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disengagement.fcl
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49
disengagement.fcl
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FUNCTION_BLOCK disengagement_FCL
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VAR_INPUT
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learning_quality : REAL;
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remaining_time : REAL;
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END_VAR
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VAR_OUTPUT
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disengagement : REAL;
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END_VAR
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FUZZIFY learning_quality
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TERM low := (0, 1) (0.2, 1) (0.4, 0);
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TERM medium := (0.2, 0) (0.4, 1) (0.6, 1) (0.8, 0);
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TERM high := (0.6, 0) (0.8, 1) (1, 1);
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END_FUZZIFY
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FUZZIFY remaining_time
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TERM low := (0, 1) (0.2, 1) (0.4, 0);
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TERM medium := (0.2, 0) (0.4, 1) (0.6, 1) (0.8, 0);
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TERM high := (0.6, 0) (0.8, 1) (1, 1);
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END_FUZZIFY
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DEFUZZIFY disengagement
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TERM low := (0, 1) (0.2, 1) (0.4, 0);
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TERM medium := (0.2, 0) (0.4, 1) (0.6, 1) (0.8, 0);
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TERM high := (0.6, 0) (0.8, 1) (1, 1);
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METHOD : COG;
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DEFAULT := 0.5;
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END_DEFUZZIFY
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RULEBLOCK No1
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AND : MIN;
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ACT : MIN;
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ACCU : MAX;
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RULE 1 : IF learning_quality IS low AND remaining_time IS low THEN disengagement IS high;
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RULE 2 : IF learning_quality IS low AND remaining_time IS medium THEN disengagement IS medium;
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RULE 3 : IF learning_quality IS low AND remaining_time IS high THEN disengagement IS medium;
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RULE 4 : IF learning_quality IS medium AND remaining_time IS low THEN disengagement IS medium;
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RULE 5 : IF learning_quality IS medium AND remaining_time IS medium THEN disengagement IS medium;
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RULE 6 : IF learning_quality IS medium AND remaining_time IS high THEN disengagement IS low;
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RULE 7 : IF learning_quality IS high AND remaining_time IS low THEN disengagement IS medium;
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RULE 8 : IF learning_quality IS high AND remaining_time IS medium THEN disengagement IS low;
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RULE 9 : IF learning_quality IS high AND remaining_time IS high THEN disengagement IS low;
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END_RULEBLOCK
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END_FUNCTION_BLOCK
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273
disengagement.js
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273
disengagement.js
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//--------------------------------------------------------------------------------
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// Code generated by jFuzzyLogic
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//--------------------------------------------------------------------------------
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function ruleAccumulationMethod_max(defuzzifierValue, valueToAggregate) {
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return (defuzzifierValue > valueToAggregate ? defuzzifierValue : valueToAggregate);
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}
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function ruleActivationMethod_min(degreeOfSupport, membership) {
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return (degreeOfSupport < membership ? degreeOfSupport : membership);
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}
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function ruleConnectionMethod_and(antecedent1, antecedent2) {
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return (antecedent1 < antecedent2 ? antecedent1 : antecedent2);
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}
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class FunctionBlock_disengagement_FCL {
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// VAR_INPUT
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learning_quality;
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remaining_time;
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// VAR_OUTPUT
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disengagement;
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// FUZZIFY learning_quality
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learning_quality_high;
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learning_quality_low;
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learning_quality_medium;
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// FUZZIFY remaining_time
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remaining_time_high;
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remaining_time_low;
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remaining_time_medium;
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// DEFUZZIFY disengagement
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defuzzify_disengagement;
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// Constructor
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constructor() {
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this.disengagement = 0.5;
