The evaluation of operation status of thermal power plant plays a important role to measure whether a power plant has a good development. The traditional method of analytic hierarchy process has disadvantage in the as...
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The evaluation of operation status of thermal power plant plays a important role to measure whether a power plant has a good development. The traditional method of analytic hierarchy process has disadvantage in the assignment of judgment matrix, this paper tried to improve the method and applied the modified method to five thermal power plants based on Moody Chart method, and the score of economic indicators of the five power plants is calculated by both methods. The calculation of the example shows the advantage of simplicity and maneuverability in the improved method,and the case verifies the rationality of it.
The identification of flow pattern is a basic and important issue in multiphase systems. However, it is difficult to discern due to the complexity of two-phase flows. In this paper, ordinary Kriging(OK) is applied t...
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The identification of flow pattern is a basic and important issue in multiphase systems. However, it is difficult to discern due to the complexity of two-phase flows. In this paper, ordinary Kriging(OK) is applied to reconstructed the two-phase flow patterns using some accurate data. Three typical flow patterns are preset to verify the effectiveness of the method and two quality assessments are used to verify it. Computational results demonstrate that two-phase flow patterns can be reconstructed successfully. The method is feasible for fluid measurement applications.
In today's society,there are a large number of picture information resources,and images are increasingly being studied in many fields,so it is very important to classify,utilize and manage images *** paper mainly ...
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In today's society,there are a large number of picture information resources,and images are increasingly being studied in many fields,so it is very important to classify,utilize and manage images *** paper mainly studies image classification by using support vector machine(SVM),and it includes the following aspects:introducing the basic theory of SVM,discussing the feature extraction methods based on color feature,spatial features and texture features,aiming at the typical feature extraction algorithms,which includes HOG feature extraction,LBP feature extraction,and Haar-like feature extraction,comparing the advantages and disadvantages of different feature *** on color feature and HOG feature respectively,classify the image with the SVM *** test results show that the SVM classifier combined with image features has good performance,high classification accuracy,fast training speed and excellent results in the image classification of small samples.
Computational models of emotional learning observed in the mammalian brain have inspired diverse self-learning control approaches. These architectures are promising in terms of their fast learning ability and low comp...
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Computational models of emotional learning observed in the mammalian brain have inspired diverse self-learning control approaches. These architectures are promising in terms of their fast learning ability and low computational cost. In this paper, the objective is to establish performance–guaranteed emotional learning–inspired control (ELIC) strategies for autonomous multi–agent systems (MAS), where each agent incorporates an ELIC structure to support the consensus controller. The objective of each ELIC structure is to identify and compensate model differences between the theoretical assumptions taken into account when tuning the consensus protocol, and the real conditions encountered in the real system to be stabilized. Stability of the closed-loop MAS is demonstrated using a Lyapunov analysis. Simulation results based on the consensus task of a group of inverted pendulums demonstrate the effectiveness of the proposed ELIC for stabilization of nonlinear MAS.
How to fast and accurately assess the severity level of COVID-19 is an essential problem, when millions of people are suffering from the pandemic around the world. Currently, the chest CT is regarded as a popular and ...
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Considering a noncentrosymmetric pinning texture composed of a square array of triangular holes, the magnetic flux penetration and expulsion are investigated experimentally and theoretically. A direct visualization of...
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Considering a noncentrosymmetric pinning texture composed of a square array of triangular holes, the magnetic flux penetration and expulsion are investigated experimentally and theoretically. A direct visualization of the magnetic landscape obtained using a magneto-optical technique on a Nb film is complemented by a multiscale numerical modeling. This combined approach allows the magnetic flux dynamics to be identified from the single flux quantum limit up to the macroscopic electromagnetic response. Within the theoretical framework provided by time-dependent Ginzburg-Landau simulations, an estimation of the in-plane current anisotropy is obtained and its dependence with the radius of the curvature of hole vertices is addressed. These simulations show that current crowding plays an important role in channeling the flux motion, favoring hole-to-hole flux hopping rather than promoting interstitial flux displacement in between the holes. The resulting anisotropy of the critical current density gives rise to a distinct pattern of discontinuity lines for increasing and decreasing applied magnetic fields, in sharp contrast to the invariable patterns reported for centrosymmetric pinning potentials. This observation is partially accounted for by the rectification effect, as demonstrated by finite-element modeling. At low temperatures, where magnetic field penetration is dominated by thermomagnetic instabilities, highly directional magnetic flux avalanches with a fingerlike shape are observed to propagate along the easy axis of the pinning potential. This morphology is reproduced by numerical simulations. Our findings demonstrate that anisotropic pinning landscapes and, in particular, ratchet potentials produce subtle modifications to the critical state field profile that are reflected in the distribution of discontinuity lines.
Manifold learning now plays a very important role in machine learning and many relevant applications. Although its superior performance in dealing with nonlinear data distribution, data sparsity is always a thorny kno...
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With the emerging technology for distributed generation and urge of improving quality of service of power supply for energy users, more and more Microgrids (MGs) are integrated into the distributed networks to serve t...
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ISBN:
(数字)9781728131375
ISBN:
(纸本)9781728131382
With the emerging technology for distributed generation and urge of improving quality of service of power supply for energy users, more and more Microgrids (MGs) are integrated into the distributed networks to serve the energy users. These Microgrids are gradually formulating a Multi-Microgrid System (MMGS, Multi-Microgrid System), which will play an important role for the future energy supply. Building a centralized control center not only increases the expense of investment, but also brings the issues of maintaining fairness among energy users. To address these problems, this paper proposes a peer-to-peer method for energy trading of MMGS, based on the idea of decentralized trading. An auction-based trading mechanism suitable for peer-to-peer energy trading is proposed first. For this mechanism, the MGs firstly declare their energy buying bids or selling quotations. Then, the market-clearing price is determined by using a unified weight clearing algorithm in a decentralized manner. By applying the edge technology of Blockchain, the implementation of the proposed peer-to-peer energy trading method, including the architecture, procedures, security check, etc., is also discussed. The proposed Blockchain-based energy trading platform can realize the decentralized and autonomous energy trading of MGs within an MMGS. A case study with an MMGS with 10 MG units is provided to demonstrate the effectiveness of the proposed approach.
The ignition voltage of micro-satellite and MEMS fuse become more and more lower, the conventional electro-explosive devices are hardly meet the requirement. In this paper, Ni-Cr metal film bridge of different size/su...
The ignition voltage of micro-satellite and MEMS fuse become more and more lower, the conventional electro-explosive devices are hardly meet the requirement. In this paper, Ni-Cr metal film bridge of different size/substrate were designed by MEMS processing technology. By using Neyer D-optimal sensitivity test method, it got the result that the threshold of ignition voltage would decrease with the decrease of designing size, and the threshold of ignition voltage with the glass substrate would be less than the silicon substrate.
Recent studies have considered thwarting false data injection (FDI) attacks against state estimation in power grids by proactively perturbing branch susceptances. This approach is known as moving target defense (MTD)....
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