Double-star spectrum fitting method based on strategy-improved Saussurea involucrata intelligent algorithm

An intelligent algorithm and spectral fitting technology, applied in computing, computing models, instruments, etc., can solve the problems of not easily jumping out of the trap of local optimality, not easy to find, and lack of diversity, avoiding premature convergence problems and helping to jump out of local areas. Early maturation and obvious effect of population diversity

Pending Publication Date: 2020-05-08
KUNMING UNIV OF SCI & TECH
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  • Application Information

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Problems solved by technology

However, the standard salp algorithm can achieve fast convergence based on the swarm optimization of the salp chain, but it is insufficient in the global search diversity. Due to the limitation of population diversity and the lack of food source update mechanis...

Method used

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  • Double-star spectrum fitting method based on strategy-improved Saussurea involucrata intelligent algorithm
  • Double-star spectrum fitting method based on strategy-improved Saussurea involucrata intelligent algorithm
  • Double-star spectrum fitting method based on strategy-improved Saussurea involucrata intelligent algorithm

Examples

Experimental program
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Effect test

Embodiment 1

[0080] The simulation experiment is carried out on the strategy-improved Salvia squirt intelligent algorithm. The experiment platform is Python, the operating system is Windows, the memory capacity is 8GB, and the CPU model is i5-85000. Select select test function (Sphere function) F1 x(-100,100), the search space dimension D is set to 30, the number of individuals in the salvia population is initialized to 50, and the convergence curve obtained by the test is figure 2 As shown; after increasing the adaptive inertia factor of the food source, the convergence curve is image 3 As shown in the figure, it can be seen that the convergence is smoother after the adaptive inertia factor is added, which is more conducive to the algorithm to escape from local precocity; in addition, the convergence curve is after increasing the number of individuals of the initial salvia population to 500 Figure 4 As shown, the convergence speed of the algorithm is significantly improved, and the time c...

Embodiment 2

[0082] Use strategy to improve the salvia intelligent algorithm to perform fitting experiments on the observation spectrum (the observation spectrum data and theoretical spectrum data used in the experiment are all existing data), the experimental platform is Python, the operating system is Windows, the memory capacity is 8GB, and the CPU model It is i5-85000. Fit the observation spectrum (No.: spec-0266-51630-0010.fits) based on the binary star model evolution library based on the chap function, and get the fitting curve as Figure 5 As shown, the fitting speed is faster and the fitting accuracy is higher, which meets the fitting requirements.

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Abstract

The invention discloses a double-star spectrum fitting method based on a strategy-improved Saussurea involucrata intelligent algorithm. The double-star spectrum fitting method comprises the followingsteps: firstly, setting a theoretical spectrum star family sample library of an observation spectrum band to be fitted under a double-star model; and then optimizing the observation spectrum to be fitted in the theoretical spectrum star family sample library by using a strategy improved Sashimi intelligent algorithm to obtain an optimal fitted spectrum. Chaotic mapping and a reverse learning method are applied to population initialization, so that the initial positions of population individuals are distributed more uniformly, the population diversity is more obvious, and the early-stage premature convergence problem of a traditional algorithm can be avoided; a random walk strategy is adopted to realize position updating of a food source, so that local convergence traps can be jumped out, and the global optimization performance of the algorithm is further enhanced; the strategy-improved scabbard intelligent algorithm is faster in convergence speed, smoother in convergence and more beneficial to jumping out of local premature, and when the strategy-improved scabbard intelligent algorithm is applied to double-star spectrum fitting, the fitting speed is higher, and the fitting precision is higher.

Description

Technical field [0001] The invention belongs to the technical field of big data processing, and specifically relates to a method for fitting massive binary star spectrum data based on a strategy-improved salvia intelligent algorithm. Background technique [0002] The spectra of galaxies or star clusters mainly come from stars. The spectrum of a galaxy contains a lot of physical information about the galaxy. How to quickly and accurately analyze the observed spectrum of a galaxy to obtain an estimate of the related physical parameters of the galaxy is the key to studying the evolution of galaxies. With the development of sky survey technology, more and more high-quality galaxy observation spectrum data are collected. The stellar cluster synthesis method is the process of comparing the integral characteristics of the stellar cluster, such as the spectrum, with the observed or theoretical stellar cluster model, to determine the composition and physical parameters of the stars that ...

Claims

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Application Information

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IPC IPC(8): G06N3/00
CPCG06N3/006
Inventor 迟焕斌王锋李忠木刘通和婧王骞李鹤健阮俊枭吴世浙陈雪鸥陈镭丹
Owner KUNMING UNIV OF SCI & TECH
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