10-11-2014, 10:11 AM
Abstracts: Artificial intelligence technology like neural network and genetic algorithm can easily cope with highly complicated and non-linear combined spatial issues. Therefore we are going to work with genetic algorithm and neural network techniques to build new predicting analysis tools for air pollutant forecasting. This new tool can be readily applied in a practical and appropriate manner in spatial research to patch the gaps in data mining and knowledge discovery functions. This study of air pollutants forecasting provides a geographical practical case to prove the functionality of the conceptual temporal analysis framework.