A Hybrid Expert System for the Estimation of the Environmental Impact of Urban Development

Abstract

Aims: In this paper we present a prototype of a computational system, running on the web, for the estimation of environmental impact caused by urban development. The system represents and manipulates the expert knowledge of the environmental impact domain through the collaborative interaction of two important artificial intelligence techniques: expert systems and neural networks. Methodology: We used an environmental impact estimation methodology based on three phases that are: the identification, characterization and evaluation of the environmental impact. Specifically, the system uses heuristic rules for the identification of environmental impacts; neural networks for the impacts characterization and decision algorithms for their evaluation. Results: The main result of this work is a prototype of a computational platform, highly visual and interactive, that provides the user with a continuous availability of knowledge and procedures used by experts for the analysis and the assessment of environmental impacts. The user provides the system with previously recollected data of environmental scenarios, and the system produces estimations about the possible negative consequences entailed by a new urban project. Conclusion: We represented and implemented the expert knowledge and procedures for the estimation of environmental impact. We discussed the design and implementation of a computational system that provides support to the estimation of environmental impacts generated by urban development. This estimation is very important because it allows proposing measures that reduce, eliminate or compensate significant environmental impacts.