MamdaniFuzzyInferenceSystem

fuzzy_logic_rs::fuzzy_inference_systems

Struct MamdaniFuzzyInferenceSystem 

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pub struct MamdaniFuzzyInferenceSystem { /* private fields */ }

Implementations§

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impl MamdaniFuzzyInferenceSystem

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pub fn new( s_norm: SNorms, t_norm: TNorms, implication: Implications, aggregation: Aggregations, defuzzifier: Defuzzifiers, ) -> Self

Examples found in repository?
examples/speed_control.rs (lines 75-81)
14fn main() {
15    let mut v1 = InputVariable::new("speed".to_string(), (0.0, 140.0));
16    v1.add_membership(MF::new(
17        "S".to_string(),
18        MFKind::Triangle(Triangle::new(-58.3, 0.0, 58.3)),
19    ));
20    v1.add_membership(MF::new(
21        "M".to_string(),
22        MFKind::Triangle(Triangle::new(11.67, 70.0, 128.3)),
23    ));
24    v1.add_membership(MF::new(
25        "L".to_string(),
26        MFKind::Triangle(Triangle::new(81.67, 140.0, 198.3)),
27    ));
28
29    let mut v2 = InputVariable::new("Distance".to_string(), (0.0, 50.0));
30    v2.add_membership(MF::new(
31        "S".to_string(),
32        MFKind::Triangle(Triangle::new(-20.83, 0.0, 20.83)),
33    ));
34    v2.add_membership(MF::new(
35        "M".to_string(),
36        MFKind::Triangle(Triangle::new(4.168, 25.0, 45.82)),
37    ));
38    v2.add_membership(MF::new(
39        "L".to_string(),
40        MFKind::Triangle(Triangle::new(29.17, 50.0, 70.82)),
41    ));
42
43    let mut o1 = OutputVariable::new(String::from("Acceleration"), (-1.0, 1.0), 100);
44    o1.add_membership(MembershipRange::new_gaussian(
45        o1.get_universe(),
46        "NB".to_string(),
47        -1.0,
48        0.2123,
49    ));
50    o1.add_membership(MembershipRange::new_gaussian(
51        o1.get_universe(),
52        "NS".to_string(),
53        -0.5,
54        0.2123,
55    ));
56    o1.add_membership(MembershipRange::new_gaussian(
57        o1.get_universe(),
58        "ZR".to_string(),
59        0.0,
60        0.2123,
61    ));
62    o1.add_membership(MembershipRange::new_gaussian(
63        o1.get_universe(),
64        "PS".to_string(),
65        0.5,
66        0.2123,
67    ));
68    o1.add_membership(MembershipRange::new_gaussian(
69        o1.get_universe(),
70        "PB".to_string(),
71        1.0,
72        0.2123,
73    ));
74
75    let mut fis = MamdaniFIS::new(
76        SNorms::Max,
77        TNorms::Min,
78        Implications::Min,
79        Aggregations::Max,
80        Defuzzifiers::Bisection,
81    );
82    fis.add_input(v1);
83    fis.add_input(v2);
84    fis.add_output(o1);
85
86    fis.add_rule(Rule::new_and(vec![0, 0, 2], 1.0));
87    fis.add_rule(Rule::new_and(vec![0, 1, 3], 1.0));
88    fis.add_rule(Rule::new_and(vec![0, 2, 4], 1.0));
89
90    fis.add_rule(Rule::new_and(vec![1, 0, 1], 1.0));
91    fis.add_rule(Rule::new_and(vec![1, 1, 2], 1.0));
92    fis.add_rule(Rule::new_and(vec![1, 2, 3], 1.0));
93
94    fis.add_rule(Rule::new_and(vec![2, 0, 0], 1.0));
95    fis.add_rule(Rule::new_and(vec![2, 1, 1], 1.0));
96    fis.add_rule(Rule::new_and(vec![2, 2, 2], 1.0));
97
98    let output = fis.compute_outputs(vec![40.0, 43.0]);
99    println!("output is: {:#?}", output);
100}
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pub fn new_all( s_norm: SNorms, t_norm: TNorms, implication: Implications, aggregation: Aggregations, defuzzifier: Defuzzifiers, rules: Vec<Rule>, inputs: Vec<InputVariable>, outputs: Vec<OutputVariable>, ) -> Self

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pub fn add_input(&mut self, input: InputVariable)

