Study On Forest Ecosystem Health Early Warning Of Beijing Mountain Area Based On Rough Set Theory

Protection of forests is to protect the human living environment and sustainable development of society. Protection of forest ecosystems is very necessary for Beijing, due to the center of political, economic and cultural of China. In this thesis, an early warning system are built, based on theory of forest health, early warning and rough set theory, as well as evaluation of forest health and forest health warning. We study the need for forest health, the importance of early warning research, analysis of factors affecting forest health and the role of incentives systematically. And also the process of forest health warning is analyzed in depth based on the PSR framework. According to the idea of constructing of forest health warning system, a forest health early warning systems was built; based on rough set model, a model of forest health warning was constructed and calculate the indicator properties and weight reduction calculation; Through the establishment of early warning and the warning expert database management system we achieve the Early Warning Control Subsystem function.Research on early warning of forest health is combination of forest health and early warning theory. In this paper, we first apply the rough set method to early warning of forest health. The rough set theory method is used as early warning model of forest health from reducing to weighting the indicators. Both of them provide a new approach to the early warning of forest health.By integrating the reduction of rough set and BP neural network, we expand the rough set theory in the field of forest health early warning and forecast. Taking the rough set as a preconditioning system of BP neural network, we can simplify the neural network's structure and reduce the training set of neural network so as to save a lot of training time to learn. The hybrid model is applied to the health forecast of Jiufeng National Forest Park, which proves that the model is reasonable and reliable.We use the established forest ecosystem and combine the development status of Beijing forest health for early warning on Beijing forest ecosystem health. The outputs of early warning diagnostic subsystem showed that there are four no warning blocks, four light warning blocks, three heavy warning blocks and one huge warning block in the fifteen forest areas of Beijing. The whole warning of Beijing forest areas is more serious. Forest mangers analyzed the source of forest disease through combining warning controlled subsystem with expert databases. At last, the corresponding forest health restoration measures can be timely and effective provided in order to suffering from exclusions.