#8 -- Add some fuzzy
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@ -8,12 +8,18 @@ import org.springframework.web.bind.annotation.RequestMapping;
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import org.springframework.web.bind.annotation.RequestMethod;
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import ru.ulstu.fc.rule.model.Antecedent;
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import ru.ulstu.fc.rule.model.InferenceForm;
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import ru.ulstu.fc.rule.service.FuzzyInferenceService;
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import java.util.Arrays;
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import java.util.List;
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@Controller
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public class InferenceMvcController {
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private final FuzzyInferenceService fuzzyInferenceService;
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public InferenceMvcController(FuzzyInferenceService fuzzyInferenceService) {
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this.fuzzyInferenceService = fuzzyInferenceService;
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}
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@GetMapping("/")
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public String initInference(Model model) {
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@ -28,7 +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", "123");
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model.addAttribute("response", fuzzyInferenceService.getFuzzyInference().get(0));
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return "index";
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}
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@ -1,84 +1,115 @@
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package ru.ulstu.fc.rule.service;
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import com.fuzzylite.Engine;
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import com.fuzzylite.activation.General;
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import com.fuzzylite.defuzzifier.Centroid;
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import com.fuzzylite.norm.s.Maximum;
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import com.fuzzylite.norm.t.AlgebraicProduct;
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import com.fuzzylite.norm.t.Minimum;
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import com.fuzzylite.rule.Rule;
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import com.fuzzylite.rule.RuleBlock;
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import com.fuzzylite.term.Activated;
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import com.fuzzylite.term.Triangle;
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import com.fuzzylite.variable.InputVariable;
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import com.fuzzylite.variable.OutputVariable;
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import org.slf4j.Logger;
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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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import java.util.stream.Collectors;
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@Service
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public class FuzzyInferenceService {
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private final static Logger LOG = LoggerFactory.getLogger(FuzzyInferenceService.class);
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private final static String OUTPUT_VARIABLE_NAME = "state";
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private final static String OUTPUT_VARIABLE_NAME = "кредит";
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private final static String RULE_TEMPLATE = "if %s is %s and %s is %s then "
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+ OUTPUT_VARIABLE_NAME
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+ " is %s";
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private final static String NO_RESULT = "Нет результата";
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// private List<String> mapRulesToString(List<DbRule> dbRules) {
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// return dbRules.stream().map(this::getFuzzyRule).collect(Collectors.toList());
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// }
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private Map<String, List<Entry<String, Integer>>> inputFuzzyTerms = Map.of(
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"возраст",
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List.of(
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new AbstractMap.SimpleEntry("молодой", 35),
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new AbstractMap.SimpleEntry("средний", 60),
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new AbstractMap.SimpleEntry("старый", 100)),
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"доход",
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List.of(
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new AbstractMap.SimpleEntry("небольшой", 35000),
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new AbstractMap.SimpleEntry("средний", 100000),
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new AbstractMap.SimpleEntry("высокий", 500000)));
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// private String getFuzzyRule(DbRule dbRule) {
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// return format(RULE_TEMPLATE,
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// dbRule.getFirstAntecedent().name(),
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// dbRule.getFirstAntecedentValue().getAntecedentValue(),
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// dbRule.getSecondAntecedent().name(),
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// dbRule.getSecondAntecedentValue().getAntecedentValue(),
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// dbRule.getId());
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// }
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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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new AbstractMap.SimpleEntry("средний", 100000),
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new AbstractMap.SimpleEntry("большой", 1000000)));
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// private RuleBlock getRuleBlock(Engine engine,
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// List<DbRule> dbRules,
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// Map<String, Double> variableValues,
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// List<AntecedentValue> antecedentValues,
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// List<Integer> consequentValues) {
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// variableValues.forEach((key, value) -> {
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// InputVariable input = new InputVariable();
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// input.setName(key);
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// input.setDescription("");
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// input.setEnabled(true);
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// input.setRange(-1, 1);
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// input.setLockValueInRange(false);
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// input.addTerm(new Triangle("спад", -1, 0));
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// input.addTerm(new Triangle("стабильно", -0.1, 0.1));
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// input.addTerm(new Triangle("рост", 0, 1));
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// engine.addInputVariable(input);
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// });
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//
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// OutputVariable output = new OutputVariable();
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// output.setName(OUTPUT_VARIABLE_NAME);
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// output.setDescription("");
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// output.setEnabled(true);
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// output.setRange(0, consequentValues.size() + 0.1);
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// output.setAggregation(new Maximum());