Examples found in repository?
examples/speed_control.rs (line 82)
14fn main() {
15    let mut v1 = InputVariable::new("speed".to_string(), (0.0, 140.0));
16    v1.add_membership(MF::new(
17        "S".to_string(),
18        MFKind::Triangle(Triangle::new(-58.3, 0.0, 58.3)),
19    ));
20    v1.add_membership(MF::new(
21        "M".to_string(),
22        MFKind::Triangle(Triangle::new(11.67, 70.0, 128.3)),
23    ));
24    v1.add_membership(MF::new(
25        "L".to_string(),
26        MFKind::Triangle(Triangle::new(81.67, 140.0, 198.3)),
27    ));
28
29    let mut v2 = InputVariable::new("Distance".to_string(), (0.0, 50.0));
30    v2.add_membership(MF::new(
31        "S".to_string(),
32        MFKind::Triangle(Triangle::new(-20.83, 0.0, 20.83)),
33    ));
34    v2.add_membership(MF::new(
35        "M".to_string(),
36        MFKind::Triangle(Triangle::new(4.168, 25.0, 45.82)),
37    ));
38    v2.add_membership(MF::new(
39        "L".to_string(),
40        MFKind::Triangle(Triangle::new(29.17, 50.0, 70.82)),
41    ));
42
43    let mut o1 = OutputVariable::new(String::from("Acceleration"), (-1.0, 1.0), 100);
44    o1.add_membership(MembershipRange::new_gaussian(
45        o1.get_universe(),
46        "NB".to_string(),
47        -1.0,
48        0.2123,
49    ));
50    o1.add_membership(MembershipRange::new_gaussian(
51        o1.get_universe(),
52        "NS".to_string(),
53        -0.5,
54        0.2123,
55    ));
56    o1.add_membership(MembershipRange::new_gaussian(
57        o1.get_universe(),
58        "ZR".to_string(),
59        0.0,
60        0.2123,
61    ));
62    o1.add_membership(MembershipRange::new_gaussian(
63        o1.get_universe(),
64        "PS".to_string(),
65        0.5,
66        0.2123,
67    ));
68    o1.add_membership(MembershipRange::new_gaussian(
69        o1.get_universe(),
70        "PB".to_string(),
71        1.0,
72        0.2123,
73    ));
74
75    let mut fis = MamdaniFIS::new(
76        SNorms::Max,
77        TNorms::Min,
78        Implications::Min,
79        Aggregations::Max,
80        Defuzzifiers::Bisection,
81    );
82    fis.add_input(v1);
83    fis.add_input(v2);
84    fis.add_output(o1);
85
86    fis.add_rule(Rule::new_and(vec![0, 0, 2], 1.0));
87    fis.add_rule(Rule::new_and(vec![0, 1, 3], 1.0));
88    fis.add_rule(Rule::new_and(vec![0, 2, 4], 1.0));
89
90    fis.add_rule(Rule::new_and(vec![1, 0, 1], 1.0));
91    fis.add_rule(Rule::new_and(vec![1, 1, 2], 1.0));
92    fis.add_rule(Rule::new_and(vec![1, 2, 3], 1.0));
93
94    fis.add_rule(Rule::new_and(vec![2, 0, 0], 1.0));
95    fis.add_rule(Rule::new_and(vec![2, 1, 1], 1.0));
96    fis.add_rule(Rule::new_and(vec![2, 2, 2], 1.0));
97
98    let output = fis.compute_outputs(vec![40.0, 43.0]);
99    println!("output is: {:#?}", output);
100}
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pub fn add_output(&mut self, output: OutputVariable)

