Matlab基于改进的 Harsdorf 距离的DBSCAN船舶航迹聚类

% clc % close all % clear all % % %% % % global noisenum % % % %% 数据路径 % % % path='AIS1246-1.CSV'; % % % %% 计算H距离 % % % [data1,px,tempMapDis,tempMapV,tempMapHeading]=myHuasdoff(path); % % % Hdist = (tempMapDis + tempMapV + tempMapHeading) / 3; % % % %% 取距离中的较小值 % % % for i = 1 : size(Hdist,1) % % % for j = i + 1 : size(Hdist,2) % % % max1 = Hdist(i,j); % % % if max1 < Hdist(j,i) % % % max1 = Hdist(j,i); % % % end % % % Hdist(i,j) = max1; % % % Hdist(j,i) = max1; % % % end % % % end % load data.mat % %% 设置聚类参数 % eps=0.056; % MinNum=18; % %% DBscan 聚类 % cluster_label=DBSCAN(Hdist,eps,MinNum); % %% 计算聚类数 % cluster_num=max(cluster_label); % %% 计算轨迹平均位置 % meanpos=zeros(length(cluster_label),2); % for i=1:length(cluster_label) % meanpos(i,1)=mean(data1(data1(:,1)==i,2)); % meanpos(i,2)=mean(data1(data1(:,1)==i,3)); % end % %% 画图 % % %% plot trace % figure % Plottrace(data1,cluster_label) % title(sprintf(['DBSCAN聚类结果（航迹示意图） \n邻域距离 = ' num2str(eps) ', 最小样本数 = ' num2str(MinNum) '\n航迹类别:' num2str(cluster_num) '类,噪声航迹:' num2str(noisenum) '条'])); % xlabel('经度') % ylabel('纬度') % %% plot meanpos % % figure % % Plotmeanpos(meanpos, cluster_label); % % title(sprintf(['DBSCAN聚类结果（航迹平均坐标示意图） \n邻域距离 = ' num2str(eps) ', 最小样本数 = ' num2str(MinNum) '\n航迹类别:' num2str(cluster_num) '类,噪声航迹:' num2str(noisenum) '条'])); % % xlabel('经度') % % ylabel('维度') % % 逐类计数典型轨迹 % filename='典型轨迹数据.xlsx'; % DXcolor={'black','magenta'}; % DXindexlist=[15,36]; % Legendslist={'主航道出口船舶典型轨迹','主航道进口船舶典型轨迹'}; % % for k=1:cluster_num % data_ind=[]; % temp_trace_ind=find(cluster_label==k); % for t=1:length(temp_trace_ind) % data_ind1=find(data1(:,1)==temp_trace_ind(t)); % data_ind=[data_ind;data_ind1]; % end % % Legendsname = ['第' num2str(k) '类航迹的典型航迹']; % Legendsname=Legendslist{k}; % [DXfinalData{k},DXdatanew{k},DXpx{k},DXfData{k},DXMapDis{k},DXMapV{k},DXMapHeading{k}]=DXGJ(data1(data_ind,:),DXcolor{k},Legendsname,DXindexlist(k)); % datawriter(filename,DXfData{k},Legendsname)% end % end % % % %% % % addpath '识别数据集' % % filename_train_in1='进口正常行为数据.xlsx'; % % filename_train_in0='进口异常行为数据.xlsx'; % addpath '正常与异常数据' % filename_train_in1='进口正常轨迹数据.xlsx'; % filename_train_in0='进口异常轨迹数据.xlsx'; % [data_in1,finalData_in1]=makeData(filename_train_in1); % [data_in0,finalData_in0]=makeData(filename_train_in0); % stepNum=20; % DistThre=linspace(1,250,stepNum); % SogThre=linspace(1,8,stepNum); % CogThre=linspace(1,8,stepNum); % % % % DistThre=1:0.01:250; % DXTrace=DXfData{2}; % % ACC_P=[]; % % ACC_S=[]; % % ACC_C=[]; % for i=1:stepNum % tDistThre=DistThre(i); % tSogThre=SogThre(i); % tCogThre=CogThre(i); % [ACC_P(i),ACC_S(i),ACC_C(i)]=drawErrerRate(finalData_in1,finalData_in0,DXTrace,tDistThre,tSogThre,tCogThre); % end % %% filename='阈值.xlsx'; data=xlsread(filename); figure plot(DistThre,[ACC_P.r],'-gp','DisPlayName','准确率') hold on plot(DistThre,1-[ACC_P.r],'-rd','DisPlayName','误警率') xlabel('位置偏差') legend figure plot(SogThre,[ACC_S.r],'-gp','DisPlayName','准确率') hold on plot(SogThre,1-[ACC_S.r],'-rd','DisPlayName','误警率') xlabel('航速偏差') legend figure plot(CogThre,[ACC_C.r],'-gp','DisPlayName','准确率') hold on plot(CogThre,1-[ACC_C.r],'-rd','DisPlayName','误警率') xlabel('航向偏差') legend %% 2类：进口 1类出口 global DistThre SogThre CogThre DistThre=60; SogThre=2.8; CogThre=3.8; addpath '正常与异常数据' filename_in='验证进口道船舶异常行为.xlsx'; tracetype=input('请选择要验证的船舶类型：1（出口）/ 2（进口）'); try DXTrace=DXfData{tracetype}; catch disp('输入错误') return end checkTrace(filename_in,DXTrace);