毕设：智能组卷平台（遗传算法）
2024-05-13 12:23:24
项目描述
智能组卷平台（遗传算法）
分为3个端：管理员端，老师端，学生端
主要功能包括 登录，学生管理，老师管理，题目管理，试卷管理，
知识管理。任务管理，教育管理，试卷管理，批卷管理，
运行环境
jdk8+redis+mysql+IntelliJ IDEA+maven
项目技术
springboot+layui+vue
项目截图
老师端
学生端
部分代码
遗传算法的使用
/*** 遗传算法*/
public class GAUtil {//编译概率private static final double mutationRate = 0.085;//精英主义private static final boolean elitism = true;//淘汰数组大小private static final int tournamentSize = 5;/*** 种群进化* @param pop 种群对象* @param rule 进化规则* @return*/public static Population evolvePopulation(Population pop, Rule rule,QuestionService questionService){Population newPop = new Population(pop.getLength());int elitismOffset;//精英主义if(elitism){elitismOffset = 1;//保留上一代最优秀的个体ExamPaperAlgotithmBean fitness = pop.getFitness();fitness.setId(0);newPop.setPaper(0,fitness);}//种群交叉操作，从当前的种群pop来创建下一代种群newPopfor (int i = elitismOffset; i < newPop.getLength(); i++){//得到两个较优选择ExamPaperAlgotithmBean parent1 = select(pop);ExamPaperAlgotithmBean parent2 = select(pop);//保持连个选择不同while (parent1.getId() == parent2.getId()){parent2 = select(pop);}//交叉ExamPaperAlgotithmBean child = crossover(parent1, parent2, rule,questionService);child.setId(i);newPop.setPaper(i,child);}//种群变异操作ExamPaperAlgotithmBean tmpPeper;for (int i = elitismOffset; i < newPop.getLength(); i++){tmpPeper = newPop.getPaper(i);mutate(tmpPeper,questionService);//计算知识点覆盖率和适应度tmpPeper.setChapterCoverage(rule);tmpPeper.setAdaptationDegree(rule, ExamPaperWeightEnum.CHAPTER_WEIGHT,ExamPaperWeightEnum.DIFFICULTY_WEIGHT);}return newPop;}/*** 选择算子:得到最优个体* @param population* @return*/public static ExamPaperAlgotithmBean select(Population population){Population pop = new Population(tournamentSize);for (int i = 0; i < tournamentSize; i++){pop.setPaper(i,population.getPaper((int)(Math.random()*population.getLength())));}return pop.getFitness();}/*** 交叉算子：* @param parent1* @param parent2* @param rule* @return*/public static ExamPaperAlgotithmBean crossover(ExamPaperAlgotithmBean parent1,ExamPaperAlgotithmBean parent2,Rule rule,QuestionService questionService){ExamPaperAlgotithmBean child = new ExamPaperAlgotithmBean(parent1.getQuestionSize());int s1 = (int) Math.random() * parent1.getQuestionSize();int s2 = (int) Math.random() * parent1.getQuestionSize();// parent1的startPos、endPos之间的序列，会被遗传到下一代int startPos = s1 < s2 ? s1 : s2;int endPos = s1 > s2 ? s1 : s2;for (int i = startPos; i < endPos; i++){child.saveQuestion(i,parent1.getQuestions().get(i));//parent1遗传给下一代的序列}List<Integer> chapterList = rule.getChapters();for (int i = 0; i < startPos; i++){if (!child.containsQuestion(parent2.getQuestions().get(i))){child.saveQuestion(i,parent2.getQuestions().get(i));}else {//如果出现相同题目，重新查找一题题目类型、知识点相同的题目Integer type = parent2.getQuestions().get(i).getQuestionType();List<Question> questions = questionService.selectByLevelTypeChapters(type, chapterList);child.saveQuestion(i,questions.get((int) Math.random()*questions.size()));}}for (int i = endPos; i < parent2.getQuestionSize(); i++){if (!child.containsQuestion(parent2.getQuestions().get(i))){child.saveQuestion(i,parent2.getQuestions().get(i));}else {//如果出现相同题目，重新查找一题题目类型、知识点相同的题目Integer type = parent2.getQuestions().get(i).getQuestionType();List<Question> questions = questionService.selectByLevelTypeChapters(type, chapterList);child.saveQuestion(i,questions.get((int) Math.random()*questions.size()));}}return child;}/*** 突变算子 每个个体的每个基因都有可能突变 每个基因变异的概率大概为0.085，小于等于时可以变异* @param paper*/public static void mutate(ExamPaperAlgotithmBean paper,QuestionService questionService){Question tmpQuestion;List<Question> list;int index;for (int i = 0;i < paper.getQuestionSize(); i++){if (Math.random() <= mutationRate){//进行突变tmpQuestion = paper.getQuestions().get(i);//从题库中获取和变异的题目类型一样分数相同的的题目（不包含编译题目）Integer type = paper.getQuestions().get(i).getQuestionType();Integer chapterId = paper.getQuestions().get(i).getChapterId();List<Integer> chapterIds = new ArrayList<>();chapterIds.add(chapterId);list = questionService.selectByLevelTypeChapters(type, chapterIds);if (list.size() > 0){index = (int) Math.random()*list.size();paper.saveQuestion(i,list.get(index));}}}}}智能组卷
