Error using FuzzyInferenceSystem/addOutput (line 866) Upper range value for variable must be greater than lower range value. Error in rulepruning (line 24) fis = addOutput(fi
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% Create a sample FIS
% fis = mamfis('tipper');
% fis = mamfis("NumInputs",3,"NumOutputs",1)
fis = mamfis('Name',"tipper");
fis = addInput(fis,'NumMFs',3,'MFType',"gaussmf");
fis.Inputs(1).Name = "service";
fis.Inputs(1).Range = [0 10];
% fis = addInput(fis, 'service', [0 10]);
% fis = addInput(fis, 'food', [0 10]);
% fis = addOutput(fis, 'tip', [0 30]);
fis.Inputs(2).Name = "food";
fis.Inputs(2).Range = [0 10];
fis.Outputs(1).Name = "tip";
fis.Outputs(1).Range = [0 30];
% Add output membership functions
% Add output membership functions
out_mf1 = zmf(fis.Outputs(1).Range, [0 15]); % 'low'
fis = addOutput(fis, out_mf1, 'Name', 'low');
out_mf2 = zmf(fis.Outputs(1).Range, [10 20]); % 'medium'
fis = addOutput(fis, out_mf2, 'Name', 'medium');
out_mf3 = zmf(fis.Outputs(1).Range, [15 25]); % 'high'
fis = addOutput(fis, out_mf3, 'Name', 'high');
out_mf4 = zmf(fis.Outputs(1).Range, [20 30]); % 'very_high'
fis = addOutput(fis, out_mf4, 'Name', 'very_high');
% Add rules
rules = [...
"If service is poor and food is rancid, then tip is cheap"; ...
"If service is good and food is delicious, then tip is generous"; ...
"If service is excellent and food is amazing, then tip is very generous"; ...
"If service is poor and food is delicious, then tip is average"; ...
"If service is good and food is rancid, then tip is little"; ...
];
fis = addRule(fis, rules);
% Perform rule pruning
[pruned_fis, pruned_rules, pruned_outputs] = pruneRules(fis, 0.2);
% Get remaining rules
remaining_rules = getRuleValues(pruned_fis);
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采纳的回答
Sam Chak
2024-5-24
The syntax to add output membership functions is incorrect. Use 'addMF()' instead. However, it is highly recommended to use the Fuzzy Logic Designer app with interactive user interface.
% Create a sample FIS
fis = mamfis('Name',"tipper");
fis = addInput(fis,'NumMFs',3,'MFType',"gaussmf");
% Create Fuzzy Input #1
fis.Inputs(1).Name = "service";
fis.Inputs(1).Range = [0 10];
% Create Fuzzy Input #2
fis.Inputs(2).Name = "food";
fis.Inputs(2).Range = [0 10];
% Create Fuzzy Output #1
fis.Outputs(1).Name = "tip";
fis.Outputs(1).Range = [0 30];
% Add output membership functions
fis = addMF(fis, 'tip', 'zmf', [ 0 15], 'Name', 'low');
fis = addMF(fis, 'tip', 'zmf', [10 20], 'Name', 'medium');
fis = addMF(fis, 'tip', 'zmf', [15 25], 'Name', 'high');
fis = addMF(fis, 'tip', 'zmf', [20 30], 'Name', 'very_high');
plotmf(fis, 'output', 1), grid on, title('Tip')
% % Add rules
% rules = [...
% "If service is poor and food is rancid, then tip is cheap"; ...
% "If service is good and food is delicious, then tip is generous"; ...
% "If service is excellent and food is amazing, then tip is very generous"; ...
% "If service is poor and food is delicious, then tip is average"; ...
% "If service is good and food is rancid, then tip is little"; ...
% ];
% fis = addRule(fis, rules);
%
% % Perform rule pruning
% [pruned_fis, pruned_rules, pruned_outputs] = pruneRules(fis, 0.2);
%
% % Get remaining rules
% remaining_rules = getRuleValues(pruned_fis);
8 个评论
Sam Chak
2024-5-30
You're welcome, @Michael Bamidele. Are you designing a decision-making system based on the concept of pure human reasoning (no math involved) using Fuzzy Logic just like the Tipper example?
Sam Chak
2024-5-30
I neglected to mention that both the pruneRules() and getRuleValues() functions are not built-in MATLAB functions. As a result, I am unable to test them. Are these functions available from the MATLAB File Exchange?
help pruneRules
help getRuleValues
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