Land use and water quality response in the northern region of Changxing County

In this paper, taking the northern region of Changxing County for example, with ammonia nitrogen as a pollution assessment index, we used an improved export coefficient method for estimate polluting load of non-point source pollution (NSP) and the social pollution survey data in the study area to estimate point source pollution. By comparing the total pollution output and the national surface water environmental quality standards find that the whole study area achieves the second water quality standard. However, Jiapu Township exceeds the water quality standards seriously because of the superfluous point source pollution. The water quality of other Townships is good. Further analysis showed that different types of land use and proportions in the northern region of Changxing County have a significant impact on the non-point source pollution, the general law is farmland contributes the largest share of the non-point source pollution output, followed by residential area and bare land, besides, with the increase in the proportion of forest and the decrease of farmland and residential area, the non-point source pollution reduces gradually. © 2010 IEEE.

Synchronous chaos in the coupled system of two logistic maps

Synchronous chaos is investigated in the coupled system of two Logistic maps. Although the diffusive coupling admits all synchronized motions, the stabilities of their configurations are dependent on the transverse Lyapunov exponents while independent of the longitudinal Lyapunov exponents. It is shown that synchronous chaos is structurally stable with respect to the system parameters. The mean motion is the pseudo-orbit of an individual local map so that its dynamics can be described by the local map. (C) 2004 Elsevier Ltd. All rights reserved.

An Extension of Self-Organizing Maps to Categorical Data

Self-organizing maps (SOM) have been recognized as a powerful tool in data exploratoration, especially for the tasks of clustering on high dimensional data. However, clustering on categorical data is still a challenge for SOM. This paper aims to extend standard SOM to handle feature values of categorical type. A batch SOM algorithm (NCSOM) is presented concerning the dissimilarity measure and update method of map evolution for both numeric and categorical features simultaneously.