Zhong Yi Wan

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We formulate a reduced-order strategy for efficiently forecasting complex high-dimensional dynamical systems entirely based on data streams. The first step of our method involves reconstructing the dynamics in a reduced-order subspace of choice using Gaussian Process Regression (GPR). GPR simultaneously allows for reconstruction of the vector field and more(More)
In this paper, a multi-objective mixed-integer piecewise nonlinear programming model (MOMIPNLP) is built to formulate the management problem of urban mining system, where the decision variables are associated with buy-back pricing, choices of sites, transportation planning and adjustment of production capacity. Different from the existing approaches, the(More)
Resulting in the security of mobile payment are the two main problems of the mobile terminal itself and the process of wireless communication. As the mobile terminal's own unique portability, small size and low cost nature,it cause that the mobile terminal weak ability of computing encryption. The emergence of mobile phone virus is also a potential security(More)
In this thesis work, we formulate a reduced-order data-driven strategy for the efficient probabilistic forecast of complex high-dimensional dynamical systems for which datastreams are available. The first step of this method consists of the reconstruction of the vector field in a reduced-order subspace of interest using Gaussian Process Regression (GPR).(More)
When we solve an ordinary nonlinear programming problem by the most and popular sequential quadratic programming (SQP) method, one of the difficulties that we must overcome is to ensure the consistence of its QP subproblems. In this paper, we develop a new SQP method which can assure that the QP subproblem at every iteration is consistent. One of the main(More)
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