【数据聚类】基于模拟退火算法实现数据聚类Matlab源码

% clc;close all;clear all;p=[ 1739.94  1675.15  2395.96373.3  3087.05  2429.471756.77  1652  1514.98864.45  1647.31  2665.9222.85  3059.54  2002.33877.88  2031.66  3071.181803.58  1583.12  2163.052352.12  2557.04  1411.53401.3  3259.94  2150.98363.34  3477.95  2462.861571.17  1731.04  1735.33104.8  3389.83  2421.83499.85  3305.75  2196.222297.28  3340.14  535.622092.62  3177.21  584.321418.79  1775.89  2772.91845.59  1918.81  2226.492205.36  3243.74  1202.692949.16  3244.44  662.421692.62  1867.5  2108.971680.67  1575.78  1725.12802.88  3017.11  1984.98172.78  3084.49  2328.652063.54  3199.76  1257.211449.58  1641.58  3405.121651.52  1713.28  1570.38341.59  3076.62  2438.63291.02  3095.68  2088.95237.63  3077.78  2251.961702.8  1639.79  2068.741877.93  1860.96  1975.3867.81  2334.68  2535.11831.49  1713.11  1604.68460.69  3274.77  2172.992374.98  3346.98  975.312271.89  3482.97  946.71783.64  1597.99  2261.31198.83  3250.45  2445.081494.63  2072.59  2550.511597.03  1921.52  2126.761598.93  1921.08  1623.331243.13  1814.07  3441.072336.31  2640.26  1599.63354  3300.12  2373.612144.47  2501.62  591.51426.31  3105.29  2057.81507.13  1556.89  1954.51343.07  3271.72  2036.942201.94  3196.22  935.532232.43  3077.87  1298.871580.1  1752.07  2463.041962.4  1594.97  1835.951495.18  1957.44  3498.021125.17  1594.39  2937.7324.22  3447.31  2145.011269.07  1910.72  2701.971802.07  1725.81  1966.351817.36  1927.4  2328.791860.45  1782.88  1875.13];[num,n]=size(p);    %样品数目centernum=4;        %类别数目IDXO=[1 2 3 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 ];% size(IDXO)CO(1,:)=[ 1739.94   1675.15   2395.96];CO(2,:)=[373.3  3087.05  2429.47];CO(3,:)=[1756.77  1652  1514.98];    end%内层循环结束        T=T*0.9;%     if(T==0)%         break;%     end    time=time+1;%     if(time-timeb>1000)%         break;%     end    disp('已退火次数');    A=time-1        disp('最优目标函数值');    J=JOendtime1=toc%退火需要的时间hold on;plot3(CO(:,1),CO(:,2),CO(:,3),'o');grid;box%title('蚁群聚类结果(R=100,t=10000)')xlabel('X')ylabel('Y')zlabel('Z')index1 = find(IDXN == 1)index2 = find(IDXN == 2)index3 = find(IDXN == 3)index4 = find(IDXN == 4)plot3(p(index1,1),p(index1,2),p(index1,3),'r+');grid;plot3(p(index2,1),p(index2,2),p(index2,3),'g*');grid;plot3(p(index3,1),p(index3,2),p(index3,3),'kx');grid;plot3(p(index4,1),p(index4,2),p(index4,3),'m.');grid;