A new type of recurrent neural network is discussed, which provides the potential for modelling unknown nonlinear systems. The proposed network is a generalization of the network described by Elman, which has three la...A new type of recurrent neural network is discussed, which provides the potential for modelling unknown nonlinear systems. The proposed network is a generalization of the network described by Elman, which has three layers including the input layer, the hidden layer and the output layer. The input layer is composed of two different groups of neurons, the group of external input neurons and the group of the internal context neurons. Since arbitrary connections can be allowed from the hidden layer to the context layer, the modified Elman network has more memory space to represent dynamic systems than the Elman network. In addition, it is proved that the proposed network with appropriate neurons in the context layer can approximate the trajectory of a given dynamical system for any fixed finite length of time. The dynamic backpropagation algorithm is used to estimate the weights of both the feedforward and feedback connections. The methods have been successfully applied to the modelling of nonlinear plants.展开更多
In this study, weather condition data such as the monthly average temperature, relative moisture, wind speed, pressure and the calculated wind power values of Zonguldak, Sinop, Dtizce, Bartm, Kastamonu, Bolu and Karab...In this study, weather condition data such as the monthly average temperature, relative moisture, wind speed, pressure and the calculated wind power values of Zonguldak, Sinop, Dtizce, Bartm, Kastamonu, Bolu and Karabi^k cities located in western Black Sea region were examined for 10 year period （2001-2011）. In the modeling of the weather conditions, linear regression analysis was used and the effect of temperature, relative moisture and pressure on wind speed was researched by non-linear regression method. Besides, in this study, the effect of roughness coefficient in cities of western Black Sea region was also taken into consideration and the wind power potentials in 10 m, 25 m and 50 m altitude were researched in detail with the help of WASP （Wind Atlas Analysis and Application） program. In the light of the values obtained by developed models and weather condition data, it was observed that some cities in the western Black Sea region have wind power potential with their effects on environment and energy.展开更多
A new back-analysis method of ground stress is proposed with comprehensive consideration of influence of topography, geology and nonlinear physical mechanical properties of rock on ground stress. This method based on ...A new back-analysis method of ground stress is proposed with comprehensive consideration of influence of topography, geology and nonlinear physical mechanical properties of rock on ground stress. This method based on non-uniform rational B-spline (NURBS) technology provides the means to build a refined three-dimensional finite element model with more accurate meshing under complex terrain and geological conditions. Meanwhile, this method is a back-analysis of ground stress with combination of multivariable linear regression model and neural network (ANN) model. Firstly, the regression model is used to fit approximately boundary loads. Regarding the regressed loads as mean value, some sets of boundary loads with the same interval are constructed according to the principle of orthogonal design, to calculate the corresponding ground stress at the observation positions using finite element method. The results (boundary loads and the corresponding ground stress) are added to the samples for ANN training. And on this basis, an ANN model is established to implement higher precise back-analysis of initial ground stress. A practical application case shows that the relative error between the inversed ground stress and observed value is mostly less than 10 %, which can meet the need of engineering design and construction requirements.展开更多
文摘A new type of recurrent neural network is discussed, which provides the potential for modelling unknown nonlinear systems. The proposed network is a generalization of the network described by Elman, which has three layers including the input layer, the hidden layer and the output layer. The input layer is composed of two different groups of neurons, the group of external input neurons and the group of the internal context neurons. Since arbitrary connections can be allowed from the hidden layer to the context layer, the modified Elman network has more memory space to represent dynamic systems than the Elman network. In addition, it is proved that the proposed network with appropriate neurons in the context layer can approximate the trajectory of a given dynamical system for any fixed finite length of time. The dynamic backpropagation algorithm is used to estimate the weights of both the feedforward and feedback connections. The methods have been successfully applied to the modelling of nonlinear plants.
文摘In this study, weather condition data such as the monthly average temperature, relative moisture, wind speed, pressure and the calculated wind power values of Zonguldak, Sinop, Dtizce, Bartm, Kastamonu, Bolu and Karabi^k cities located in western Black Sea region were examined for 10 year period （2001-2011）. In the modeling of the weather conditions, linear regression analysis was used and the effect of temperature, relative moisture and pressure on wind speed was researched by non-linear regression method. Besides, in this study, the effect of roughness coefficient in cities of western Black Sea region was also taken into consideration and the wind power potentials in 10 m, 25 m and 50 m altitude were researched in detail with the help of WASP （Wind Atlas Analysis and Application） program. In the light of the values obtained by developed models and weather condition data, it was observed that some cities in the western Black Sea region have wind power potential with their effects on environment and energy.
基金Innovative Research Groups of the National Natural Science Foundation of China (No.51021004)National Science Foundation of China (No. 51079096)Program for New Century Excellent Talents in University (No. NCET-08-0391)
文摘A new back-analysis method of ground stress is proposed with comprehensive consideration of influence of topography, geology and nonlinear physical mechanical properties of rock on ground stress. This method based on non-uniform rational B-spline (NURBS) technology provides the means to build a refined three-dimensional finite element model with more accurate meshing under complex terrain and geological conditions. Meanwhile, this method is a back-analysis of ground stress with combination of multivariable linear regression model and neural network (ANN) model. Firstly, the regression model is used to fit approximately boundary loads. Regarding the regressed loads as mean value, some sets of boundary loads with the same interval are constructed according to the principle of orthogonal design, to calculate the corresponding ground stress at the observation positions using finite element method. The results (boundary loads and the corresponding ground stress) are added to the samples for ANN training. And on this basis, an ANN model is established to implement higher precise back-analysis of initial ground stress. A practical application case shows that the relative error between the inversed ground stress and observed value is mostly less than 10 %, which can meet the need of engineering design and construction requirements.
