As a nonlinear and time-varying complex dynamic system, wastewater treatment process(WWTP) is difficult to be controlled. In this paper, to control the dissolved oxygen(DO) concentration in a WWTP, a growing and pruni...
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ISBN:
(纸本)9781509009107
As a nonlinear and time-varying complex dynamic system, wastewater treatment process(WWTP) is difficult to be controlled. In this paper, to control the dissolved oxygen(DO) concentration in a WWTP, a growing and pruning recurrent fuzzy neural network(GPRFNN)-based controlsystem is proposed which contains RFNN controllers and RFNN identifier. The identifier is used to model the WWTP with an adaptive algorithm to afford model information for the controllers, while the controllers are designed to adjust the control variables to make the WWTP run smoothly. Furthermore, the structure of the RFNN is self-organized to keep the output steady in structural adjustment phase, which is also theoretically proved. Finally, the control performance of the proposed system is shown by simulation results.
PM2.5 is difficult to accurately forecast due to the influence of multiple meteorological and pollutant variables in the complex nonlinear dynamic atmosphere *** this paper,an Elman neural network prediction method ba...
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ISBN:
(纸本)9781509009107
PM2.5 is difficult to accurately forecast due to the influence of multiple meteorological and pollutant variables in the complex nonlinear dynamic atmosphere *** this paper,an Elman neural network prediction method based on chaos theory is put forward for the ***,the chaotic characteristics of the concentration of the PM2.5 are analyzed and verified from the correlation dimension,the maximum Lyapunov exponent and the Kolmogorov ***,phase space reconstruction technique of chaotic theory is adopted to reconstruct the phase space of PM2.5 time *** reconstructed phase space and the future concentration of PM2.5 are taken as the input and output of the Elman neural network with chaos theory(Elman-chaos) *** numerical and experimental analyses show that this method is proportionally superior to that without considering the chaos characteristics and other *** Elman-chaos prediction model has better prediction performance and application value.
In this paper, we present a deep learning based approach to performing the whole-day prediction of the traffic speed for the elevated highway. In order to learn the temporal features of traffic speed data in a hierarc...
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The high dimensionality of the current battlefield information increases the complexity of the information utilization, which leads to the deterioration of the battlefield information services. The effective reduction...
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Based on the Spark big data analysis platform, using Yarn management resource scheduling problem, using Hbase as the storage mode of distributed data. Through the mass of car data, dig out the key factors that affect ...
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Based on the Spark big data analysis platform, using Yarn management resource scheduling problem, using Hbase as the storage mode of distributed data. Through the mass of car data, dig out the key factors that affect the safety of car performance, and show in the form of visualization. An effective scheme is put forward for the maintenance and fault detection of the user's vehicle. The experimental results show that the analysis method based on Spark platform can quickly, effectively and accurately analyze the keyinformation and play a guiding and analytical role for users.
This paper we investigates the problem of stability and bifurcation of fractional-order financial system time-delay via the Lyapunov stability judgment method and application of impulse control method. Finally, a nume...
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This paper we investigates the problem of stability and bifurcation of fractional-order financial system time-delay via the Lyapunov stability judgment method and application of impulse control method. Finally, a numerical simulation example is provided to verify the effectiveness and the benefit of the proposed stability and bifurcation criterion.
The casting quality management costs too much manpower, material and financial resources and is still lack of scientific status. In view of these conditions, this paper builds the casting quality management cloud plat...
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The casting quality management costs too much manpower, material and financial resources and is still lack of scientific status. In view of these conditions, this paper builds the casting quality management cloud platform based on Spark. Build and deploy Spark Standalone on the local computer. Parallel computing and cloud storage mechanism are implemented by Spark. Task management scheduling is implemented by Standalone. The foundry enterprise uses this platform to carry on the big data analysis to the influence factors of casting quality in the casting production. According to the results of the analysis, the scientific guidance and efficient scheduling of the manufacturing process are carried out. The quality management of castings is standardized and scientific. The scrap rate of castings is reduced. Through the large data analysis of various factors affecting the quality of casting, a set of scientific and efficient management scheme is provided.
The technology of Internet of automobile is designed to solve problems in field of transportation about safety, efficiency and environment. The system is based on data supplied by hardware in vehicles, design a mobile...
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The technology of Internet of automobile is designed to solve problems in field of transportation about safety, efficiency and environment. The system is based on data supplied by hardware in vehicles, design a mobile client APP and a management system for sellers through cloud computing, mass data distribution technology, which achieve the automobile driving data collection and analysis, fault reminders, track search, vehicle positioning, tips information release and other functions, and also achieve the intelligent analysis of automobile driving data. To some extent, the technology solves the problems such as automobile mileage not clear, hard to locate the automobile location, complicated ownership transfer, unable to self-help troubleshooting, hard to find the nearest repair point and so on.
For image representation methods of image classification, it is very important to represent the image well. In this paper, we propose a novel representation method for image classification, which can combine the advan...
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ISBN:
(纸本)9781509067602
For image representation methods of image classification, it is very important to represent the image well. In this paper, we propose a novel representation method for image classification, which can combine the advantage that the sparse representation can effectively use image information and the advantage that the PCA method can effectively eliminate the interference of irrelevant image information, and overcome the shortcomings of them. The proposed method firstly used the PCA method to obtain the first numbers of eigenvectors with the largest contribution rate for the samples of each subject as the training samples, and then these training samples are used to represent the test sample.
In this paper,a sliding-mode controller of aggregated thermostatically controlled loads is designed to track the automatic generation control signal in ancillary service *** improve the tracking performance,we optimiz...
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ISBN:
(纸本)9781509009107
In this paper,a sliding-mode controller of aggregated thermostatically controlled loads is designed to track the automatic generation control signal in ancillary service *** improve the tracking performance,we optimize the boundary layer of the sliding-mode controller by the parabola interpolation optimization *** results demonstrate that the parabola interpolation optimization algorithm is an efficient method to find the optimal boundary layer,and the proposed controller with optimal boundary layer can reduce the tracking errors for frequency regulation service in power grid.
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