The pixel-based classification of remotely sensed images always produces a large amount of "speckled" or "salt and pepper" noises. Both post-classification smoothing and object-based classification...
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ISBN:
(纸本)9781479939046
The pixel-based classification of remotely sensed images always produces a large amount of "speckled" or "salt and pepper" noises. Both post-classification smoothing and object-based classification techniques have been proposed to tackle this problem. However, most of them are not adequate to deal with the noises in object-based classification of very high resolution (VHR) remote sensing imagery, because a lot of noisy regions will be produced by image segmentation and the existing post-classification approaches generally are tailored towards pixel-based classification. This paper proposes a novel noise removal approach for object-based classification of VHR imagery via post-classification. It includes four phases: firstly, an image is segmented into homogeneous regions;secondly, all regions are classified according to their spectral and texture features;thirdly, noisy regions are distinguished by using shape features. Finally, the noisy regions are removed by using contextual features. Experimental results show the proposed approach is effective and can improve the overall accuracy of classification of VHR remote sensing imagery.
Low cycle fatigue life of a steam turbine rotor is predicted using a new CDM model. A simulation experiment is made to compute the damage accumulation of a 300 MW steam turbine rotor under cold start. Adopting the cyc...
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ISBN:
(纸本)9781479947249
Low cycle fatigue life of a steam turbine rotor is predicted using a new CDM model. A simulation experiment is made to compute the damage accumulation of a 300 MW steam turbine rotor under cold start. Adopting the cyclic stress-strain relation,this new continuum damage mechanics model exhibits a conservative character. Comparison with result of the linear accumulation theory and practical test data indicates that present new nonlinear CDM model describes the damage accumulation more precisely and reasonably in engineering.
A new visual monitoring communication algorithm model is described in this paper which can improve the communication efficiency between the PLC(programmable logic controller) and its programming software. The model co...
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ISBN:
(纸本)9781784660468
A new visual monitoring communication algorithm model is described in this paper which can improve the communication efficiency between the PLC(programmable logic controller) and its programming software. The model consists of dynamic packaging algorithm and scrolling view algorithm aiming at meeting real-time visual monitoring. It is described in detail that how to adjust the length of communication data frame and refresh the data of current scrolling view of the programming software concerning the algorithm model. The experimental results show that the communication efficiency and the interface refreshing properties of visual monitoring will be improved with the increase of communication traffic load which proves that the algorithm modelling is effective.
This paper presents a compound fuzzy PID control strategy for the thrust hydraulic controlsystem of hard rock tunnel boring *** dynamic mathematical model of thrust hydraulic system is built and implemented in DSHplu...
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This paper presents a compound fuzzy PID control strategy for the thrust hydraulic controlsystem of hard rock tunnel boring *** dynamic mathematical model of thrust hydraulic system is built and implemented in DSHplus software *** control strategy of speed and pressure is proposed to handle the control problem of thrust hydraulic *** logic PID technique is adopted to deal with the nonlinearity of the thrust hydraulic *** are carried out to verify the performance of proposed compound control strategy.
In this paper, we investigate the dynamic modeling and trajectory tracking control of hard rock Tunnel Boring Machine(TBM). The acceleration equation, moment of momentum equation, kinematics equation and orientation e...
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ISBN:
(纸本)9781479937097
In this paper, we investigate the dynamic modeling and trajectory tracking control of hard rock Tunnel Boring Machine(TBM). The acceleration equation, moment of momentum equation, kinematics equation and orientation equation of TBM are built up. The dynamic mathematical model of TBM attitude is presented by composing of these four equations. The model provides a foundation for the trajectory tracking control of TBM behavior. Fuzzy PID controller is used to design velocity controller, vertical controller and lateral controller. The effectiveness of the proposed methods is shown by illustrative example.
In the combustion system and ash fouling system of boiler,the furnace exit gas temperature(FEGT)is the key parameter for ensuring high *** it is hard to achieve satisfactory performance through conventional control st...