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this.defuzzify_disengagement = new Array(1000);
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}
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// Calculate function block
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calc() {
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this.reset();
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this.fuzzify();
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this.calc_No1();
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this.defuzzify();
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}
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// RULEBLOCK No1
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calc_No1() {
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// RULE 1 : IF (learning_quality IS low) AND (remaining_time IS low) THEN disengagement IS high;
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let degreeOfSupport_1 = 1.0 * (ruleConnectionMethod_and(this.learning_quality_low, this.remaining_time_low));
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if (degreeOfSupport_1 > 0) {
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for (let i = 0; i < 1000; i++) {
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let x = 0.0 + i * 0.001;
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let membership = this.membership_disengagement_high(x);
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let y = ruleActivationMethod_min(degreeOfSupport_1 , membership);
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this.defuzzify_disengagement[i] = ruleAccumulationMethod_max(this.defuzzify_disengagement[i], y);
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}
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}
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// RULE 2 : IF (learning_quality IS low) AND (remaining_time IS medium) THEN disengagement IS medium;
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let degreeOfSupport_2 = 1.0 * (ruleConnectionMethod_and(this.learning_quality_low, this.remaining_time_medium));
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if (degreeOfSupport_2 > 0) {
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for (let i = 0; i < 1000; i++) {
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let x = 0.0 + i * 0.001;
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let membership = this.membership_disengagement_medium(x);
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let y = ruleActivationMethod_min(degreeOfSupport_2 , membership);
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this.defuzzify_disengagement[i] = ruleAccumulationMethod_max(this.defuzzify_disengagement[i], y);
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}
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}
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// RULE 3 : IF (learning_quality IS low) AND (remaining_time IS high) THEN disengagement IS medium;
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let degreeOfSupport_3 = 1.0 * (ruleConnectionMethod_and(this.learning_quality_low, this.remaining_time_high));
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if (degreeOfSupport_3 > 0) {
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for (let i = 0; i < 1000; i++) {
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let x = 0.0 + i * 0.001;
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let membership = this.membership_disengagement_medium(x);
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let y = ruleActivationMethod_min(degreeOfSupport_3 , membership);
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this.defuzzify_disengagement[i] = ruleAccumulationMethod_max(this.defuzzify_disengagement[i], y);
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}
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}
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// RULE 4 : IF (learning_quality IS medium) AND (remaining_time IS low) THEN disengagement IS medium;
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let degreeOfSupport_4 = 1.0 * (ruleConnectionMethod_and(this.learning_quality_medium, this.remaining_time_low));
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if (degreeOfSupport_4 > 0) {
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for (let i = 0; i < 1000; i++) {
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let x = 0.0 + i * 0.001;
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let membership = this.membership_disengagement_medium(x);
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let y = ruleActivationMethod_min(degreeOfSupport_4 , membership);
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this.defuzzify_disengagement[i] = ruleAccumulationMethod_max(this.defuzzify_disengagement[i], y);
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}
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}
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// RULE 5 : IF (learning_quality IS medium) AND (remaining_time IS medium) THEN disengagement IS medium;
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let degreeOfSupport_5 = 1.0 * (ruleConnectionMethod_and(this.learning_quality_medium, this.remaining_time_medium));
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if (degreeOfSupport_5 > 0) {
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for (let i = 0; i < 1000; i++) {
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let x = 0.0 + i * 0.001;
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let membership = this.membership_disengagement_medium(x);
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let y = ruleActivationMethod_min(degreeOfSupport_5 , membership);
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this.defuzzify_disengagement[i] = ruleAccumulationMethod_max(this.defuzzify_disengagement[i], y);
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}
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}
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// RULE 6 : IF (learning_quality IS medium) AND (remaining_time IS high) THEN disengagement IS low;
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let degreeOfSupport_6 = 1.0 * (ruleConnectionMethod_and(this.learning_quality_medium, this.remaining_time_high));
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if (degreeOfSupport_6 > 0) {
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for (let i = 0; i < 1000; i++) {
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let x = 0.0 + i * 0.001;
