fuzzy_b.m

The neuro-fuzzy software for identification and data analysis has been implemented in the MATLAB lan

%Script for the fuzzy inference system

global model
global memb_fun
global model_bias
global arch
global format_out
global init
global no_sets

global mod_id
global mod_path
global mhist_id
global mhist_path
global err_id
global err_path
global ehist_id
global ehist_path
global pred_id
global pred_path
global memo_id
global memo_path

current_dir=pwd;
c=computer;

if isunix
	current_dir=[current_dir,'/'];
else
	if  strcmp(c(1:2),'PC')
		current_dir=[current_dir,'\'];
	end

	if  strcmp(c(1:2),'MA')
		current_dir=[current_dir,':'];
	end
end

%__________________________________________________________________


%%%The 'data' (the training set) matrix is stored in the file:
		data_id='data.mat';
		data_path=current_dir;
%%%Save the memoranda in the file:
		memo_id='memo_id';
		memo_path=current_dir;
%__________________________________________________________________

%Train one model of given complexity or find the best complexity?
		%pr='one_mod';
		pr='evaluate';
		%pr='comp_err';
%__________________________________________________________________


%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%for model training only_____________
%%%%complexity 
		comp=5;
%Save the trained model in the file:
		mod_id='model.mat';
		mod_path=current_dir;
%Save the computation diary in the file:
		mhist_id='mhist.txt';
		mhist_path=current_dir;
%__________________________________________________________________


%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%for model evaluating only___________
%%%The trained model is stored in the file:
		tmod_id='model.mat';
		tmod_path=current_dir;
%%%The 'in' (test set) matrix is stored in the file:
		in_id='in.mat';
		in_path=current_dir;
%Save the predicted output in the file:
		pred_id='out_hat.mat';
		pred_path=current_dir;
%__________________________________________________________________


%%%%%%%%%%%%%%%%%for complexity-error exploration only_____________
%%%range of complexity 
		comp_min=10;
		comp_max=20;
%%%validation 
	 	valid='x_valid';
%%%no_sets  x_valid
		no_sets=10;
%Save the error Vs complexity matrix in the file:
		err_id='errors.mat';
		err_path=current_dir;
%Save the computation diary in the file:
		ehist_id='ehist.txt';
		ehist_path=current_dir;
%__________________________________________________________________








%%%model type
	 	model='fuz';

%_______for complexity-error exploration and model training only:__
%%%form of membership functions	
 	 	 memb_fun='gaussian';
		%memb_fun='triangular';


%_______for complexity-error exploration and model training only:__
%%%Bias
	 	%model_bias='bias';
		 model_bias='no_bias';


%_______for complexity-error exploration and model training only:__
%%%architecture
	 	 arch='comb';
 		%arch='weigthed';


%_______for complexity-error exploration and model training only:__
%%%format_out
	  	 format_out='linear';
		%format_out='constant';


%%%cluster: initialization of the centers and bases
		%init='k_mean';
	 	 init='HFC';
%__________________________________________________________________


if strcmp(pr,'one_mod')
	eval(['load ',data_path,data_id]);
	fuz_aux(pr,comp,data);	
elseif strcmp(pr,'evaluate')
	eval(['load ',tmod_path,tmod_id]);
	eval(['load ',in_path,in_id]);	
	fuz_aux(pr,centers,bases,par,bias,in);
elseif strcmp(pr,'comp_err')
	eval(['load ',data_path,data_id]);
	fuz_aux(pr,comp_min,comp_max,data);	
end		

%__________________________________________________________________
clear model valid memb_fun model_bias		
clear arch format_out init no_sets	
clear mod_id mod_path mhist_id mhist_path	
clear err_id err_path ehist_id ehist_path
clear pred_id pred_path in_id in_path
clear tmod_id tmod_path
clear memo_id memo_path							 
clear pr 
clear centers bases par bias in												
clear comp comp_min comp_max
clear data data_id data_path		
clear c current_dir			
%__________________________________________________________________