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// output.setDefuzzifier(new Centroid(10));
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// output.setDefaultValue(Double.NaN);
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// output.setLockValueInRange(false);
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// for (int i = 0; i < consequentValues.size(); i++) {
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// output.addTerm(new Triangle(consequentValues.get(i).toString(), i, i + 1));
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// }
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// engine.addOutputVariable(output);
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//
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// RuleBlock mamdani = new RuleBlock();
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// mamdani.setName("mamdani");
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// mamdani.setDescription("");
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// mamdani.setEnabled(true);
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// mamdani.setConjunction(new Minimum());
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// //mamdani.setDisjunction(null);
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// mamdani.setImplication(new AlgebraicProduct());
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// mamdani.setActivation(new General());
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// mapRulesToString(dbRules).forEach(r -> {
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// LOG.info(r);
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// mamdani.addRule(Rule.parse(r, engine));
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// });
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// return mamdani;
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// }
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private List<String> getDemoRules() {
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return List.of(
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String.format(RULE_TEMPLATE, "возраст", "молодой", "доход", "высокий", "большой"),
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String.format(RULE_TEMPLATE, "возраст", "средний", "доход", "высокий", "средний"),
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String.format(RULE_TEMPLATE, "возраст", "старый", "доход", "высокий", "средний")
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);
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}
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private List<InputVariable> getInputVariables() {
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return List.of(getInputVariable("возраст", inputFuzzyTerms.get("возраст")),
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getInputVariable("доход", inputFuzzyTerms.get("доход")));
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}
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private InputVariable getInputVariable(String name, List<Entry<String, Integer>> terms) {
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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.setEnabled(true);
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input.setLockValueInRange(false);
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double prev = 0;
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for (int i = 0; i < terms.size(); i++) {
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Triangle term = new Triangle(terms.get(i).getKey(), prev, terms.get(i).getValue());
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prev = term.getVertexB();
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input.addTerm(term);
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}
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return input;
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}
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private <T extends Enum<T>> OutputVariable getOutputVariable(String name, List<Entry<String, Integer>> terms) {
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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.setEnabled(true);
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output.setAggregation(new Maximum());
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output.setDefuzzifier(new Centroid(10));
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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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for (int i = 0; i < terms.size(); i++) {
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Triangle term = new Triangle(terms.get(i).getKey(), prev, terms.get(i).getValue());
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prev = term.getVertexB();
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output.addTerm(term);
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}
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return output;
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}
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private RuleBlock getRuleBlock(Engine engine,
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List<String> rules) {
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getInputVariables().forEach(engine::addInputVariable);
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engine.addOutputVariable(getOutputVariable("кредит", outputFuzzyTerms.get("кредит")));
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RuleBlock mamdani = new RuleBlock();
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mamdani.setName("mamdani");
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mamdani.setDescription("");
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mamdani.setEnabled(true);
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mamdani.setConjunction(new Minimum());
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mamdani.setImplication(new AlgebraicProduct());
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mamdani.setActivation(new General());
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rules.forEach(r -> mamdani.addRule(Rule.parse(r, engine)));
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return mamdani;
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}
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private Engine getFuzzyEngine() {
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Engine engine = new Engine();
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@ -87,29 +118,6 @@ public class FuzzyInferenceService {
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return engine;
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}
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// public List<Assessment> getFuzzyInference(List<DbRule> dbRules,
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// List<AntecedentValue> antecedentValues,
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// Map<String, Double> variableValues) {
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// validateVariables(variableValues, dbRules);
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// variableValues.entrySet().forEach(e -> System.out.println(e.getKey() + " " + e.getValue()));
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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, dbRules, variableValues, antecedentValues, consequentValues));
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// Map<String, Double> consequents = getConsequent(engine, variableValues);
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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 assessments;
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// }
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private Map<String, Double> getConsequent(Engine engine, Map<String, Double> variableValues) {
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OutputVariable outputVariable = engine.getOutputVariable(OUTPUT_VARIABLE_NAME);
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for (Map.Entry<String, Double> variableValue : variableValues.entrySet()) {
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@ -124,4 +132,25 @@ public class FuzzyInferenceService {
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? Map.of(NO_RESULT, 0.0)
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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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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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}
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}
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