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In this paper, we present an approach for evolutionary learning of motif in biopolymer sequences. The focuses in this paper is evolutionary inference of Gaussian model, Differential Evolution for optimization and Markov chain Monte Carlo(MCMC) for sampling are applied in the probability learning of Gaussian model. The framework involves calculations of corresponding weight, mean and covariance. To...
Mixture model comprises a finite or infinite number of different distributional types of components and offers a much wider range of modeling possibilities than its components. In his paper, we present an approach for Bayesian inference of mixture model with Differential Evolution and Markov chain Monte Carlo(MCMC). Bayesian inference on Gaussian mixture model via Gibbs sampling and optimization with...
Unit load system of thermal power plant is a multivariable system with strong coupling. Its performance has great impact on the safety and economy of the unit. In this paper, multivariable feed-forward and feedback GPC (generalized predictive control) is introduced into the control of unit load system. The coupling between the power loop and pressure loop is treated as knowable exterior disturbance...
GPC (generalized predictive control) is widely used in the control of plant with inertia and delay. This paper proposes feed-forward and feedback GPC in the control of MIMO system. The coupling is treated as knowable exterior disturbance and considered during the designing process of GPC controllers. With structure analysis, the new controller is equivalent to feed-forward and feedback control system...
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