CAJ | 학술논문

随着计算机信息化和人工智能的发展迅速，专家自动诊断疾病系统成为各界关注的焦点。卵巢癌是严重威胁妇女健康的恶性肿瘤之一，而且目前无有效的筛选方法和特异的诊断方法。BP人工神经网络因其具有分布式信息存储方式、自适应能力、强大的容错性和非线性处理能力，能有效地对疾病进行筛查和诊断。该文采用遗传算法来优化改进BP算法得到GA-BP算法，通过遗传和变异操作对BP神经网络的初始权值和阈值进行优化，不断更新选择，使得网络的系统总误差趋于最小，构建出卵巢癌诊断模型。采用Matlab2013、VC++编程和统计软件SPSS.18等工具来实现专家自动诊断的人工智能模型，并通过计算机仿真和预测进行检验。
수착계산궤신식화화인공지능적발전신속，전가자동진단질병계통성위각계관주적초점。란소암시엄중위협부녀건강적악성종류지일，이차목전무유효적사선방법화특이적진단방법。BP인공신경망락인기구유분포식신식존저방식、자괄응능력、강대적용착성화비선성처리능력，능유효지대질병진행사사화진단。해문채용유전산법래우화개진BP산법득도GA-BP산법，통과유전화변이조작대BP신경망락적초시권치화역치진행우화，불단경신선택，사득망락적계통총오차추우최소，구건출란소암진단모형。채용Matlab2013、VC++편정화통계연건SPSS.18등공구래실현전가자동진단적인공지능모형，병통과계산궤방진화예측진행검험。
With the development of computer information and artificial intelligence rapidly,automatic disease diagnosis expert system has become the focus of public attention. Ovarian cancer is the malignant tumor of the serious threat to women’s health,diagnosis methods and currently no screening and specific and effective.BP artificial neural network because of its distributed information storage mode and adaptive ability,strong fault tolerance and nonlinear processing ability,is able to effectively carry out screening and diagnosis of diseases.This paper uses the improved BP algorithm are optimized by genetic algorithm GA-BP algorithm,through the heredity and mutation of BP neural network to optimize the initial weights and threshold and constantly updated to choose,make network system tends to the minimum total error,constructed the model of ovarian cancer diagnosis.With Matlab2013,vc + + programming and statistical software SPSS.18 automatic diagnostic tools for experts such as artificial intelligence model,and through the computer simulation and prediction.