Hybrid Systems Knowledge Representation Using Modelling Environment System Techniques Artificial Intelligence
This addresses the need for better methods to handle increasing complexity in environmental modeling, though it appears incremental in proposing hybrid approaches.
The paper examines different AI techniques for modeling environmental systems and proposes that hybrid mechanisms combining multiple methods could create more advanced systems capable of incorporating human decisions to drive landscape changes.
Knowledge-based or Artificial Intelligence techniques are used increasingly as alternatives to more classical techniques to model ENVIRONMENTAL SYSTEMS. Use of Artificial Intelligence (AI) in environmental modelling has increased with recognition of its potential. In this paper we examine the DIFFERENT TECHNIQUES of Artificial intelligence with profound examples of human perception, learning and reasoning to solve complex problems. However with the increase of complexity better methods are required. Keeping in view of the above some researchers introduced the idea of hybrid mechanism in which two or more methods can be combined which seems to be a positive effort for creating a more complex; advanced and intelligent system which has the capability to in- cooperate human decisions thus driving the landscape changes.