Examples found in repository?
examples/speed_control.rs (line 84)
14fn main() {
15    let mut v1 = InputVariable::new("speed".to_string(), (0.0, 140.0));
16    v1.add_membership(MF::new(
17        "S".to_string(),
18        MFKind::Triangle(Triangle::new(-58.3, 0.0, 58.3)),
19    ));
20    v1.add_membership(MF::new(
21        "M".to_string(),
22        MFKind::Triangle(Triangle::new(11.67, 70.0, 128.3)),
23    ));
24    v1.add_membership(MF::new(
25        "L".to_string(),
26        MFKind::Triangle(Triangle::new(81.67, 140.0, 198.3)),
27    ));
28
29    let mut v2 = InputVariable::new("Distance".to_string(), (0.0, 50.0));
30    v2.add_membership(MF::new(
31        "S".to_string(),
32        MFKind::Triangle(Triangle::new(-20.83, 0.0, 20.83)),
33    ));
34    v2.add_membership(MF::new(
35        "M".to_string(),
36        MFKind::Triangle(Triangle::new(4.168, 25.0, 45.82)),
37    ));
38    v2.add_membership(MF::new(
39        "L".to_string(),
40        MFKind::Triangle(Triangle::new(29.17, 50.0, 70.82)),
41    ));
42
43    let mut o1 = OutputVariable::new(String::from("Acceleration"), (-1.0, 1.0), 100);
44    o1.add_membership(MembershipRange::new_gaussian(
45        o1.get_universe(),
46        "NB".to_string(),
47        -1.0,
48        0.2123,
49    ));
50    o1.add_membership(MembershipRange::new_gaussian(
51        o1.get_universe(),
52        "NS".to_string(),
53        -0.5,
54        0.2123,
55    ));
56    o1.add_membership(MembershipRange::new_gaussian(
57        o1.get_universe(),
58        "ZR".to_string(),
59        0.0,
60        0.2123,
61    ));
62    o1.add_membership(MembershipRange::new_gaussian(
63        o1.get_universe(),
64        "PS".to_string(),
65        0.5,
66        0.2123,
67    ));
68    o1.add_membership(MembershipRange::new_gaussian(
69        o1.get_universe(),
70        "PB".to_string(),
71        1.0,
72        0.2123,
73    ));
74
75    let mut fis = MamdaniFIS::new(
76        SNorms::Max,
77        TNorms::Min,
78        Implications::Min,
79        Aggregations::Max,
80        Defuzzifiers::Bisection,
81    );
82    fis.add_input(v1);
83    fis.add_input(v2);
84    fis.add_output(o1);
85
86    fis.add_rule(Rule::new_and(vec![0, 0, 2], 1.0));
87    fis.add_rule(Rule::new_and(vec![0, 1, 3], 1.0));
88    fis.add_rule(Rule::new_and(vec![0, 2, 4], 1.0));
89
90    fis.add_rule(Rule::new_and(vec![1, 0, 1], 1.0));
91    fis.add_rule(Rule::new_and(vec![1, 1, 2], 1.0));
92    fis.add_rule(Rule::new_and(vec![1, 2, 3], 1.0));
93
94    fis.add_rule(Rule::new_and(vec![2, 0, 0], 1.0));
95    fis.add_rule(Rule::new_and(vec![2, 1, 1], 1.0));
96    fis.add_rule(Rule::new_and(vec![2, 2, 2], 1.0));
97
98    let output = fis.compute_outputs(vec![40.0, 43.0]);
99    println!("output is: {:#?}", output);
100}
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pub fn add_rule(&mut self, rule: Rule)

Examples found in repository?
examples/speed_control.rs (line 86)
14fn main() {
15    let mut v1 = InputVariable::new("speed".to_string(), (0.0, 140.0));
16    v1.add_membership(MF::new(
17        "S".to_string(),
18        MFKind::Triangle(Triangle::new(-58.3, 0.0, 58.3)),
19    ));
20    v1.add_membership(MF::new(
21        "M".to_string(),
22        MFKind::Triangle(Triangle::new(11.67, 70.0, 128.3)),
23    ));
24    v1.add_membership(MF::new(
25        "L".to_string(),
26        MFKind::Triangle(Triangle::new(81.67, 140.0, 198.3)),
27    ));
28
29    let mut v2 = InputVariable::new("Distance".to_string(), (0.0, 50.0));
30    v2.add_membership(MF::new(
31        "S".to_string(),
32        MFKind::Triangle(Triangle::new(-20.83, 0.0, 20.83)),
33    ));
34    v2.add_membership(MF::new(
35        "M".to_string(),
36        MFKind::Triangle(Triangle::new(4.168, 25.0, 45.82)),
37    ));
38    v2.add_membership(MF::new(
39        "L".to_string(),
40        MFKind::Triangle(Triangle::new(29.17, 50.0, 70.82)),
41    ));
42
43    let mut o1 = OutputVariable::new(String::from("Acceleration"), (-1.0, 1.0), 100);
44    o1.add_membership(MembershipRange::new_gaussian(
45        o1.get_universe(),
46        "NB".to_string(),
47        -1.0,
48        0.2123,
49    ));
50    o1.add_membership(MembershipRange::new_gaussian(
51        o1.get_universe(),
52        "NS".to_string(),
53        -0.5,
54        0.2123,
55    ));
56    o1.add_membership(MembershipRange::new_gaussian(
57        o1.get_universe(),
58        "ZR".to_string(),
59        0.0,
60        0.2123,
61    ));
62    o1.add_membership(MembershipRange::new_gaussian(
63        o1.get_universe(),
64        "PS".to_string(),
65        0.5,
66        0.2123,
67    ));
68    o1.add_membership(MembershipRange::new_gaussian(
69        o1.get_universe(),
70        "PB".to_string(),
71        1.0,
72        0.2123,
73    ));
74
75    let mut fis = MamdaniFIS::new(
76        SNorms::Max,
77        TNorms::Min,
78        Implications::Min,
79        Aggregations::Max,
80        Defuzzifiers::Bisection,
81    );
82    fis.add_input(v1);
83    fis.add_input(v2);
84    fis.add_output(o1);
85
86    fis.add_rule(Rule::new_and(vec![0, 0, 2], 1.0));
87    fis.add_rule(Rule::new_and(vec![0, 1, 3], 1.0));
88    fis.add_rule(Rule::new_and(vec![0, 2, 4], 1.0));
89
90    fis.add_rule(Rule::new_and(vec![1, 0, 1], 1.0));
91    fis.add_rule(Rule::new_and(vec![1, 1, 2], 1.0));
92    fis.add_rule(Rule::new_and(vec![1, 2, 3], 1.0));
93
94    fis.add_rule(Rule::new_and(vec![2, 0, 0], 1.0));
95    fis.add_rule(Rule::new_and(vec![2, 1, 1], 1.0));
96    fis.add_rule(Rule::new_and(vec![2, 2, 2], 1.0));
97
98    let output = fis.compute_outputs(vec![40.0, 43.0]);
99    println!("output is: {:#?}", output);
100}
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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 implication(&self, connected_inputs: Vec<f64>) -> Vec<Vec<Vec<f64>>>

