romanov73/fuzzy-controller
1
0
Fork 0
Code Issues 5 Pull Requests 1 Packages Projects Releases Wiki Activity

#8 -- Add some fuzzy

Browse Source
This commit is contained in:
Anton Romanov 2023-09-07 16:06:37 +04:00
parent 75765558d4
commit ab9a60cdd2
2 changed files with 117 additions and 82 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

8
src/main/java/ru/ulstu/fc/rule/controller/InferenceMvcController.java
View File

@ -8,12 +8,18 @@ import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.RequestMethod; import org.springframework.web.bind.annotation.RequestMethod;
import ru.ulstu.fc.rule.model.Antecedent; import ru.ulstu.fc.rule.model.Antecedent;
import ru.ulstu.fc.rule.model.InferenceForm; import ru.ulstu.fc.rule.model.InferenceForm;
import ru.ulstu.fc.rule.service.FuzzyInferenceService;
import java.util.Arrays; import java.util.Arrays;
import java.util.List; import java.util.List;
@Controller @Controller
public class InferenceMvcController { public class InferenceMvcController {
private final FuzzyInferenceService fuzzyInferenceService;
public InferenceMvcController(FuzzyInferenceService fuzzyInferenceService) {
this.fuzzyInferenceService = fuzzyInferenceService;
}
@GetMapping("/") @GetMapping("/")
public String initInference(Model model) { public String initInference(Model model) {
@ -28,7 +34,7 @@ public class InferenceMvcController {
model.addAttribute("ageAntecedents", getAgeAntecedents()); model.addAttribute("ageAntecedents", getAgeAntecedents());
model.addAttribute("incomeAntecedents", getIncomeAntecedents()); model.addAttribute("incomeAntecedents", getIncomeAntecedents());
model.addAttribute("inferenceForm", inferenceForm); model.addAttribute("inferenceForm", inferenceForm);
model.addAttribute("response", "123"); model.addAttribute("response", fuzzyInferenceService.getFuzzyInference().get(0));
return "index"; return "index";
} }

