According to weather sampling data from static GMS-5 images,the projections of IR1,IR2,VS WV in high-dimension feature spaces such as gray degree,grade degree and veins can be clustered. In this way,we can get to know the subject area of each weather sample in the feature spaces,so that we can get the weather classification of each nephogram.

Based on the sample data of GMS-5 stationary satellite, a high-dimension spectral feature space combining with gray and grads values of infrared, vapour and visible light channels images was constructed, and corresponding clustering analysis was performed.

Finally, the clustering regions of the various weather kind in the high-dimension spectral feature space were divided up by computing a actual image's gray and grads values and judging their mapping location in the high-dimension feature space, the weather kind of the image pels is distinguished, and the auto classification of the satellite cloud image is also carried out.

The machine conceptually implements the following idea: input vectors are non-linearly mapped to a very high-dimension feature space.

The machine conceptually implements the following idea: input vectors are non-linearly mapped to a very high-dimension feature space.

Low-and high-dimension limits of a phase separation model

The Belinsky-Zakharov inverse scatteringmethod is extended to a double high-dimension form.

Algorithms of determining maximum (in modulus) complex-conjugate eigenvalues are considered as applied to finding eigenvalues of high-dimension matrices according to the Khilenko method.

Based on the concept of attractors of nonlinear system, the phase space with higher dimension is reconstructed by using observed single meteorological time series and then the weather attractor is embedded in it. The dimension of weather attractor and the weather predictability can be estimated from the time evolution of initially close pieces of trajectories. Computation results used daily data sets of the general circulation index at 500 hPa in Asia and Beijing temperature in wintertime show the fractal dimensions...

Based on the concept of attractors of nonlinear system, the phase space with higher dimension is reconstructed by using observed single meteorological time series and then the weather attractor is embedded in it. The dimension of weather attractor and the weather predictability can be estimated from the time evolution of initially close pieces of trajectories. Computation results used daily data sets of the general circulation index at 500 hPa in Asia and Beijing temperature in wintertime show the fractal dimensions of 3.8 and 5.4 for these two attractors, respectively; and for which predictability time scale of 6-14 days, while weather predictability time scale of 4-9 days resulted from the e-folding expansion of trajectories in phase space.

The difficuities in forecasting weather result from non－linearity、high—dimension and data’s lack of preciseness．Consequently’we take advantage of Artificial NeuralNetwork to solve meteorological problems． Back－Propagation network is used to forecast the intensity of Southwest Vortex’s rainfall over the southwestern part of Shandong province in China．After learning by itself，network automatically abstracts the relationship between predctors and predictand from historical data．Finally，we areable to make a comparably...

The difficuities in forecasting weather result from non－linearity、high—dimension and data’s lack of preciseness．Consequently’we take advantage of Artificial NeuralNetwork to solve meteorological problems． Back－Propagation network is used to forecast the intensity of Southwest Vortex’s rainfall over the southwestern part of Shandong province in China．After learning by itself，network automatically abstracts the relationship between predctors and predictand from historical data．Finally，we areable to make a comparably ocrrect prediction by means of BP network．

From the viewpoint of system theory, the concept of complex large system for flood disaster is put forward, and some aspects of its characteristics such as high dimension, dynamics and complexity are discussed. Based on the comprehensive methodology with qualitative and quantilative integration, the comprehensive methodology of flood disaster analysis such as simulation, forecasting and evaluation as well as decision are investigated. Therefore,...

From the viewpoint of system theory, the concept of complex large system for flood disaster is put forward, and some aspects of its characteristics such as high dimension, dynamics and complexity are discussed. Based on the comprehensive methodology with qualitative and quantilative integration, the comprehensive methodology of flood disaster analysis such as simulation, forecasting and evaluation as well as decision are investigated. Therefore, it will provide the scientific basis for investigating the methodology for the management and control on flood disaster, and it is helpful for improving the relationships among resource and environmant as well as social development.