pyFTS/hwang.py
2017-01-25 12:17:07 -02:00

44 lines
1.5 KiB
Python

import numpy as np
from pyFTS.common import FuzzySet,FLR,Transformations
from pyFTS import fts
class HighOrderFTS(fts.FTS):
def __init__(self, name):
super(HighOrderFTS, self).__init__(1, name)
self.isHighOrder = True
self.minOrder = 2
self.name = "Hwang High Order FTS"
self.shortname = "Hwang" + name
self.detail = "Hwang"
def forecast(self, data):
cn = np.array([0.0 for k in range(len(self.sets))])
ow = np.array([[0.0 for k in range(len(self.sets))] for z in range(self.order - 1)])
rn = np.array([[0.0 for k in range(len(self.sets))] for z in range(self.order - 1)])
ft = np.array([0.0 for k in range(len(self.sets))])
ret = []
for t in np.arange(self.order-1, len(data)):
for s in range(len(self.sets)):
cn[s] = self.sets[s].membership(data[t])
for w in range(self.order - 1):
ow[w, s] = self.sets[s].membership(data[t - w])
rn[w, s] = ow[w, s] * cn[s]
ft[s] = max(ft[s], rn[w, s])
mft = max(ft)
out = 0.0
count = 0.0
for s in range(len(self.sets)):
if ft[s] == mft:
out = out + self.sets[s].centroid
count += 1.0
ret.append(out / count)
return ret
def train(self, data, sets, order=1, parameters=None):
self.sets = sets
self.order = order