#8 -- final of the demo
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@ -34,7 +34,7 @@ public class InferenceMvcController {
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model.addAttribute("ageAntecedents", getAgeAntecedents());
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model.addAttribute("incomeAntecedents", getIncomeAntecedents());
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model.addAttribute("inferenceForm", inferenceForm);
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model.addAttribute("response", fuzzyInferenceService.getFuzzyInference().get(0));
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model.addAttribute("response", fuzzyInferenceService.getFuzzyInference());
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return "index";
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}
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@ -17,7 +17,6 @@ import org.slf4j.LoggerFactory;
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import org.springframework.stereotype.Service;
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import java.util.AbstractMap;
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import java.util.ArrayList;
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import java.util.List;
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import java.util.Map;
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import java.util.Map.Entry;
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@ -45,7 +44,7 @@ public class FuzzyInferenceService {
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new AbstractMap.SimpleEntry("высокий", 500000)));
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private Map<String, List<Entry<String, Integer>>> outputFuzzyTerms = Map.of(
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"кредит", List.of(new AbstractMap.SimpleEntry("небольшой", 200000),
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"кредит", List.of(new AbstractMap.SimpleEntry("небольшой", 20000),
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new AbstractMap.SimpleEntry("средний", 100000),
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new AbstractMap.SimpleEntry("большой", 1000000)));
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@ -66,6 +65,7 @@ public class FuzzyInferenceService {
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final InputVariable input = new InputVariable();
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input.setName(name);
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input.setDescription("");
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input.setRange(0, terms.get(terms.size() - 1).getValue());
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input.setEnabled(true);
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input.setLockValueInRange(false);
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double prev = 0;
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@ -81,9 +81,10 @@ public class FuzzyInferenceService {
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final OutputVariable output = new OutputVariable();
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output.setName(name);
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output.setDescription("");
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output.setRange(0, terms.get(terms.size() - 1).getValue());
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output.setEnabled(true);
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output.setAggregation(new Maximum());
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output.setDefuzzifier(new Centroid(10));
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output.setDefuzzifier(new Centroid(terms.get(terms.size() - 1).getValue()));
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output.setDefaultValue(Double.NaN);
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output.setLockValueInRange(false);
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double prev = 0;
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@ -133,24 +134,10 @@ public class FuzzyInferenceService {
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: outputVariable.fuzzyOutput().getTerms().stream().collect(Collectors.toMap(t -> t.getTerm().getName(), Activated::getDegree));
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}
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public List<Double> getFuzzyInference() {
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//variableValues.entrySet().forEach(e -> System.out.println(e.getKey() + " " + e.getValue()));
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public Map<String, Double> getFuzzyInference() {
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Engine engine = getFuzzyEngine();
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//List<Integer> consequentValues = dbRules.stream().map(DbRule::getId).collect(Collectors.toList());
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engine.addRuleBlock(getRuleBlock(engine, getDemoRules()));
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Map<String, Double> consequents = getConsequent(engine, Map.of("возраст", 20.0, "доход", 250000.0));
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if (consequents.containsKey(NO_RESULT)) {
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return new ArrayList<>();
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}
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/*List<Assessment> assessments = new ArrayList<>();
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for (Map.Entry<String, Double> consequent : consequents.entrySet()) {
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for (DbRule dbRule : dbRules) {
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if (dbRule.getId().equals(Integer.valueOf(consequent.getKey()))) {
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assessments.add(new Assessment(dbRule, consequent.getValue()));
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}
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}
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}*/
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return List.of(0.0);
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return getConsequent(engine, Map.of("возраст", 20.0, "доход", 250000.0));
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}
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}
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