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In the combustion system and ash fouling system of boiler,the furnace exit gas temperature(FEGT)is the key parameter for ensuring high *** it is hard to achieve satisfactory performance through conventional control strategy,the control problem of FEGT has become critical and significant in coal-fired boiler *** this paper,a new predictive control scheme based on particle swarm optimization(PSO)and CM-LSSVM-PLS model is *** the proposed control scheme,a new CM-LSSVM-PLS method is proposed and used as the predictive model to predict the future *** the process of CM-LSSVM-PLS method,c-means cluster(CM)algorithm is used to partition the training data into several different subsets by considering the characteristics of operational *** sub-models are subsequently developed in the individual subsets based on least squares support vector machine(LSSVM).Then,partial least squares algorithm(PLS)is employed as the combination ***,PSO is used as the receding optimization *** proposed control is verified through operation data of a 300MW generating *** simulation results show that the effectiveness of our proposed control scheme.
We propose a novel regression, which is called Twin Support Vector Regression(TSVR) to improve the precision of indoor positioning. Similar as Support Vector Regression(SVR), there are 6 parameters to be identified. H...
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ISBN:
(纸本)9781479937097
We propose a novel regression, which is called Twin Support Vector Regression(TSVR) to improve the precision of indoor positioning. Similar as Support Vector Regression(SVR), there are 6 parameters to be identified. However, compared with SVR, less computation time and approximate performance can be achieved with TSVR. Genetic Algorithm(GA) is used to avoid local optimum in indoor positioning to get proper parameters in TSVR. Experimental example is shown to illustrate the effectiveness of the proposed methods.
The increasing demands on the indoor location service inspire the wide attentions to investigate the indoor position algorithms. Access point(AP) selection is critical important for increasing the estimation accuracy ...
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The increasing demands on the indoor location service inspire the wide attentions to investigate the indoor position algorithms. Access point(AP) selection is critical important for increasing the estimation accuracy of the indoor location. In this paper, the key features in influencing the accuracy of indoor location systems are investigated. Base on the analysis results, we present an AP selection strategy for indoor location by proposing a novel AP selection index for test point. By using the experiment data, the K-Nearest Neighbor(KNN) and weighted-KNN(WKNN) indoor location methods are carried out to illustrate the performance proposed AP selection strategy. The performance of our AP selection strategy is validated by comparing with the exhaustive AP selection strategy, the fisher AP selection strategy and the largest RSSI strength AP selection strategy. The experiment results show that the proposed AP selection strategy can improve the location accuracy of indoor location with Wi-Fi.
This paper mainly studies the hourly water demand forecasting performances of water supply system in shanghai with LS-SVM. The teaching-learning-based optimization(TLBO) is adopted to adjust the hyper-parameters of le...
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This paper mainly studies the hourly water demand forecasting performances of water supply system in shanghai with LS-SVM. The teaching-learning-based optimization(TLBO) is adopted to adjust the hyper-parameters of least squares support vector machine(LS-SVM).To improve the forecast accuracy, An ameliorated TLBO algorithm called ATLBO is introduced. The experimental results show that the model of water demand forecasting with ATLBO has better regression precision than grid search, particle swarm optimization(PSO) and TLBO.
Consensus is a fundamental and important problem for cooperative *** paper mainly studies the consensus of networked multi-agent systems with nonlinear couplings via pinning *** adaptive desired weighting consensus pr...
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ISBN:
(纸本)9781479947249
Consensus is a fundamental and important problem for cooperative *** paper mainly studies the consensus of networked multi-agent systems with nonlinear couplings via pinning *** adaptive desired weighting consensus protocol is proposed to control a small fraction of pinned agents for directed ***,an adaptive controller gain average consensus protocol is presented via the selected pinning agents for weighted directed *** conditions for achieving the desired consensus asymptotically are ***,theoretical results are validated via simulations.
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