TSKFuzzyInferenceSystem

fuzzy_logic_rs::fuzzy_inference_systems

Struct TSKFuzzyInferenceSystem 

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pub struct TSKFuzzyInferenceSystem { /* private fields */ }

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impl TSKFuzzyInferenceSystem

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pub fn new( s_norm: SNorms, t_norm: TNorms, defuzzification: TSKDefuzzifiers, ) -> Self

Examples found in repository?
examples/function_approximation.rs (line 22)
11fn main() {
12    let x1 = 0.0;
13    let x2 = 0.25;
14    let x3 = 0.5;
15    let x4 = 0.75;
16    let x5 = 1.0;
17    let original_function = |x| x * (1.0 - x);
18    let y15 = original_function(x1);
19    let y24 = original_function(x2);
20    let y3 = original_function(x3);
21
22    let mut fis = TSKFIS::new(SNorms::Max, TNorms::Min, TSKDefuzzifiers::Mean);
23
24    let mut x: InputVariable = InputVariable::new("X".to_string(), (0.0, 1.0));
25    x.add_membership(MembershipFunction::new(
26        "x1".to_string(),
27        MFKind::Gaussian(Gaussian::new(x1, 0.09)),
28    ));
29    x.add_membership(MembershipFunction::new(
30        "x2".to_string(),
31        MFKind::Gaussian(Gaussian::new(x2, 0.09)),
32    ));
33    x.add_membership(MembershipFunction::new(
34        "x3".to_string(),
35        MFKind::Gaussian(Gaussian::new(x3, 0.09)),
36    ));
37    x.add_membership(MembershipFunction::new(
38        "x4".to_string(),
39        MFKind::Gaussian(Gaussian::new(x4, 0.09)),
40    ));
41    x.add_membership(MembershipFunction::new(
42        "x5".to_string(),
43        MFKind::Gaussian(Gaussian::new(x5, 0.09)),
44    ));
45    fis.add_input(x);
46
47    let mut y: TSKOutputVariable = TSKOutputVariable::new("Y".to_string());
48    y.add_constant_membership(y15);
49    y.add_constant_membership(y24);
50    y.add_constant_membership(y3);
51
52    fis.add_output(y);
53
54    fis.add_rule(Rule::new_and(vec![0, 0], 1.0));
55    fis.add_rule(Rule::new_and(vec![1, 1], 1.0));
56    fis.add_rule(Rule::new_and(vec![2, 2], 1.0));
57    fis.add_rule(Rule::new_and(vec![3, 1], 1.0));
58    fis.add_rule(Rule::new_and(vec![4, 0], 1.0));
59    
60    let out: Vec<f64> = fis.compute_outputs(vec![0.6]);
61    println!("{:?}", out);
62}
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pub fn add_input(&mut self, input: InputVariable)

Examples found in repository?
examples/function_approximation.rs (line 45)
11fn main() {
12    let x1 = 0.0;
13    let x2 = 0.25;
14    let x3 = 0.5;
15    let x4 = 0.75;
16    let x5 = 1.0;
17    let original_function = |x| x * (1.0 - x);
18    let y15 = original_function(x1);
19    let y24 = original_function(x2);
20    let y3 = original_function(x3);
21
22    let mut fis = TSKFIS::new(SNorms::Max, TNorms::Min, TSKDefuzzifiers::Mean);
23
24    let mut x: InputVariable = InputVariable::new("X".to_string(), (0.0, 1.0));
25    x.add_membership(MembershipFunction::new(
26        "x1".to_string(),
27        MFKind::Gaussian(Gaussian::new(x1, 0.09)),
28    ));
29    x.add_membership(MembershipFunction::new(
30        "x2".to_string(),
31        MFKind::Gaussian(Gaussian::new(x2, 0.09)),
32    ));
33    x.add_membership(MembershipFunction::new(
34        "x3".to_string(),
35        MFKind::Gaussian(Gaussian::new(x3, 0.09)),
36    ));
37    x.add_membership(MembershipFunction::new(
38        "x4".to_string(),
39        MFKind::Gaussian(Gaussian::new(x4, 0.09)),
40    ));
41    x.add_membership(MembershipFunction::new(
42        "x5".to_string(),
43        MFKind::Gaussian(Gaussian::new(x5, 0.09)),
44    ));
45    fis.add_input(x);
46
47    let mut y: TSKOutputVariable = TSKOutputVariable::new("Y".to_string());
48    y.add_constant_membership(y15);
49    y.add_constant_membership(y24);
50    y.add_constant_membership(y3);
51
52    fis.add_output(y);
53
54    fis.add_rule(Rule::new_and(vec![0, 0], 1.0));
55    fis.add_rule(Rule::new_and(vec![1, 1], 1.0));
56    fis.add_rule(Rule::new_and(vec![2, 2], 1.0));
57    fis.add_rule(Rule::new_and(vec![3, 1], 1.0));
58    fis.add_rule(Rule::new_and(vec![4, 0], 1.0));
59    
60    let out: Vec<f64> = fis.compute_outputs(vec![0.6]);
61    println!("{:?}", out);
62}
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pub fn add_output(&mut self, variable: TSKOutputVariable)

