy approach, supported by well established fuzzy theory, which is characterized by a high expressive power and an intuitive human-like manner. We believe that in this way, a more clear analyses of the resilience and fragility bond can be done exploiting in a more suitable way fuzzy logic capabilities, because the inference process to obtain an aggravation coefficient is based precisely on the establishment of rules (if-then type) directly over the involved variables in social vulnerability formation which allows a smooth application of risk management knowledge, encouraging debate over the used rules, besides the discussion among the employed membership functions.

Paper Nr: 5
Title:

MASC: Map Sectors Creator - A Tool to Help at the Configuration of Multi-Agents Systems for Everyone

Authors:

Aurélie Gaudieux, Joël Kwan, Yasine Gangat and Rémy Courdier

Abstract: The initialization at the beginning of all type of simulation is recurring. In the field of multi-agents, spatial environments on a micro or macro scale, or more abstract context, such as mapping out energy sources for example, need often to be modelled. The initialization of these environments wherein evolve agents is generally tedious and time-consuming depending on the fineness of the mesh of the cutting in case of a 2D spatial representation. In this paper, we present MASC (Map Sectors Creator), a user-oriented tool that permits easy initialization through the creation of a mesh directly usable in multi-agents systems simulations platforms. The automation of cutting out maps followed by the generation of directly usable code snippets optimize the working time on initialization and allow to focus on the simulations results and observations.

Paper Nr: 6
Title:

Fuzzy Modeling of Migration from the State of Oaxaca, Mexico

Authors:

Anais Vermonden and Carlos Gay

Abstract: This study shows an important innovation with the use of fuzzy logic to develop models on the migration factors occurring in the state of Oaxaca, México, since fuzzy logic has not been applied in this field. Migration is a complex system as individuals make their own decision to migrate. The major factors causing migration are: higher employment in the primary sector, high grades of unemployment, high marginalization index, small communities, soil degradation, violence and remittance received. Another tendency shown in these models is that municipalities in Oaxaca with greater levels of education are having higher migration levels due to the lack of opportunities to continue studies or well-paid jobs. Climate change may impose greater movement of people as it can worsen the already precarious soil situation. Even if the models present some error in the calculation of the migration index, it made clear what other variables should be included to show the impacts of climate change on migration.

Paper Nr: 7
Title:

Using Fuzzy Cognitive Mapping and Nonlinear Hebbian Learning for Modeling, Simulation and Assessment of the Climate System, Based on a Planetary Boundaries Framework

Authors:

Iván Paz-Ortiz and Carlos Gay-Garcia

Abstract: In the present work a fuzzy cognitive map for the qualitative assessment of the Earth climate system is developed by considering subsystems on which the climate equilibrium depends. The cognitive map was developed as a collective map by aggregating different experts opinions. The resulting network was characterized by graph indexes and used for simulation and analysis of hidden pattens and model sensitivity. Linguistic variables were used to fuzzify the edges and were aggregated to produce an overall linguistic weight for each edge. The resulting linguistic weights were defuzzified using the “Center of Gravity”, and the current state of the Earth climate system was simulated and discussed. Finally, a nonlinear Hebbian Learning algorithm was used for updating the edges of the map until a desired state. The overall results are discussed to explore possible policy implementation, environmental decision making and management.

Paper Nr: 8
Title:

The Fuzzy Nature of Climate Change Scenarios Maps

Authors:

Carlos Gay García and Oscar Sánchez Meneses

Abstract: The most important uncertainties present in the global change scenarios are the climate sensibility, represented by the wide variety of GCM´s available, and the uncertainty that comes from the different GHG emission scenarios. Starting from a fuzzy climate model constructed with concentrations of GHG, obtained as a result of linear emission pathways, and output temperatures obtained with a deterministic simple climate model (MAGICC) it has been determinate the output fuzzy set of global delta T thresholds such as 1, 2, 3 and 4 °C for 2100 and a medium sensibility of 3.0 °C/W/m2. These fuzzy sets are used for assign uncertainties to values of temperature increase and precipitation change percentage taken from a map of regional climate change and for interpret the map in a fuzzy sense. We present some maps of temperature increase and precipitation change percentage for Mexico.