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Top2. Artificial Intelligence And The Natural Resources
According to Millington (2006), “the Artificial Intelligence (AI) is about making computers able to perform the thinking tasks that humans and animals are capable of”. In this way, computers can already solve many problems, as arithmetic, sorting, searching, etc. The focus of our studies is on the Cellular Automata (CA) (Burks, 1970) and Multi-Agent-Based Simulation (MABS) techniques (Gilbert & Troitzsch, 1999). In the follow sections, we will present case studies with these techniques with more details. However, many other applications can be done using AI techniques, as neural networks, genetic algorithms or fuzzy sets.
The idea of Neural Networks was inspired from biological nervous systems. In fact, neural networks are an attempt to create systems that work in a similar way to the human brain. The brain consists of tens of billions of neurons densely interconnected. The function of an Artificial Neural Network (ANN) is to produce an output pattern when presented with an input one (Picton, 2000). The ANN has been used in several works related to natural resources management. A good example is the work of Iliadis & Maris (2006). In this work, an ANN performs an effective estimate of the Average Annual Water-Supply on an annual basis, for each mountainous watershed of Cyprus, where there is a lack of drinking water during summer periods. Another example is the work of Ahmad & Simonovic (2005), which presents a framework to show viable alternatives when the hydrologic application requires that an accurate forecast of the stream flow behavior be provided using only the available time series data, and with relatively moderate conceptual understanding of the hydrologic dynamics of the particular watershed under investigation.