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The load identification of the shield machine is presented in this paper by introducing the mechanical analysis of shield excavating into the nonlinear multiple regression of on-site data. The analysis on mechanical characteristics of shield-soil system can decouple the nonlinear multi-parameter problem of load, so it is great helpful for the regression process to establish a load model. Then a load...
The fluctuations and forecasting errors of wind power require large amount of flexibility in power system operation. The flexibility is often provided by conventional thermal generating units. This paper focuses on the variations in operating cost caused by integration of an increasing amount of wind power in thermal generation system. A new chronological production simulation platform utilized for...
This paper presents a mechanical model to predict the operational loads acting on the cutter head of shield tunnel machine during excavation based on contact mechanics theory, in which the cutter head is considered as a rigid cylinder punch and the soil to be excavated is simplified as an elastic half-space. Then the estimation formulae of the operational loads are obtained and the influence of some...
This paper put forward a new method of the fuzzy rules and wavelet neural network model for short-term load forecasting. The neural call function is basis of nonlinear wavelets. We overcome the shortcoming of single train set of fuzzy rules. It can be seen from the example this method can improve effectively the forecast accuracy and speed. The forecast model was tested and the result showed that...
In the software environment with security policy enforced, the behavior of application depends on not only its binary code, but also the enforcing security policy. Therefore, remote attestation for security policy is as important as that for binary code. However, since the specialties of security policy, which include more mutable and mixture of semantics, it is not suitable to use integrity measurement...
This paper put forward a new method of the variable structure artificial neural network model for mid-long term load forecasting. We overcome the shortcoming of single train set of ANN. It can be seen from the example this method can improve effectively the forecast accuracy and speed. The forecast model was tested and the result showed that it was an effective way to forecast mid-long term electric...
This paper proposes a new method for mid-long term load forecasting-fuzzy rules by genetic algorithms based on Takagi-Sugeno Fuzzy Logic System, and establishing the fuzzy model for load forecasting. lt can be seen from the example this method can improve effectively the forecast accuracy and speed. It can be applied to the mid-long term electric load forecasting.
This paper put forward a new method of the fuzzy rules and wavelet neural network model for mid-long term load forecasting. The neural call function is basis of nonlinear wavelets. We overcome the shortcoming of single train set of fuzzy rules. It can be seen from the example this method can improve effectively the forecast accuracy and speed. The forecast model was tested and the result showed that...
This paper put forward a new method of the SVM and fuzzy rules model for short-term load forecasting. The neural call function is basis of nonlinear wavelets. We overcome the shortcoming of single train set of SVM. It can be seen from the example this method can improve effectively the forecast accuracy and speed. The forecast model was tested and the result showed that it was an effective way to...
This paper put forward a new method of the wavelet neural network model for mid-long term load forecasting. The neural call function is basis of nonlinear wavelets. We overcome the shortcoming of single train set of ANN. It can be seen from the example this method can improve effectively the forecast accuracy and speed. The forecast model was tested and the result showed that it was an effective way...
This paper put forward a new method of the SVM and wavelet neural network model for short-term load forecasting. The neural call function is basis of nonlinear wavelets. We overcome the shortcoming of single train set of SVM. It can be seen from the example this method can improve effectively the forecast accuracy and speed. The forecast model was tested and the result showed that it was an effective...
This paper proposes a new method for load forecasting-fuzzy rules by genetic algorithms based on Takagi-Sugeno fuzzy logic system, and establishing the fuzzy model for load forecasting. It can be seen from the example this method can improve effectively the forecast accuracy and speed. It can be applied to the daily electric load forecasting.
Upsetting is an important technics for improving the inner structure of metal. The stress, strain and temperature distribution can influence the effect of upsetting. To achieve good effect of upsetting, a prediction model of upsetting based on thermo-elastic-plastic finite element equation is built. The three-dimensional upsetting process is studied by using the method of finite element Lagrange analysis,...
In the integrated model, which is composed of the vehicle fill problem, VFP for short, and the vehicle scheduling problem, VSP for short, according to their interrelationship and interrestriction, the solution of VFP takes the key role to ensure the whole solutions of the model are high efficient and feasible. By researching on the problem of vehicle loading based on effective space, a method has...
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