A splicing system based genetic algorithm is proposed to optimize dynamical radial basis function(RBF)neural network,which is used to extract valuable process information from input output data.The novel RBF net-work ...A splicing system based genetic algorithm is proposed to optimize dynamical radial basis function(RBF)neural network,which is used to extract valuable process information from input output data.The novel RBF net-work training technique includes the network structure into the set of function centers by compromising between the conflicting requirements of reducing prediction error and simultaneously decreasing model complexity.The ef-fectiveness of the proposed method is illustrated through the development of dynamic models as a benchmark discrete example and a continuous stirred tank reactor by comparing with several different RBF network training methods.展开更多
It always adopts the direct hierarchy analysis to value the exploitation conditions of surface mining areas. This way has some unavoidable shortcomings because it is mainly under the aid of experts and it is affected ...It always adopts the direct hierarchy analysis to value the exploitation conditions of surface mining areas. This way has some unavoidable shortcomings because it is mainly under the aid of experts and it is affected by the subjective thinking of the experts. This paper puts forwards a new approach that divides the whole exploitation conditions into sixteen subsidiary systems and each subsidiary system forms a neural network system. The whole decision system of exploitation conditions of surface mining areas is composed of sixteen subsidiary neural network systems. Each neural network is practiced with the data of the worksite, which is reasonable and scientific. This way will be a new decision approach for exploiting the surface mining areas.展开更多
Networks are a class of general systems represented by becomes a weighted graph visualizing the constraints imposed their UC-structure. Suppressing the nature of elements the network by interconnections rather than th...Networks are a class of general systems represented by becomes a weighted graph visualizing the constraints imposed their UC-structure. Suppressing the nature of elements the network by interconnections rather than the elements themselves. These constraints follow generalized Kirchhoff＇s laws derived from physical constraints. Once we have a graph; then the working environment becomes the graph-theory. An algorithm derived from graph theory is developed within the paper in order to analyze general networks. The algorithm is based on computing all the spanning trees in the graph G with an associated weight. This weight is the product ofadmittance＇s of the edges forming the spanning tree. In the first phase this algorithm computes a depth first spanning tree together with its cotree. Both are used as parents for controlled generation of off-springs. The control is represented in selecting the off-springs that were not generated previously. While the generation of off-springs, is based on replacement of one or more tree edges by cycle edges corresponding to cotree edges. The algorithm can generate a frequency domain analysis of the network.展开更多
The hot-dip galvanizing line(HDGL) is a typical order-driven discrete-event process in steelmaking. It has some complicated dynamic characteristics such as a large time-varying delay, strong nonlinearity, and unmeasur...The hot-dip galvanizing line(HDGL) is a typical order-driven discrete-event process in steelmaking. It has some complicated dynamic characteristics such as a large time-varying delay, strong nonlinearity, and unmeasured disturbance, all of which lead to the difficulty of an online coating weight controller design. We propose a novel neural network based control system to solve these problems. The proposed method has been successfully applied to a real production line at Va Lin LY Steel Co., Loudi, China. The industrial application results show the effectiveness and efficiency of the proposed method, including significant reductions in the variance of the coating weight and the transition time.展开更多
基金Supported by the National Natural Science Foundation of China (No.60421002)the National High Technology Research and Development Program of China (863 Program,2006AA040308).
文摘A splicing system based genetic algorithm is proposed to optimize dynamical radial basis function(RBF)neural network,which is used to extract valuable process information from input output data.The novel RBF net-work training technique includes the network structure into the set of function centers by compromising between the conflicting requirements of reducing prediction error and simultaneously decreasing model complexity.The ef-fectiveness of the proposed method is illustrated through the development of dynamic models as a benchmark discrete example and a continuous stirred tank reactor by comparing with several different RBF network training methods.
文摘It always adopts the direct hierarchy analysis to value the exploitation conditions of surface mining areas. This way has some unavoidable shortcomings because it is mainly under the aid of experts and it is affected by the subjective thinking of the experts. This paper puts forwards a new approach that divides the whole exploitation conditions into sixteen subsidiary systems and each subsidiary system forms a neural network system. The whole decision system of exploitation conditions of surface mining areas is composed of sixteen subsidiary neural network systems. Each neural network is practiced with the data of the worksite, which is reasonable and scientific. This way will be a new decision approach for exploiting the surface mining areas.
文摘Networks are a class of general systems represented by becomes a weighted graph visualizing the constraints imposed their UC-structure. Suppressing the nature of elements the network by interconnections rather than the elements themselves. These constraints follow generalized Kirchhoff＇s laws derived from physical constraints. Once we have a graph; then the working environment becomes the graph-theory. An algorithm derived from graph theory is developed within the paper in order to analyze general networks. The algorithm is based on computing all the spanning trees in the graph G with an associated weight. This weight is the product ofadmittance＇s of the edges forming the spanning tree. In the first phase this algorithm computes a depth first spanning tree together with its cotree. Both are used as parents for controlled generation of off-springs. The control is represented in selecting the off-springs that were not generated previously. While the generation of off-springs, is based on replacement of one or more tree edges by cycle edges corresponding to cotree edges. The algorithm can generate a frequency domain analysis of the network.
文摘The hot-dip galvanizing line(HDGL) is a typical order-driven discrete-event process in steelmaking. It has some complicated dynamic characteristics such as a large time-varying delay, strong nonlinearity, and unmeasured disturbance, all of which lead to the difficulty of an online coating weight controller design. We propose a novel neural network based control system to solve these problems. The proposed method has been successfully applied to a real production line at Va Lin LY Steel Co., Loudi, China. The industrial application results show the effectiveness and efficiency of the proposed method, including significant reductions in the variance of the coating weight and the transition time.