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let membership = this.membership_disengagement_low(x);
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let y = ruleActivationMethod_min(degreeOfSupport_6 , membership);
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this.defuzzify_disengagement[i] = ruleAccumulationMethod_max(this.defuzzify_disengagement[i], y);
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}
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}
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// RULE 7 : IF (learning_quality IS high) AND (remaining_time IS low) THEN disengagement IS medium;
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let degreeOfSupport_7 = 1.0 * (ruleConnectionMethod_and(this.learning_quality_high, this.remaining_time_low));
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if (degreeOfSupport_7 > 0) {
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for (let i = 0; i < 1000; i++) {
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let x = 0.0 + i * 0.001;
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let membership = this.membership_disengagement_medium(x);
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let y = ruleActivationMethod_min(degreeOfSupport_7 , membership);
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this.defuzzify_disengagement[i] = ruleAccumulationMethod_max(this.defuzzify_disengagement[i], y);
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}
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}
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// RULE 8 : IF (learning_quality IS high) AND (remaining_time IS medium) THEN disengagement IS low;
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let degreeOfSupport_8 = 1.0 * (ruleConnectionMethod_and(this.learning_quality_high, this.remaining_time_medium));
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if (degreeOfSupport_8 > 0) {
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for (let i = 0; i < 1000; i++) {
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let x = 0.0 + i * 0.001;
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let membership = this.membership_disengagement_low(x);
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let y = ruleActivationMethod_min(degreeOfSupport_8 , membership);
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this.defuzzify_disengagement[i] = ruleAccumulationMethod_max(this.defuzzify_disengagement[i], y);
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}
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}
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// RULE 9 : IF (learning_quality IS high) AND (remaining_time IS high) THEN disengagement IS low;
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let degreeOfSupport_9 = 1.0 * (ruleConnectionMethod_and(this.learning_quality_high, this.remaining_time_high));
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if (degreeOfSupport_9 > 0) {
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for (let i = 0; i < 1000; i++) {
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let x = 0.0 + i * 0.001;
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let membership = this.membership_disengagement_low(x);
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let y = ruleActivationMethod_min(degreeOfSupport_9 , membership);
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this.defuzzify_disengagement[i] = ruleAccumulationMethod_max(this.defuzzify_disengagement[i], y);
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}
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}
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}
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// Defuzzify
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defuzzify() {
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let sum_disengagement = 0.0;
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let wsum_disengagement = 0.0;
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let x;
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for (let i = 0; i < 1000; i++) {
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x = 0.0 + i * 0.001;
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sum_disengagement += this.defuzzify_disengagement[i];
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wsum_disengagement += x * this.defuzzify_disengagement[i];
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}
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if (sum_disengagement == 0) {
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sum_disengagement = 1.0;
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}
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this.disengagement = wsum_disengagement / sum_disengagement;
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}
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// Fuzzify all variables
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fuzzify() {
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this.learning_quality_high = this.membership_learning_quality_high(this.learning_quality);
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this.learning_quality_low = this.membership_learning_quality_low(this.learning_quality);
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this.learning_quality_medium = this.membership_learning_quality_medium(this.learning_quality);
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this.remaining_time_high = this.membership_remaining_time_high(this.remaining_time);
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this.remaining_time_low = this.membership_remaining_time_low(this.remaining_time);
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this.remaining_time_medium = this.membership_remaining_time_medium(this.remaining_time);
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}
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// Membership functions
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membership_disengagement_high(x) {
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if (x <= 0.6) return 0.0;
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if (x > 1.0) return 1.0;
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if (x <= 0.8) return 0.0 + (1.0 - 0.0) * ((x - 0.6) / (0.8 - 0.6));
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if (x <= 1.0) return 1.0 + (1.0 - 1.0) * ((x - 0.8) / (1.0 - 0.8));
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}
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membership_disengagement_low(x) {
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if (x <= 0.0) return 1.0;