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pub fn aggregation(&self, implication_vec: Vec<Vec<Vec<f64>>>) -> Vec<Vec<f64>>

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pub fn defuzzification(&self, aggregation_vec: Vec<Vec<f64>>) -> Vec<f64>

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

Examples found in repository?
examples/speed_control.rs (line 98)
14fn main() {
15    let mut v1 = InputVariable::new("speed".to_string(), (0.0, 140.0));
16    v1.add_membership(MF::new(
17        "S".to_string(),
18        MFKind::Triangle(Triangle::new(-58.3, 0.0, 58.3)),
19    ));
20    v1.add_membership(MF::new(
21        "M".to_string(),
22        MFKind::Triangle(Triangle::new(11.67, 70.0, 128.3)),
23    ));
24    v1.add_membership(MF::new(
25        "L".to_string(),
26        MFKind::Triangle(Triangle::new(81.67, 140.0, 198.3)),
27    ));
28
29    let mut v2 = InputVariable::new("Distance".to_string(), (0.0, 50.0));
30    v2.add_membership(MF::new(
31        "S".to_string(),
32        MFKind::Triangle(Triangle::new(-20.83, 0.0, 20.83)),
33    ));
34    v2.add_membership(MF::new(
35        "M".to_string(),
36        MFKind::Triangle(Triangle::new(4.168, 25.0, 45.82)),
37    ));
38    v2.add_membership(MF::new(
39        "L".to_string(),
40        MFKind::Triangle(Triangle::new(29.17, 50.0, 70.82)),
41    ));
42
43    let mut o1 = OutputVariable::new(String::from("Acceleration"), (-1.0, 1.0), 100);
44    o1.add_membership(MembershipRange::new_gaussian(
45        o1.get_universe(),
46        "NB".to_string(),
47        -1.0,
48        0.2123,
49    ));
50    o1.add_membership(MembershipRange::new_gaussian(
51        o1.get_universe(),
52        "NS".to_string(),
53        -0.5,
54        0.2123,
55    ));
56    o1.add_membership(MembershipRange::new_gaussian(
57        o1.get_universe(),
58        "ZR".to_string(),
59        0.0,
60        0.2123,
61    ));
62    o1.add_membership(MembershipRange::new_gaussian(
63        o1.get_universe(),
64        "PS".to_string(),
65        0.5,
66        0.2123,
67    ));
68    o1.add_membership(MembershipRange::new_gaussian(
69        o1.get_universe(),
70        "PB".to_string(),
71        1.0,
72        0.2123,
73    ));
74
75    let mut fis = MamdaniFIS::new(
76        SNorms::Max,
77        TNorms::Min,
78        Implications::Min,
79        Aggregations::Max,
80        Defuzzifiers::Bisection,
81    );
82    fis.add_input(v1);
83    fis.add_input(v2);
84    fis.add_output(o1);
85
86    fis.add_rule(Rule::new_and(vec![0, 0, 2], 1.0));
87    fis.add_rule(Rule::new_and(vec![0, 1, 3], 1.0));
88    fis.add_rule(Rule::new_and(vec![0, 2, 4], 1.0));
89
90    fis.add_rule(Rule::new_and(vec![1, 0, 1], 1.0));
91    fis.add_rule(Rule::new_and(vec![1, 1, 2], 1.0));
92    fis.add_rule(Rule::new_and(vec![1, 2, 3], 1.0));
93
94    fis.add_rule(Rule::new_and(vec![2, 0, 0], 1.0));
95    fis.add_rule(Rule::new_and(vec![2, 1, 1], 1.0));
96    fis.add_rule(Rule::new_and(vec![2, 2, 2], 1.0));
97
98    let output = fis.compute_outputs(vec![40.0, 43.0]);
99    println!("output is: {:#?}", output);
100}

Trait Implementations§

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impl Debug for MamdaniFuzzyInferenceSystem

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

Formats the value using the given formatter. Read more

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