Biochemical path planning method based on improved agent-assisted shuffled frog leaping algorithm
A technology of shuffling frog jumping and path planning, applied in the direction of genetic model, etc., can solve the problems of time-varying nonlinearity, complex biochemical reaction process, difficult identification and parameter estimation, etc., to improve the efficiency of the algorithm
Inactive Publication Date: 2022-07-29
TIANJIN UNIV
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The biochemical reaction process is complex, and the mathematical model established by the biochemical metabolic pathway is time-varying, nonlinear and uncertain, and identification and parameter estimation are difficult, so the design of the biochemical metabolic pathway is a complex optimization problem
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[0053] It should be noted that the embodiments of the present invention and the features of the embodiments may be combined with each other under the condition of no conflict.
[0054] In the description of the present invention, it should be understood that the terms "center", "portrait", "horizontal", "top", "bottom", "front", "rear", "left", "right", " The orientation or positional relationship indicated by vertical, horizontal, top, bottom, inner, outer, etc. is based on the orientation or positional relationship shown in the drawings, and is only for the convenience of describing the present invention and The description is simplified rather than indicating or implying that the device or element referred to must have a particular orientation, be constructed and operate in a particular orientation, and therefore should not be construed as limiting the invention. In addition, the terms "first", "second", etc. are used for descriptive purposes only, and should not be constru...
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The invention provides a biochemical path planning method based on an improved agent-assisted shuffled frog leaping algorithm. The biochemical path planning method comprises the following steps: initializing a population; the agent model is initialized; grouping populations; updating the population; updating the model; and judging whether the shuffled frog-leaping algorithm meets a termination condition or not, if the shuffled frog-leaping algorithm does not meet the termination condition, continuing to group the populations, otherwise, outputting a current population fitness optimal solution as a final solution, namely, outputting a biochemical metabolism path with maximum Gibbs free energy. According to the method, the Gibbs free energy of the biochemical metabolic pathway is predicted by using the proxy model, the Gibbs free energy is predicted for the metabolic pathway on which biochemical experiments are difficult to carry out, and comprehensive coverage of the Gibbs free energy of the natural metabolic pathway is realized.
Description
technical field [0001] The invention belongs to the field of biochemical reaction path design, in particular to a biochemical path planning method based on an improved agent-assisted shuffling frog leaping algorithm. Background technique [0002] Shuffled Frog Leaping Algorithm (SFLA) is a new heuristic intelligent evolutionary algorithm first proposed by Eusuff and Lansey in 2006, which is inspired by the foraging behavior of frogs. SFLA conducts a local search in subgroups of frogs through a meme algorithm, frogs use a hybrid strategy to mix jumping algorithms, and exchange information in the local search. SFLA combines the advantages of meme algorithm and particle swarm algorithm to exchange information in local search and global search respectively, combining the two information exchange methods well. Overall, SFLA is highly searchable and easy to implement, and can be used to solve many nonlinear, undetectable, and multi-state problems. [0003] As a powerful optimiza...
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IPC IPC(8): G06N3/12
CPCG06N3/126
Inventor 张涛曹亚慧赵鑫贾雪刘晶晶
Owner TIANJIN UNIV