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if (x > 0.4) return 0.0;
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if (x <= 0.2) return 1.0 + (1.0 - 1.0) * ((x - 0.0) / (0.2 - 0.0));
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if (x <= 0.4) return 1.0 + (0.0 - 1.0) * ((x - 0.2) / (0.4 - 0.2));
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}
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membership_disengagement_medium(x) {
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if (x <= 0.2) return 0.0;
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if (x > 0.8) return 0.0;
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if (x <= 0.4) return 0.0 + (1.0 - 0.0) * ((x - 0.2) / (0.4 - 0.2));
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if (x <= 0.6) return 1.0 + (1.0 - 1.0) * ((x - 0.4) / (0.6 - 0.4));
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if (x <= 0.8) return 1.0 + (0.0 - 1.0) * ((x - 0.6) / (0.8 - 0.6));
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}
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membership_learning_quality_high(x) {
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if (x <= 0.6) return 0.0;
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if (x > 1.0) return 1.0;
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if (x <= 0.8) return 0.0 + (1.0 - 0.0) * ((x - 0.6) / (0.8 - 0.6));
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if (x <= 1.0) return 1.0 + (1.0 - 1.0) * ((x - 0.8) / (1.0 - 0.8));
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}
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membership_learning_quality_low(x) {
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if (x <= 0.0) return 1.0;
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if (x > 0.4) return 0.0;
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if (x <= 0.2) return 1.0 + (1.0 - 1.0) * ((x - 0.0) / (0.2 - 0.0));
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if (x <= 0.4) return 1.0 + (0.0 - 1.0) * ((x - 0.2) / (0.4 - 0.2));
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}
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membership_learning_quality_medium(x) {
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if (x <= 0.2) return 0.0;
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if (x > 0.8) return 0.0;
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if (x <= 0.4) return 0.0 + (1.0 - 0.0) * ((x - 0.2) / (0.4 - 0.2));
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if (x <= 0.6) return 1.0 + (1.0 - 1.0) * ((x - 0.4) / (0.6 - 0.4));
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if (x <= 0.8) return 1.0 + (0.0 - 1.0) * ((x - 0.6) / (0.8 - 0.6));
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}
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membership_remaining_time_high(x) {
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if (x <= 0.6) return 0.0;
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if (x > 1.0) return 1.0;
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if (x <= 0.8) return 0.0 + (1.0 - 0.0) * ((x - 0.6) / (0.8 - 0.6));
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if (x <= 1.0) return 1.0 + (1.0 - 1.0) * ((x - 0.8) / (1.0 - 0.8));
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}
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membership_remaining_time_low(x) {
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if (x <= 0.0) return 1.0;
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if (x > 0.4) return 0.0;
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if (x <= 0.2) return 1.0 + (1.0 - 1.0) * ((x - 0.0) / (0.2 - 0.0));
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if (x <= 0.4) return 1.0 + (0.0 - 1.0) * ((x - 0.2) / (0.4 - 0.2));
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}
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membership_remaining_time_medium(x) {
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if (x <= 0.2) return 0.0;
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if (x > 0.8) return 0.0;
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if (x <= 0.4) return 0.0 + (1.0 - 0.0) * ((x - 0.2) / (0.4 - 0.2));
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if (x <= 0.6) return 1.0 + (1.0 - 1.0) * ((x - 0.4) / (0.6 - 0.4));
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if (x <= 0.8) return 1.0 + (0.0 - 1.0) * ((x - 0.6) / (0.8 - 0.6));
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}
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// Print
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print() {
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console.log("Function block disengagement_FCL:\n");
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console.log(" Output %s: %f\n", "disengagement" , this.disengagement);
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console.log(" Input %s: %f\n", "learning_quality" , this.learning_quality);
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console.log(" %s: %f\n", "learning_quality_high" , this.learning_quality_high);
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console.log(" %s: %f\n", "learning_quality_low" , this.learning_quality_low);
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console.log(" %s: %f\n", "learning_quality_medium" , this.learning_quality_medium);
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console.log(" Input %s: %f\n", "remaining_time" , this.remaining_time);
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console.log(" %s: %f\n", "remaining_time_high" , this.remaining_time_high);
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console.log(" %s: %f\n", "remaining_time_low" , this.remaining_time_low);
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console.log(" %s: %f\n", "remaining_time_medium" , this.remaining_time_medium);
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}
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// Reset output
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reset() {
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for (let i = 0 ; i < 1000; i++) {
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this.defuzzify_disengagement[i] = 0.0;
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}
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}
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};
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window.FunctionBlock_disengagement_FCL = FunctionBlock_disengagement_FCL;
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