Examples found in repository?
examples/function_approximation.rs (line 52)
11fn main() {
12    let x1 = 0.0;
13    let x2 = 0.25;
14    let x3 = 0.5;
15    let x4 = 0.75;
16    let x5 = 1.0;
17    let original_function = |x| x * (1.0 - x);
18    let y15 = original_function(x1);
19    let y24 = original_function(x2);
20    let y3 = original_function(x3);
21
22    let mut fis = TSKFIS::new(SNorms::Max, TNorms::Min, TSKDefuzzifiers::Mean);
23
24    let mut x: InputVariable = InputVariable::new("X".to_string(), (0.0, 1.0));
25    x.add_membership(MembershipFunction::new(
26        "x1".to_string(),
27        MFKind::Gaussian(Gaussian::new(x1, 0.09)),
28    ));
29    x.add_membership(MembershipFunction::new(
30        "x2".to_string(),
31        MFKind::Gaussian(Gaussian::new(x2, 0.09)),
32    ));
33    x.add_membership(MembershipFunction::new(
34        "x3".to_string(),
35        MFKind::Gaussian(Gaussian::new(x3, 0.09)),
36    ));
37    x.add_membership(MembershipFunction::new(
38        "x4".to_string(),
39        MFKind::Gaussian(Gaussian::new(x4, 0.09)),
40    ));
41    x.add_membership(MembershipFunction::new(
42        "x5".to_string(),
43        MFKind::Gaussian(Gaussian::new(x5, 0.09)),
44    ));
45    fis.add_input(x);
46
47    let mut y: TSKOutputVariable = TSKOutputVariable::new("Y".to_string());
48    y.add_constant_membership(y15);
49    y.add_constant_membership(y24);
50    y.add_constant_membership(y3);
51
52    fis.add_output(y);
53
54    fis.add_rule(Rule::new_and(vec![0, 0], 1.0));
55    fis.add_rule(Rule::new_and(vec![1, 1], 1.0));
56    fis.add_rule(Rule::new_and(vec![2, 2], 1.0));
57    fis.add_rule(Rule::new_and(vec![3, 1], 1.0));
58    fis.add_rule(Rule::new_and(vec![4, 0], 1.0));
59    
60    let out: Vec<f64> = fis.compute_outputs(vec![0.6]);
61    println!("{:?}", out);
62}
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pub fn add_rule(&mut self, rule: Rule)

Examples found in repository?
examples/function_approximation.rs (line 54)
11fn main() {
12    let x1 = 0.0;
13    let x2 = 0.25;
14    let x3 = 0.5;
15    let x4 = 0.75;
16    let x5 = 1.0;
17    let original_function = |x| x * (1.0 - x);
18    let y15 = original_function(x1);
19    let y24 = original_function(x2);
20    let y3 = original_function(x3);
21
22    let mut fis = TSKFIS::new(SNorms::Max, TNorms::Min, TSKDefuzzifiers::Mean);
23
24    let mut x: InputVariable = InputVariable::new("X".to_string(), (0.0, 1.0));
25    x.add_membership(MembershipFunction::new(
26        "x1".to_string(),
27        MFKind::Gaussian(Gaussian::new(x1, 0.09)),
28    ));
29    x.add_membership(MembershipFunction::new(
30        "x2".to_string(),
31        MFKind::Gaussian(Gaussian::new(x2, 0.09)),
32    ));
33    x.add_membership(MembershipFunction::new(
34        "x3".to_string(),
35        MFKind::Gaussian(Gaussian::new(x3, 0.09)),
36    ));
37    x.add_membership(MembershipFunction::new(
38        "x4".to_string(),
39        MFKind::Gaussian(Gaussian::new(x4, 0.09)),
40    ));
41    x.add_membership(MembershipFunction::new(
42        "x5".to_string(),
43        MFKind::Gaussian(Gaussian::new(x5, 0.09)),
44    ));
45    fis.add_input(x);
46
47    let mut y: TSKOutputVariable = TSKOutputVariable::new("Y".to_string());
48    y.add_constant_membership(y15);
49    y.add_constant_membership(y24);
50    y.add_constant_membership(y3);
51
52    fis.add_output(y);
53
54    fis.add_rule(Rule::new_and(vec![0, 0], 1.0));
55    fis.add_rule(Rule::new_and(vec![1, 1], 1.0));
56    fis.add_rule(Rule::new_and(vec![2, 2], 1.0));
57    fis.add_rule(Rule::new_and(vec![3, 1], 1.0));
58    fis.add_rule(Rule::new_and(vec![4, 0], 1.0));
59    
60    let out: Vec<f64> = fis.compute_outputs(vec![0.6]);
61    println!("{:?}", out);
62}
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pub fn get_s_norm(&self, fuzzified: &[f64]) -> f64

