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
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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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