1.完整项目描述和程序获取
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2.部分仿真图预览
3.算法概述
住宅价格是住宅市场的核心，住宅市场的变化关系到广大消费者的切身利益，商品房价格是升是降，销售是冷是旺，是社会关注的热点问题。因此，从不同角度来看，对商品住宅价格的研究都存在着重要的理论与现实意义。商品住宅价格的变化受市场供求、人口、居民收入水平、经济政策等诸多因素的影响，其随时间变动的过程具有很大的不确定性，为较全面地刻画各方面对住房价格的影响，以把握未来住房价格的变动趋势，将通过神经元网络理论的预测方法，延伸应用于商品住宅价格的研究，对住宅价格进行科学的预测。
4.部分源码
%% Parameters initialization
%load data
load data\housing_data.mat
%Display the original data
figure;
subplot(4,4,1);plot(x(1,:));title('Per capita crime rate per town');
subplot(4,4,2);plot(x(2,:));title('Proportion of residential land zoned for lots over 500m2');
subplot(4,4,3);plot(x(3,:));title('Proportion of non-retail business acres per town');
subplot(4,4,4);plot(x(4,:));title('1 within 1km from the sea, 0 otherwise');
subplot(4,4,5);plot(x(5,:));title('Nitric oxides concentration (parts per 10 million)');
subplot(4,4,6);plot(x(6,:));title('Average number of rooms per dwelling');
subplot(4,4,7);plot(x(7,:));title('Proportion of owner-occupied units built prior to 1940');
subplot(4,4,8);plot(x(8,:));title('Weighted distances to a main shopping center');
subplot(4,4,9);plot(x(9,:));title('Index of accessibility to motorways');
subplot(4,4,10);plot(x(10,:));title('Full-value of council rate per $10,000');
subplot(4,4,11);plot(x(11,:));title('Pupil-teacher ratio by town');
subplot(4,4,12);plot(x(12,:));title('Population below the age of 20');
subplot(4,4,13);plot(x(13,:));title('Percentage of retirees');
figure;
plot(10000*t,'r');title('PRICE');grid on
%% Select multiple data,train neural network
%step1：parameter
net = fitnet(10);
net.trainParam.epcohs = 1000;%train times
net.trainParam.goal = 0.0001;%aim error
%step2：train
net = train(net,x,t);
%% By using the neural network to predict the price of houses
view(net);
y1 = net(x);%predict
%% Shows the result
figure;
subplot(221);plot(t);
title('Original price');axis([0,length(t),0,max(t)]);
subplot(222);plot(y1);
title('Predict prices ');axis([0,length(y1),0,max(y1)]);
subplot(223);plot(y1);hold on;plot(t,'r');hold off;
legend('Predict prices','Original price');
title('Predict prices');axis([0,length(y1),0,max(y1)]);
subplot(224);plot(y1 - t,'k');
title('Prediction error ');
05_003_m
