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Keywords: Takagi–Sugeno model System identification Heuristic algorithms Hydraulic turbine governing system Chaotic gravitational search algorithm Fuzzy c-regression model a b s t r a c t Hydraulic turbine governing system (HTGS) is a complicated nonlinear system that controls the frequency and power output of hydroelectric generating unit (HGU). The(More)
For Product Named Entity Recognition, Conditional Random Fields model is used in this paper. By introducing the domain ontology features to the CRFs model can improve the performance of Product Named Entity Recognition, and experiments were made to compare the two kinds of feature templates. Empirical results show that the PNER based on CRFs model with(More)
Convex 1-D first-order total variation (TV) denoising is an effective method for eliminating signal noise, which can be defined as convex optimization consisting of a quadratic data fidelity term and a non-convex regularization term. It not only ensures strict convex for optimization problems, but also improves the sparseness of the total variation term by(More)
Mechanical vibration signal mapped into a high-dimensional space tends to exhibit a special distribution and movement characteristics, which can further reveal the dynamic behavior of the original time series. As the most natural representation of high-dimensional data, tensor can preserve the intrinsic structure of the data to the maximum extent. Thus, the(More)
For the case of complicated turbulent velocity distribution caused by the pipeline structure of hydraulic unit, a method of multi-channel ultrasonic flow rate measurement based on piecewise curve fitting is proposed. In this method, the line mean velocities are obtained by the multi-channel parallel layers measurement. According to the features of the fluid(More)
A framework for product named entity recognition in Chinese was presented using Conditional Random Fields with multiple features in this paper. It differentiates from most of the previous approaches mainly as follows. Firstly, introducing the domain ontology features to the CRFs model can use its semantic information. Secondly, combining internal and(More)
This paper presented a novel procedure based on the ensemble empirical mode decomposition and extreme learning machine. Firstly, EEMD was utilized to decompose the vibration signals into a number of IMFs adaptively and the permutation entropy of each IMF was calculated to generate the fault feature matrix. Secondly, a new extreme learning machine was(More)