基于遗传算法的排序融合方法matlab程序

function distance=RankingDistance(ranking1,ranking2,distanceType,weight) %ranking1为计算权值的基准 %kendall距离输出的是归一化后的距离 %footrule距离输出的是归一化后的距离 if nargin<4 weight=ones(size(ranking1)); end Sweight=weightRerank(ranking1,weight);% - 按照排序顺序进行加权，靠前的序号和靠后的序号对结果影响程度不同 switch distanceType case 1 %Spearman's footrule distance=sum(abs(ranking1-ranking2).*Sweight,2)*2/(max(size(ranking1).^2)); case 2 %Spearman's footrule based 2-norm distance=sum(((ranking1-ranking2).^2).*Sweight,2)*2/(max(size(ranking1).^2)); case 3 %Kendall Distance %-------------------------------------------------------------------------- % %将全局排序位置转化为局部排序关系 % ranking1=RankingSort(ranking1); % ranking2=RankingSort(ranking2); %-------------------------------------------------------------------------- distance=KendallDistance(ranking1,ranking2); end end function Sweight=weightRerank(ranking,weight) [~,tmpRanking]=sort(ranking); [~,intRanking]=sort(tmpRanking); Sweight=ones(size(intRanking)); for i=1:size(intRanking,2) Sweight(intRanking(i))=weight(i); end end function distance=KendallDistance(ranking1,ranking2) % if KendallErrDisp % if max(size(unique(ranking1)))~=max(size(ranking1))||max(size(unique(ranking2)))~=max(size(ranking1)) % disp('排序有同序号项') % end % end LengthOfRank=max(size(ranking1)); tmpDistance=0; for i=1:LengthOfRank-1 for j=i+1:LengthOfRank if (ranking1(i)>ranking1(j))&&(ranking2(i)>ranking2(j)) else if (ranking1(i)<ranking1(j))&&(ranking2(i)<ranking2(j)) else if (ranking1(i)==ranking1(j))&&(ranking2(i)==ranking2(j)) else tmpDistance=tmpDistance+1; end end end % OrderJudge=(ranking1(i)-ranking1(j))*(ranking2(i)-ranking2(j)); % if OrderJudge<=0 % % if (ranking1(i)-ranking1(j))==0&&(ranking2(i)-ranking2(j))==0 % if (ranking1(i)-ranking1(j))==0||(ranking2(i)-ranking2(j))==0 % else % tmpDistance=tmpDistance+1; % end % end end end distance=tmpDistance*2/LengthOfRank/(LengthOfRank-1); end