Mercurial > hg > camir-aes2014
comparison toolboxes/FullBNT-1.0.7/bnt/examples/dynamic/mk_mildew_dbn.m @ 0:e9a9cd732c1e tip
first hg version after svn
author | wolffd |
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date | Tue, 10 Feb 2015 15:05:51 +0000 |
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-1:000000000000 | 0:e9a9cd732c1e |
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1 function bnet = mk_mildew_dbn() | |
2 | |
3 % DBN for foreacasting the gross yield of wheat based on climatic data, | |
4 % observations of leaf area index (LAI) and extension of mildew, | |
5 % and knowledge of amount of fungicides used and time of usage. | |
6 % From Kjaerulff '95. | |
7 | |
8 Fungi=1; Mildew=2; LAI=3; Precip=4; Temp=5; Micro=6; Solar=7; Photo=8; Dry=9; | |
9 n = 9; | |
10 intra = zeros(n,n); | |
11 intra(Mildew, LAI)=1; | |
12 intra(LAI,[Micro Photo])=1; | |
13 intra(Precip,Micro)=1; | |
14 intra(Temp,[Micro Photo])=1; | |
15 intra(Solar,Photo)=1; | |
16 intra(Photo,Dry)=1; | |
17 | |
18 inter = zeros(n,n); | |
19 inter(Fungi,Mildew)=1; | |
20 inter(Mildew,Mildew)=1; | |
21 inter(LAI,LAI)=1; | |
22 inter(Micro,Mildew)=1; | |
23 inter(Dry,Dry)=1; | |
24 | |
25 ns = 2*ones(1,n); | |
26 bnet = mk_dbn(intra, inter, ns, 'observed', [Photo]); | |
27 | |
28 for e=1:max(bnet.equiv_class(:)) | |
29 i = bnet.rep_of_eclass(e); | |
30 bnet.CPD{e} = tabular_CPD(bnet,i); | |
31 end |