/*** 随机生成试卷题目id列表* @param model* @param user* @return*/private List<Integer> getRandomQuetionIds(ExamPaperAttrVM model, User user){ ;List<Integer> errorIds = examPaperQuestionCustomerAnswerService.selectErrorIdList(user.getId());ExamPaperQuestionsAttrVM questionsAttrVM = new ExamPaperQuestionsAttrVM(model.getSubjectId(), model.getDifficult(), errorIds);List<Integer> newIds = questionMapper.selectNotErrorQuestionIds(questionsAttrVM);Integer errorNum = model.getErrorQuestionNum();Integer newNum = model.getNewQuestionNum();List<Integer> ids = ExamUtil.randomNewErrorQuestionIds(errorNum, newNum, errorIds, newIds);return ids;}/*** 生成试卷请求编辑vo -- 用于生成试卷对象 -- 智能训练* @param model* @return*/@Overridepublic ExamPaperEditRequestVM getExamPaperEditRequestVM(ExamPaperAttrVM model){User user = webContext.getCurrentUser();List<Integer> Ids = getRandomQuetionIds(model,user);List<Question> questions = questionService.selectQuestionsByIds(Ids);String totalScore = ExamUtil.scoreToVM(questions.stream().mapToInt(q -> q.getScore()).sum());//试卷总分List<Integer> qTypes = questions.stream().map(q ->q.getQuestionType()).distinct().collect(Collectors.toList());//试卷所有类型题名（单选、多选..）List<ExamPaperTitleItemVM> titleItems = qTypes.stream().map(qt -> {List<Question> titleQuestions =questions.stream().filter(q -> q.getQuestionType() == qt).collect(Collectors.toList());//试卷每个小标题下的题目列表List<QuestionEditRequestVM> titleQuestionEditRequestVMs = titleQuestions.stream().map(q -> {QuestionEditRequestVM titleQuestionEditRequestVM = questionService.getQuestionEditRequestVM(q);return titleQuestionEditRequestVM;}).collect(Collectors.toList());//将Quetion转换为vo对象ExamPaperTitleItemVM examPaperTitleItemVM = new ExamPaperTitleItemVM();//生产试卷examPaperTitleItemVM.setName(QuestionTypeEnum.fromCode(qt).getName());examPaperTitleItemVM.setQuestionItems(titleQuestionEditRequestVMs);return examPaperTitleItemVM;}).collect(Collectors.toList());ExamPaperEditRequestVM vm = new ExamPaperEditRequestVM();vm.setName(ExamPaperTypeEnum.TelligentTrain.getName() + count.incrementAndGet());vm.setLevel(user.getUserLevel());vm.setSubjectId(model.getSubjectId());vm.setScore(totalScore);vm.setPaperType(ExamPaperTypeEnum.TelligentTrain.getCode());vm.setSuggestTime(ExamUtil.getExamPaperSuggestTime(questions));vm.setTitleItems(titleItems);return vm;}/*** 智能组卷* @param model* @return*/@Overridepublic ExamPaperEditRequestVM getExamPaperEditRequestVM(ExamPaperRuleVM model) {User user = webContext.getCurrentUser();ExamPaperEditRequestVM vm = getIntelligenceExamPaper(model, user, ExamPaperWeightEnum.runCount, ExamPaperWeightEnum.population_size, ExamPaperWeightEnum.expectAdapter);return vm;}/*** 智能组卷* @param model* @param user* @param runCount* @param populationSize* @param expectAdapter* @return*/private ExamPaperEditRequestVM getIntelligenceExamPaper(ExamPaperRuleVM model, User user, int runCount, int populationSize,double expectAdapter ){Rule rule = getRuleFromVM(model);if (rule == null){throw new RuntimeException();}List<List<Question>> lists = getQuestionsByLevelAndChapters(rule.getChapters());ExamPaperAlgotithmBean fitness = getFitnessFromPopulation(rule, lists, true, runCount, populationSize, expectAdapter);List<Question> questions = fitness.getQuestions();String totalScore = ExamUtil.scoreToVM(questions.stream().mapToInt(q -> q.getScore()).sum());List<Integer> qTypes = questions.stream().map(q ->q.getQuestionType()).distinct().collect(Collectors.toList());List<ExamPaperTitleItemVM> titleItems = qTypes.stream().map(qt -> {List<Question> titleQuestions =questions.stream().filter(q -> q.getQuestionType() == qt).collect(Collectors.toList());List<QuestionEditRequestVM> titleQuestionEditRequestVMs = titleQuestions.stream().map(q -> {Chapter chapter = chapterMapper.selectByPrimaryKey(q.getChapterId());TextContent textContent = textContentService.selectById(q.getInfoTextContentId());QuestionObject questionObject = JsonUtil.toJsonObject(textContent.getContent(), QuestionObject.class);QuestionEditRequestVM titleQuestionEditRequestVM = questionService.getQuestionEditRequestVM(q);titleQuestionEditRequestVM.setTitle(questionObject.getTitleContent() + "(" + chapter.getName() + ")");return titleQuestionEditRequestVM;}).collect(Collectors.toList());//将Quetion转换为vo对象ExamPaperTitleItemVM examPaperTitleItemVM = new ExamPaperTitleItemVM();//生产试卷examPaperTitleItemVM.setName(QuestionTypeEnum.fromCode(qt).getName());examPaperTitleItemVM.setQuestionItems(titleQuestionEditRequestVMs);return examPaperTitleItemVM;}).collect(Collectors.toList());ExamPaperEditRequestVM vm = new ExamPaperEditRequestVM();vm.setName(ExamPaperTypeEnum.TelligentExam.getName() + count.incrementAndGet());vm.setLevel(user.getUserLevel());vm.setSubjectId(model.getSubjectId());vm.setScore(totalScore);vm.setPaperType(ExamPaperTypeEnum.TelligentExam.getCode());vm.setSuggestTime(ExamUtil.getExamPaperSuggestTime(questions));vm.setTitleItems(titleItems);return vm;}/*** 得到不同类型题chapters知识点内的题目，然后添加到列表中* @param chapters* @return*/private List<List<Question>> getQuestionsByLevelAndChapters(List<Integer> chapters){List<List<Question>> questions = new ArrayList<>(5);for (int i = QuestionTypeEnum.SingleChoice.getCode();i <= QuestionTypeEnum.ShortAnswer.getCode(); i++){questions.add(questionService.selectByLevelTypeChapters(i,chapters));}return questions;}private Rule getRuleFromVM(ExamPaperRuleVM model){Rule rule = modelMapper.map(model, Rule.class);double difficulty = rule.getDifficulty();rule.setDifficulty(difficulty * 1.5 / 5);//不限、简单、中等、困难 * 1.5Integer total = ExamUtil.getExpectTotalScore(rule);rule.setTotalScore(total);return rule;}/*** 种群进化选出最优个体* @param rule* @param lists* @param initFlag* @param runCount* @param populationSize* @param expectAdapter* @return*/private ExamPaperAlgotithmBean getFitnessFromPopulation(Rule rule,List<List<Question>> lists,boolean initFlag,int runCount,int populationSize,double expectAdapter){int initCount = 0;Population population = new Population(populationSize,true,rule,lists);System.out.println("---------------------------------------");int index = 0;for (ExamPaperAlgotithmBean e: population.getPapers()){System.out.println("个体：" + ++index + "适应度为：" + e.getAdaptationDegree() + "难度为：" + e.getDifficulty() + "知识点覆盖率为：" + e.getChapterCoverage());}System.out.println("初始适应度：" + population.getFitness().getAdaptationDegree());while (initCount < runCount && population.getFitness().getAdaptationDegree() < expectAdapter){initCount++;GAUtil.evolvePopulation(population,rule,questionService);System.out.println("第 " + initCount + " 次进化，适应度为：" + population.getFitness().getAdaptationDegree());}System.out.println("进化次数：" + initCount);System.out.println(population.getFitness().getAdaptationDegree());ExamPaperAlgotithmBean fitness = population.getFitness();return fitness;}毕设：智能组卷平台（遗传算法）相关推荐
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