Applications Of Artificial Neural Network In Intelligent Spatial Decision Support System

Geographic information system is more and more important in modern society, because the geographic information system not only provides the rich spatial information for us, but also provides the supporting information for us through its formidable spatial analysis ability. The geographic information system has provided the formidable data capture, storage, display's tool for the decision support, but its analysis and inference function is quite weak, essentially it is a data rich but the knowledge deficient system which lacks the intelligent inference function to solve complex spatial decision support problem, therefore, need to develop the Intelligent Spatial Decision Support Systems(ISDSS) based on geographic information system, it will be used in the data capture, input, storage, analysis and output; in the knowledge representation and inference; in automatically learning; system integration; man-machine interactive.As for ISDSS, the symbolic approaches were still one kind of important knowledge representation and the inference method. But the artificial neural network which has the massively parallel distributional structure has the superiority which the other means does not have. No matter which approaches ISDSS does apply, the bottleneck which restricts the ISDSS development will be the spatial knowledge acquire, so the ability of data mining and discovery knowledge from spatial database is very important. Therefore studies about the artificial neural network as well as other intelligent methods in the spatial knowledge acquire, representation and inference is vital significance for the problem above. In this article the mainly focus on is the application of artificial neural network in the spatial intelligent decision support systems. The main work has the following aspects:1. The spatial mathematical models building based on the neural networkBP neural network model with hide units may estimate any continuous function by the any precision, so the artificial neural network has important role in the GIS data model building, it is one of GIS effective tools in this domain. In this article, the spatial mathematical model building based on neural network is discussed, it introduces the essential neuron concept in the spatial model building, and this can reduce the redundant neuron units in the neural network, and enables the spatial mathematical model simply and effectively.2. Spatial knowledge representation and inference based on neural networkThe knowledge representation and the inference are the key problem in intelligent decision support systems. In order to understand and carries on the inference, the intelligent system needs to capture the related domain knowledge. Because the spatial decision support systems is a intelligent system for inference, so the spatial knowledge representation and the inference is the key question. In this article, the traditional knowledge representation and inference is introduced, and then the artificial neural network method for knowledge representation and inference isproposed. Because its stronger fault-tolerant, massively parallel handling and learning capability, therefore it will be the effective method in the spatial decision support systems or a powerful supplement. The uncertainty spatial knowledge's representation and inference is also discussed, the fuzzy neural network is used in uncertainty spatial knowledge representation and inference. 3. Spatial data mining and knowledge discovery based on neural networkThe spatial knowledge is the vital factor for the spatial intelligence decision support systems, it is also the bottleneck in spatial decision support systems , so the acquire spatial knowledge is the primary mission in intelligent spatial decision support systems. The spatial data mining and the knowledge discovery technology is just for this need. In spatial database, there are many spatial knowledge can be discovered, there are also many methods can be used for spatial data mining and knowledge discovery. The main method used in spa...