Quality requirements of injection molding parts have become more and more stringent. Part weight is one of the most important quality characteristics. A model free optimization method based on the simultaneous perturb...
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ISBN:
(纸本)9781615673278
Quality requirements of injection molding parts have become more and more stringent. Part weight is one of the most important quality characteristics. A model free optimization method based on the simultaneous perturbation stochastic approximation (SPSA) method is presented for the weight control of injection molded parts. The experimental results using different materials show that this model free optimization method is effective for the part weight control.
Terahertz time-domain spectroscopy (THz-TDS) is a newly developed technique in the last decade. A new method to classify tea is proposed based on THz-TDS and pattern recognition method. Four kinds of tea are investiga...
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Heat dissipation is a very important subject during the design of RGB-LED backlighting system on LCD because the heat produced by modern LEDs themselves can excessively influence their characteristics. This paper repo...
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Based on the capacitances obtained from a 12-electrode electrical capacitance tomography (ECT) system and the least-squares support vector machine (LS-SVM) technique, a new method is proposed for the online voidage me...
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Due to the stochastic characteristic of photovoltaic (PV) generation, energy storage devices are indispensable to smooth the power flow and provide the electric energy with high quality. In this paper, an integrated D...
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Due to the stochastic characteristic of photovoltaic (PV) generation, energy storage devices are indispensable to smooth the power flow and provide the electric energy with high quality. In this paper, an integrated DC/DC converter is proposed to realize high performance interfaces for PV array, battery and load. This converter consists of a boost converter for the PV array and a buck/boost converter for the battery, which can realize multifunction including power generation, charge and discharge. The grid-connected and stand-alone operation modes of this converter are analyzed. From this analysis, the control strategies are developed for both modes. A coordination scheme is proposed for the power balance at the stand-alone mode. Simulation and experiments verify the practical feasibility and effectiveness of this multi-function converter.
Recent advances in terahertz wave sources and detectors have resulted in a wide range of applications of the terahertz technique. In this paper, the feasibility of using the terahertz technique for the measurement of ...
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Based on a hybrid flowmeter and a dominant phase identifier, a new system is proposed for oil-water two-phase flow measurement. The hybrid flowmeter consists of an oval gear flowmeter and a Venturi meter. The dominant...
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We abstract the bus transport networks(BTNs)to two kinds of complex networks with space L and spaceP methods *** improved community detecting algorithm(PKM agglomerative algorithm),we analyzethe community property of ...
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We abstract the bus transport networks(BTNs)to two kinds of complex networks with space L and spaceP methods *** improved community detecting algorithm(PKM agglomerative algorithm),we analyzethe community property of two kinds of BTNs *** results show that the BTNs graph described with space Lmethod have obvious community property,but the other kind of BTNs graph described with space P method have *** reason is that the BTNs graph described with space P method have the intense overlapping community propertyand general community division algorithms can not identify this kind of community *** overcome this problem,we propose a novel community structure called N-depth community and present a corresponding community detectingalgorithm,which can detect overlapping *** the novel community structure and detecting algorithmto a BTN evolution model described with space P,whose network property agrees well with real BTNs',we get obviouscommunity property.
Kernel-based methods work by embedding the data into a feature space and then searching linear hypothesis among the embedding data points. The performance is mostly affected by which kernel is used. A promising way is...
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Kernel-based methods work by embedding the data into a feature space and then searching linear hypothesis among the embedding data points. The performance is mostly affected by which kernel is used. A promising way is to learn the kernel from the data automatically. A general regularized risk functional (RRF) criterion for kernel matrix learning is proposed. Compared with the RRF criterion, general RRF criterion takes into account the geometric distributions of the embedding data points. It is proven that the distance between different geometric distributions can be estimated by their centroid distance in the reproducing kernel Hilbert space. Using this criterion for kernel matrix learning leads to a convex quadratically constrained quadratic programming (QCQP) problem. For several commonly used loss functions, their mathematical formulations are given. Experiment results on a collection of benchmark data sets demonstrate the effectiveness of the proposed method.
Diverse modeling frameworks have been utilized with the ultimate goal of translating brain cortical signals into prediction of visible behavior. The inputs to these models are usually multidimensional neural recording...
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