A novel regression algorithm of multi-output least squares support vector machine is proposed for the modeling of multi-output systems. The fitting error of each dimension output and the fitting error of overall outpu...
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A novel regression algorithm of multi-output least squares support vector machine is proposed for the modeling of multi-output systems. The fitting error of each dimension output and the fitting error of overall output are defined. And combined with the equality constraints of least squares support vector machine, the linear equation of multi-output least squares support vector machine is deduced. A multioutput combustion system model for utility boiler is established based on above algorithm and the prediction of NOx emission, carbon content of fly ash, exhaust flue gas temperature and desuperheating water of reheater is achieved. In addition, the parameters of the multi-output model are optimized by particle swarm optimization. The performance of the multi-output least squares support vector machine model and multiple single-output least squares support vector machine are compared. The effectiveness of the multi-output model is verified and it provides a good foundation for combustion optimization.
In order to solve the current difficulties of modeling for designing Intelligent Service Mobile Robot (ISMR), a new modeling method based on metasynthesis is proposed from the macro and micro levels. And the system an...
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For low NOx emission from coal-fired power plants, the computational intelligence(CI) technologies for NOx emission modeling and optimization are summarized. The modeling technologies of CI for NOx emission include ar...
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For low NOx emission from coal-fired power plants, the computational intelligence(CI) technologies for NOx emission modeling and optimization are summarized. The modeling technologies of CI for NOx emission include artificial neural networks and fuzzy systems. The optimization methods for low NOx emission combustion consist of evolutionary computation and swarm intelligence. Each method's advantage and disadvantage are comprised and the prospect of low NOx emission combustion is forecasted.
A coal ash fusion temperature model is constructed based on support vector machine(SVM). The compositions of coal ash are employed as the inputs and the ash fusion temperature is the output. A series of improvement is...
A coal ash fusion temperature model is constructed based on support vector machine(SVM). The compositions of coal ash are employed as the inputs and the ash fusion temperature is the output. A series of improvement is made on basic ant colony optimization(ACO) and it is used to optimize the parameters of the SVM model. The coal ash fusion temperature is predicted by the ACO-optimized SVM model. Some experiments are performed to compare the predicted and the measured temperature and the results show the ACO-optimized SVM model can achieve better predicting performance. The advantages of SVM model, such as small sampling, fast computing speed and real-time processing and predicting are also displayed.
In this paper, we examine a resonant capacitor current feedback (RCCF) self-oscillating resonant inverter from nonlinear point of view. By adopting a four-stage equivalent model, we derive the soft-switching dead time...
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In order to design H2/H∞ PID controller, this paper proposed a novel niche quantum genetic algorithm that was based on chaotic mutation operator. The simulation results show that, it can obtain better effect when ado...
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This paper is concerned with the problem of Hα filtering for a class of discrete-time linear parameter-varying (LPV) systems with Markovian switching under data missing and quantization. A stochastic variable is used...
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This paper is concerned with the problem of H ∞ filtering for a class of discrete-time linear parameter-varying (LPV) systems with Markovian switching under data missing and quantization. A stochastic variable is us...
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This paper is concerned with the problem of H ∞ filtering for a class of discrete-time linear parameter-varying (LPV) systems with Markovian switching under data missing and quantization. A stochastic variable is used to describe the model of the data missing phenomenon. Then a H ∞ filter is designed to guarantee the filtering error dynamics is stochastically stable with H ∞ performance. The existence of the desired H ∞ filter is ensured by some sufficient conditions expressed in terms of parameterized linear matrix inequalities (PLMIs). The proposed theoretical findings are validated by numerical results.
This paper investigates the problem of quantized filtering for a class of discrete-time linear parameter-varying systems with Markovian switching under data missing. The measured output of the plant is quantized by a ...
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The corona performance and the electromagnetic environment of the transmission system has become a crucial issue that has been taken into consideration in the line design, and among which audible noise (AN) is one of ...
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ISBN:
(纸本)9781424456215
The corona performance and the electromagnetic environment of the transmission system has become a crucial issue that has been taken into consideration in the line design, and among which audible noise (AN) is one of the most important factors. The wind in the high altitude area is mostly strong, and could greatly influence the AN. This paper, based on the high altitude HDVC test line, studied the characteristics of AN generated by the transmission line, and analyzed the influence of wind velocity and wind direction on the AN lateral profile.
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