Temporal data mining using genetic algorithm and neural network —A case study of air pollutant forecasts

Shine-Wei Lin, Chih-Hong Sun, Chin-Han Chen
2004 Geo-spatial Information Science  
Artificial intelligence technology like neural network and genetic algorithm can easily cope with highly complicated and non-linear combined spatial and temporal issues. Therefore this paper integrated genetic algorithm and neural network techniques to build new temporal predicting analysis tools for Geographic Information System (GIS). These new GIS tools can be readily applied in a practical and appropriate manner in spatial and temporal research to patch the gaps in GIS data mining and
more » ... dge discovery functions. The specific achievement here is the integration of related artificial intelligent technologies into GIS software to establish a conceptual spatial and temporal analysis framework. And, by using this framework to develop an Artificial intelligent Spatial and temporal Information Analyst (ASIA) system which then is fully utilized in the existing GIS package so that it is convenient for the domain experts to work with it and apply it. This study of air pollutants forecasting provides a geographical practical case to prove the rationalization and justness of the conceptual temporal analysis framework.
doi:10.1007/bf02826674 fatcat:ds4yyw7dk5fmfcnywqmav5xbne