Making Predictions of Global Warming Impacts Using a Semantic Web Tool that Simulates Fuzzy Cognitive Maps

One of the most important environmental problems of our era is Global Warming (GW), which derives its roots mainly from anthropogenic activities and is expected to cause far-reaching and long-lasting impacts to the natural environment, ecosystems and human societies. The purpose of this paper is twofold: (a) to develop a model of the causal relationships that exist in the field of GW, using the well-established Artificial Intelligence technique of Fuzzy Cognitive Maps (FCMs) and (b) to develop a Semantic Web simulation software tool, that visually simulates the FCM dynamic behavior and studies the equilibrium that the FCM dynamic system reaches. Using this generic tool, various scenarios can be imposed to the FCM model and predictions can be made on these, in a what-if manner. The features of the web simulation tool are exhibited using the FCM that was created and concerns Global Warming. By applying Semantic Web technologies, the tool makes the results and the various FCM models, that can be implemented in it, easily accessible to various users or systems, through the Internet. In this way, policy makers can use this technique and tool to make predictions by viewing dynamically the consequences that the system predicts to their imposed scenarios and share them through the world wide web.

Automated summary

This paper aims to simulate and study the causal relationships of Global Warming using Fuzzy Cognitive Maps (FCMs) technology and developing a Semantic Web simulation software tool. The tool allows predictions of the impact under various scenarios and sharing them through the Internet.