Extended multi-interval Legendre-Gauss-Radau pseudospectral method for mixed-integer optimal control problem in engineering

Liu, Zhe; Li, Shurong; Zhao, Kai

doi:10.1080/00207721.2020.1849862

Cited by 5 publications

(1 citation statement)

References 36 publications

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“…GMM can be regarded as a continuous hidden Markov model (CHMM) with a state of 1. It can better display the probability distribution of multi-category observation data in the sample space using GMM [14]. e probability density function of a K-order GMM is obtained by the weighted summation of K Gaussian probability density functions:…”

Section: Gaussian Mixture Model (Gmm)mentioning

confidence: 99%

Application of Discriminative Training Algorithm Based on the Improved Gaussian Mixture Model in English Translation Evaluation

Wang

2022

International Transactions on Electrical Energy Systems

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English translation, also a kind of language conversion, refers to the activities of expressing each other in English to express another language or another language to express English. This paper aimed to evaluate and research methods of English translation based on the improved Gaussian mixture model (GMM). The paper proposed a simple evaluation and analysis of English translation using a discriminative training algorithm. In the experimental part, on the one hand, taking students, teachers, and translators as case study objects, through a questionnaire survey, it can be known that the number of students who scored more than 80 points in the English translation test is increasing every year, from 11.30% in the first year to 21.13% in the fourth year, an increase of nearly 10%. On the other hand, it can be seen from the speech translation experiment that the correct translation rate was 46.18% by using intelligent technology to distinguish translation. The experimental results showed that the discriminative training algorithm under the improved GMM algorithm is effective in the research of English translation evaluation.

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Section: Gaussian Mixture Model (Gmm)mentioning

confidence: 99%

Application of Discriminative Training Algorithm Based on the Improved Gaussian Mixture Model in English Translation Evaluation

Wang

2022

International Transactions on Electrical Energy Systems

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Time-Domain Decomposition for Mixed-Integer Optimal Control Problems

2023

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We consider mixed-integer optimal control problems, whose optimality conditions involve global combinatorial optimization aspects for the corresponding Hamiltonian pointwise in time. We propose a time-domain decomposition, which makes this problem class accessible for mixed-integer programming using parallel-in-time direct discretizations. The approach is based on a decomposition of the optimality system and the interpretation of the resulting subproblems as suitably chosen mixed-integer optimal control problems on subintervals in time. An iterative procedure then ensures continuity of the states at the boundaries of the subintervals via co-state information encoded in virtual controls. We prove convergence of this iterative scheme for discrete-continuous linear-quadratic problems and present numerical results both for linear-quadratic as well as nonlinear problems.

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A numerical method for interval multi-objective mixed-integer optimal control problems based on quantum heuristic algorithm

Liu

2021

Ann Oper Res

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Extended multi-interval Legendre-Gauss-Radau pseudospectral method for mixed-integer optimal control problem in engineering

Cited by 5 publications

References 36 publications

Application of Discriminative Training Algorithm Based on the Improved Gaussian Mixture Model in English Translation Evaluation

Application of Discriminative Training Algorithm Based on the Improved Gaussian Mixture Model in English Translation Evaluation

Time-Domain Decomposition for Mixed-Integer Optimal Control Problems

A numerical method for interval multi-objective mixed-integer optimal control problems based on quantum heuristic algorithm

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