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pub fn get_t_norm(&self, fuzzified: &[f64]) -> f64

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pub fn get_rules(&self, rule_index: usize) -> &[i32]

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pub fn get_input_rules(&self, rule_index: usize) -> &[i32]

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pub fn get_output_rules(&self, rule_index: usize) -> &[i32]

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pub fn fuzzification(&self, input_vec: Vec<f64>) -> Vec<Vec<f64>>

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pub fn connect_inputs(&self, fuzzified: Vec<Vec<f64>>) -> Vec<f64>

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pub fn weighed_inputs(&self, connected_inputs: Vec<f64>) -> Vec<f64>

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pub fn get_mu(&self, input_vec: &Vec<f64>) -> Vec<Vec<f64>>

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pub fn compute_outputs(&self, input: Vec<f64>) -> Vec<f64>

Examples found in repository?
examples/function_approximation.rs (line 60)
11fn main() {
12    let x1 = 0.0;
13    let x2 = 0.25;
14    let x3 = 0.5;
15    let x4 = 0.75;
16    let x5 = 1.0;
17    let original_function = |x| x * (1.0 - x);
18    let y15 = original_function(x1);
19    let y24 = original_function(x2);
20    let y3 = original_function(x3);
21
22    let mut fis = TSKFIS::new(SNorms::Max, TNorms::Min, TSKDefuzzifiers::Mean);
23
24    let mut x: InputVariable = InputVariable::new("X".to_string(), (0.0, 1.0));
25    x.add_membership(MembershipFunction::new(
26        "x1".to_string(),
27        MFKind::Gaussian(Gaussian::new(x1, 0.09)),
28    ));
29    x.add_membership(MembershipFunction::new(
30        "x2".to_string(),
31        MFKind::Gaussian(Gaussian::new(x2, 0.09)),
32    ));
33    x.add_membership(MembershipFunction::new(
34        "x3".to_string(),
35        MFKind::Gaussian(Gaussian::new(x3, 0.09)),
36    ));
37    x.add_membership(MembershipFunction::new(
38        "x4".to_string(),
39        MFKind::Gaussian(Gaussian::new(x4, 0.09)),
40    ));
41    x.add_membership(MembershipFunction::new(
42        "x5".to_string(),
43        MFKind::Gaussian(Gaussian::new(x5, 0.09)),
44    ));
45    fis.add_input(x);
46
47    let mut y: TSKOutputVariable = TSKOutputVariable::new("Y".to_string());
48    y.add_constant_membership(y15);
49    y.add_constant_membership(y24);
50    y.add_constant_membership(y3);
51
52    fis.add_output(y);
53
54    fis.add_rule(Rule::new_and(vec![0, 0], 1.0));
55    fis.add_rule(Rule::new_and(vec![1, 1], 1.0));
56    fis.add_rule(Rule::new_and(vec![2, 2], 1.0));
57    fis.add_rule(Rule::new_and(vec![3, 1], 1.0));
58    fis.add_rule(Rule::new_and(vec![4, 0], 1.0));
59    
60    let out: Vec<f64> = fis.compute_outputs(vec![0.6]);
61    println!("{:?}", out);
62}

Trait Implementations§

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impl Debug for TSKFuzzyInferenceSystem

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fn fmt(&self, f: &mut Formatter<'_>) -> Result

Formats the value using the given formatter. Read more

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