Fractal dimensions of a terrain quantitatively describe the self-organizedstructure of the terrain geometry. However, the local topographic variation cannot be illustrated bythe conventional box-counting method. This ...Fractal dimensions of a terrain quantitatively describe the self-organizedstructure of the terrain geometry. However, the local topographic variation cannot be illustrated bythe conventional box-counting method. This paper proposes a successive shift box-counting method,in which the studied object is divided into small sub-objects that are composed of a series of gridsaccording to its characteristic scaling. The terrain fractal dimensions in the grids are calculatedwith the successive shift box-counting method and the scattered points with values of fractaldimensions are obtained. The present research shows that the planar variation of fractal dimensionsis well consistent with fault traces and geological boundaries.展开更多
Based on the research of Particle Swarm Optimization (PSO) learning rate, two learning rates are changed linearly with velocity-formula evolving in order to adjust the proportion of social part and cognitional part; t...Based on the research of Particle Swarm Optimization (PSO) learning rate, two learning rates are changed linearly with velocity-formula evolving in order to adjust the proportion of social part and cognitional part; then the methods are applied to BP neural network training, the convergence rate is heavily accelerated and locally optional solution is avoided. According to actual data of two levels compound-box in vibration lab, signals are analyzed and their characteristic values are abstracted. By applying the trained BP neural networks to compound-box fault diagnosis, it is indicated that the methods are sound effective.展开更多
文摘Fractal dimensions of a terrain quantitatively describe the self-organizedstructure of the terrain geometry. However, the local topographic variation cannot be illustrated bythe conventional box-counting method. This paper proposes a successive shift box-counting method,in which the studied object is divided into small sub-objects that are composed of a series of gridsaccording to its characteristic scaling. The terrain fractal dimensions in the grids are calculatedwith the successive shift box-counting method and the scattered points with values of fractaldimensions are obtained. The present research shows that the planar variation of fractal dimensionsis well consistent with fault traces and geological boundaries.
基金Supported by National Natural Science Foundation (No.50575214)
文摘Based on the research of Particle Swarm Optimization (PSO) learning rate, two learning rates are changed linearly with velocity-formula evolving in order to adjust the proportion of social part and cognitional part; then the methods are applied to BP neural network training, the convergence rate is heavily accelerated and locally optional solution is avoided. According to actual data of two levels compound-box in vibration lab, signals are analyzed and their characteristic values are abstracted. By applying the trained BP neural networks to compound-box fault diagnosis, it is indicated that the methods are sound effective.