191
src/main/java/ru/ulstu/fc/rule/service/FuzzyInferenceService.java
View File

@ -1,84 +1,115 @@
package ru.ulstu.fc.rule.service; package ru.ulstu.fc.rule.service;
import com.fuzzylite.Engine; import com.fuzzylite.Engine;
import com.fuzzylite.activation.General;
import com.fuzzylite.defuzzifier.Centroid;
import com.fuzzylite.norm.s.Maximum;
import com.fuzzylite.norm.t.AlgebraicProduct;
import com.fuzzylite.norm.t.Minimum;
import com.fuzzylite.rule.Rule;
import com.fuzzylite.rule.RuleBlock;
import com.fuzzylite.term.Activated; import com.fuzzylite.term.Activated;
import com.fuzzylite.term.Triangle;
import com.fuzzylite.variable.InputVariable; import com.fuzzylite.variable.InputVariable;
import com.fuzzylite.variable.OutputVariable; import com.fuzzylite.variable.OutputVariable;
import org.slf4j.Logger; import org.slf4j.Logger;
import org.slf4j.LoggerFactory; import org.slf4j.LoggerFactory;
import org.springframework.stereotype.Service; import org.springframework.stereotype.Service;
import java.util.AbstractMap;
import java.util.ArrayList;
import java.util.List;
import java.util.Map; import java.util.Map;
import java.util.Map.Entry;
import java.util.stream.Collectors; import java.util.stream.Collectors;
@Service @Service
public class FuzzyInferenceService { public class FuzzyInferenceService {
private final static Logger LOG = LoggerFactory.getLogger(FuzzyInferenceService.class); private final static Logger LOG = LoggerFactory.getLogger(FuzzyInferenceService.class);
private final static String OUTPUT_VARIABLE_NAME = "state"; private final static String OUTPUT_VARIABLE_NAME = "кредит";
private final static String RULE_TEMPLATE = "if %s is %s and %s is %s then " private final static String RULE_TEMPLATE = "if %s is %s and %s is %s then "
+ OUTPUT_VARIABLE_NAME + OUTPUT_VARIABLE_NAME
+ " is %s"; + " is %s";
private final static String NO_RESULT = "Нет результата"; private final static String NO_RESULT = "Нет результата";
// private List<String> mapRulesToString(List<DbRule> dbRules) { private Map<String, List<Entry<String, Integer>>> inputFuzzyTerms = Map.of(
// return dbRules.stream().map(this::getFuzzyRule).collect(Collectors.toList()); "возраст",
// } List.of(
new AbstractMap.SimpleEntry("молодой", 35),
new AbstractMap.SimpleEntry("средний", 60),
new AbstractMap.SimpleEntry("старый", 100)),
"доход",
List.of(
new AbstractMap.SimpleEntry("небольшой", 35000),
new AbstractMap.SimpleEntry("средний", 100000),
new AbstractMap.SimpleEntry("высокий", 500000)));
// private String getFuzzyRule(DbRule dbRule) { private Map<String, List<Entry<String, Integer>>> outputFuzzyTerms = Map.of(
// return format(RULE_TEMPLATE, "кредит", List.of(new AbstractMap.SimpleEntry("небольшой", 200000),
// dbRule.getFirstAntecedent().name(), new AbstractMap.SimpleEntry("средний", 100000),
// dbRule.getFirstAntecedentValue().getAntecedentValue(), new AbstractMap.SimpleEntry("большой", 1000000)));
// dbRule.getSecondAntecedent().name(),
// dbRule.getSecondAntecedentValue().getAntecedentValue(),
// dbRule.getId());
// }
// private RuleBlock getRuleBlock(Engine engine, private List<String> getDemoRules() {
// List<DbRule> dbRules, return List.of(
// Map<String, Double> variableValues, String.format(RULE_TEMPLATE, "возраст", "молодой", "доход", "высокий", "большой"),
// List<AntecedentValue> antecedentValues, String.format(RULE_TEMPLATE, "возраст", "средний", "доход", "высокий", "средний"),
// List<Integer> consequentValues) { String.format(RULE_TEMPLATE, "возраст", "старый", "доход", "высокий", "средний")
// variableValues.forEach((key, value) -> { );
// InputVariable input = new InputVariable(); }
// input.setName(key);
// input.setDescription(""); private List<InputVariable> getInputVariables() {
// input.setEnabled(true); return List.of(getInputVariable("возраст", inputFuzzyTerms.get("возраст")),
// input.setRange(-1, 1); getInputVariable("доход", inputFuzzyTerms.get("доход")));
// input.setLockValueInRange(false); }
// input.addTerm(new Triangle("спад", -1, 0));
// input.addTerm(new Triangle("стабильно", -0.1, 0.1)); private InputVariable getInputVariable(String name, List<Entry<String, Integer>> terms) {
// input.addTerm(new Triangle("рост", 0, 1)); final InputVariable input = new InputVariable();
// engine.addInputVariable(input); input.setName(name);
// }); input.setDescription("");
// input.setEnabled(true);
// OutputVariable output = new OutputVariable(); input.setLockValueInRange(false);
// output.setName(OUTPUT_VARIABLE_NAME); double prev = 0;
// output.setDescription(""); for (int i = 0; i < terms.size(); i++) {
// output.setEnabled(true); Triangle term = new Triangle(terms.get(i).getKey(), prev, terms.get(i).getValue());
// output.setRange(0, consequentValues.size() + 0.1); prev = term.getVertexB();
// output.setAggregation(new Maximum()); input.addTerm(term);
