标题:
[问题求助]
[已解决]python多参数拟合
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作者:
Liule
时间:
2020-7-16 12:30
标题:
[已解决]python多参数拟合
函数z=(a*(y+273.15)+b+cx+d*(y+273.15)*LN(y+273.15)+e*(y+273.15)^2)/(8.3144*(y+273.15)*LN(10)), 现在有一些(x, y, z)的数据点(见附件),怎样拟合出最佳的参数 (a, b, c, d, e)?
作者:
Blakelee
时间:
2020-7-16 15:37
回复
1#
Liule
#!/usr/bin/env python3
from scipy.optimize import differential_evolution
from math import log
from math import e
import numpy as np
data = """1.0 300 -35.287
1.5 315 -34.047
2.0 330 -32.872
2.5 345 -31.757
====copy your data=====
5.0 880 -12.729
5.0 890 -12.547
5.0 900 -12.369"""
data = data.split("\n")
data = list(map(lambda x: filter(None, x.split(" ")), data))
data = map(lambda x: list(map(float, x)), data)
data = list(data)
def f(x, y, a, b, c, d, f):
return (a * (y + 273.15) + b + c * x + d * (y + 273.15) * np.log(y+273.15) \
+ f * ((y+273.15) ** 2)) / (8.3144 * (y + 273.15) * log(10,e))
def fitness(parameters):
error = 0
for x, y, z in data:
res = f(x, y, *parameters)
error += abs(res - z) ** 2
return error
from scipy.optimize import differential_evolution
bounds = [(-500000, 500000)] * 5
x = differential_evolution(fitness, bounds, disp=True).x
print(list(x))
作者:
Liule
时间:
2020-7-16 15:44
谢谢,但你的结果和真实值[1584.427,-587474,1810,-203.3164,0.09271]有点差距,能否再改进一下?
作者:
Blakelee
时间:
2020-7-16 17:42
根据计算结果缩小(a, b, c, d, f)各自的bound,直至f(x)的数值足够小(精度足够高)。
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