// output.setDefuzzifier(new Centroid(10)); }
// output.setDefaultValue(Double.NaN); return input;
// output.setLockValueInRange(false); }
// for (int i = 0; i < consequentValues.size(); i++) {
// output.addTerm(new Triangle(consequentValues.get(i).toString(), i, i + 1)); private <T extends Enum<T>> OutputVariable getOutputVariable(String name, List<Entry<String, Integer>> terms) {
// } final OutputVariable output = new OutputVariable();
// engine.addOutputVariable(output); output.setName(name);
// output.setDescription("");
// RuleBlock mamdani = new RuleBlock(); output.setEnabled(true);
// mamdani.setName("mamdani"); output.setAggregation(new Maximum());
// mamdani.setDescription(""); output.setDefuzzifier(new Centroid(10));
// mamdani.setEnabled(true); output.setDefaultValue(Double.NaN);
// mamdani.setConjunction(new Minimum()); output.setLockValueInRange(false);
// //mamdani.setDisjunction(null); double prev = 0;
// mamdani.setImplication(new AlgebraicProduct()); for (int i = 0; i < terms.size(); i++) {
// mamdani.setActivation(new General()); Triangle term = new Triangle(terms.get(i).getKey(), prev, terms.get(i).getValue());
// mapRulesToString(dbRules).forEach(r -> { prev = term.getVertexB();
// LOG.info(r); output.addTerm(term);
// mamdani.addRule(Rule.parse(r, engine)); }
// }); return output;
// return mamdani; }
// }
private RuleBlock getRuleBlock(Engine engine,
List<String> rules) {
getInputVariables().forEach(engine::addInputVariable);
engine.addOutputVariable(getOutputVariable("кредит", outputFuzzyTerms.get("кредит")));
RuleBlock mamdani = new RuleBlock();
mamdani.setName("mamdani");
mamdani.setDescription("");
mamdani.setEnabled(true);
mamdani.setConjunction(new Minimum());
mamdani.setImplication(new AlgebraicProduct());
mamdani.setActivation(new General());
rules.forEach(r -> mamdani.addRule(Rule.parse(r, engine)));
return mamdani;
}
private Engine getFuzzyEngine() { private Engine getFuzzyEngine() {
Engine engine = new Engine(); Engine engine = new Engine();
@ -87,29 +118,6 @@ public class FuzzyInferenceService {
return engine; return engine;
} }
// public List<Assessment> getFuzzyInference(List<DbRule> dbRules,
// List<AntecedentValue> antecedentValues,
// Map<String, Double> variableValues) {
// validateVariables(variableValues, dbRules);
// variableValues.entrySet().forEach(e -> System.out.println(e.getKey() + " " + e.getValue()));
// Engine engine = getFuzzyEngine();
// List<Integer> consequentValues = dbRules.stream().map(DbRule::getId).collect(Collectors.toList());
// engine.addRuleBlock(getRuleBlock(engine, dbRules, variableValues, antecedentValues, consequentValues));
// Map<String, Double> consequents = getConsequent(engine, variableValues);
// if (consequents.containsKey(NO_RESULT)) {
// return new ArrayList<>();
// }
// List<Assessment> assessments = new ArrayList<>();
// for (Map.Entry<String, Double> consequent : consequents.entrySet()) {
// for (DbRule dbRule : dbRules) {
// if (dbRule.getId().equals(Integer.valueOf(consequent.getKey()))) {
// assessments.add(new Assessment(dbRule, consequent.getValue()));
// }
// }
// }
// return assessments;
// }
private Map<String, Double> getConsequent(Engine engine, Map<String, Double> variableValues) { private Map<String, Double> getConsequent(Engine engine, Map<String, Double> variableValues) {
OutputVariable outputVariable = engine.getOutputVariable(OUTPUT_VARIABLE_NAME); OutputVariable outputVariable = engine.getOutputVariable(OUTPUT_VARIABLE_NAME);
for (Map.Entry<String, Double> variableValue : variableValues.entrySet()) { for (Map.Entry<String, Double> variableValue : variableValues.entrySet()) {
@ -124,4 +132,25 @@ public class FuzzyInferenceService {
? Map.of(NO_RESULT, 0.0) ? Map.of(NO_RESULT, 0.0)
: outputVariable.fuzzyOutput().getTerms().stream().collect(Collectors.toMap(t -> t.getTerm().getName(), Activated::getDegree)); : outputVariable.fuzzyOutput().getTerms().stream().collect(Collectors.toMap(t -> t.getTerm().getName(), Activated::getDegree));
} }
public List<Double> getFuzzyInference() {
//variableValues.entrySet().forEach(e -> System.out.println(e.getKey() + " " + e.getValue()));
Engine engine = getFuzzyEngine();
//List<Integer> consequentValues = dbRules.stream().map(DbRule::getId).collect(Collectors.toList());
engine.addRuleBlock(getRuleBlock(engine, getDemoRules()));
Map<String, Double> consequents = getConsequent(engine, Map.of("возраст", 20.0, "доход", 250000.0));
if (consequents.containsKey(NO_RESULT)) {
return new ArrayList<>();
}
/*List<Assessment> assessments = new ArrayList<>();
for (Map.Entry<String, Double> consequent : consequents.entrySet()) {
for (DbRule dbRule : dbRules) {
if (dbRule.getId().equals(Integer.valueOf(consequent.getKey()))) {
assessments.add(new Assessment(dbRule, consequent.getValue()));
}
}
}*/
return List.of(0.0);
}
} }