运动学基于改进的遗传算法和高斯烟羽模型模拟气体扩散

Posted 2021-06-30 博主QQ2449341593

一、简介

1 高斯羽烟模型方程

式中c为污染物浓度(单位：kg/m3)
Q为源强(单位：kg/s)
u为泄漏高度的平均风速(单位：m/s)
y、z分别用浓度标准偏差表示的y轴及z轴上的扩散参数
H为泄漏有效高度(单位：m)

2 扩散系数系数

二、源代码

function varargout = mGA_new(varargin)
% MGA_NEW MATLAB code for mGA_new.fig
%      MGA_NEW, by itself, creates a new MGA_NEW or raises the existing
%      singleton*.
%
%      H = MGA_NEW returns the handle to a new MGA_NEW or the handle to
%      the existing singleton*.
%
%      MGA_NEW('CALLBACK',hObject,eventData,handles,...) calls the local
%      function named CALLBACK in MGA_NEW.M with the given input arguments.
%
%      MGA_NEW('Property','Value',...) creates a new MGA_NEW or raises the
%      existing singleton*.  Starting from the left, property value pairs are
%      applied to the GUI before mGA_new_OpeningFcn gets called.  An
%      unrecognized property name or invalid value makes property application
%      stop.  All inputs are passed to mGA_new_OpeningFcn via varargin.
%
%      *See GUI Options on GUIDE's Tools menu.  Choose "GUI allows only one
%      instance to run (singleton)".
%
% See also: GUIDE, GUIDATA, GUIHANDLES

% Edit the above text to modify the response to help mGA_new

% Last Modified by GUIDE v2.5 04-Jul-2020 16:21:23

% Begin initialization code - DO NOT EDIT
gui_Singleton = 1;
gui_State = struct('gui_Name',       mfilename, ...
                   'gui_Singleton',  gui_Singleton, ...
                   'gui_OpeningFcn', @mGA_new_OpeningFcn, ...
                   'gui_OutputFcn',  @mGA_new_OutputFcn, ...
                   'gui_LayoutFcn',  [] , ...
                   'gui_Callback',   []);
if nargin && ischar(varargin{1})
    gui_State.gui_Callback = str2func(varargin{1});
end

if nargout
    [varargout{1:nargout}] = gui_mainfcn(gui_State, varargin{:});
else
    gui_mainfcn(gui_State, varargin{:});
end
% End initialization code - DO NOT EDIT


% --- Executes just before mGA_new is made visible.
function mGA_new_OpeningFcn(hObject, eventdata, handles, varargin)
% This function has no output args, see OutputFcn.
% hObject    handle to figure
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)
% varargin   command line arguments to mGA_new (see VARARGIN)

% Choose default command line output for mGA_new
handles.output = hObject;

% Update handles structure
guidata(hObject, handles);

% UIWAIT makes mGA_new wait for user response (see UIRESUME)
% uiwait(handles.figure1);


% --- Outputs from this function are returned to the command line.
function varargout = mGA_new_OutputFcn(hObject, eventdata, handles) 
% varargout  cell array for returning output args (see VARARGOUT);
% hObject    handle to figure
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)

% Get default command line output from handles structure
varargout{1} = handles.output;


% --- Executes on selection change in popupmenu1.
function popupmenu1_Callback(hObject, eventdata, handles)
% hObject    handle to popupmenu1 (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)

% Hints: contents = cellstr(get(hObject,'String')) returns popupmenu1 contents as cell array
%        contents{get(hObject,'Value')} returns selected item from popupmenu1


% --- Executes during object creation, after setting all properties.
function popupmenu1_CreateFcn(hObject, eventdata, handles)
% hObject    handle to popupmenu1 (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    empty - handles not created until after all CreateFcns called

% Hint: popupmenu controls usually have a white background on Windows.
%       See ISPC and COMPUTER.
if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))
    set(hObject,'BackgroundColor','white');
end



function feng_Callback(hObject, eventdata, handles)
% hObject    handle to feng (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)

% Hints: get(hObject,'String') returns contents of feng as text
%        str2double(get(hObject,'String')) returns contents of feng as a double


% --- Executes during object creation, after setting all properties.
function feng_CreateFcn(hObject, eventdata, handles)
% hObject    handle to feng (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    empty - handles not created until after all CreateFcns called

% Hint: edit controls usually have a white background on Windows.
%       See ISPC and COMPUTER.
if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))
    set(hObject,'BackgroundColor','white');
end



function gaodu_Callback(hObject, eventdata, handles)
% hObject    handle to gaodu (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)

% Hints: get(hObject,'String') returns contents of gaodu as text
%        str2double(get(hObject,'String')) returns contents of gaodu as a double


% --- Executes during object creation, after setting all properties.
function gaodu_CreateFcn(hObject, eventdata, handles)
% hObject    handle to gaodu (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    empty - handles not created until after all CreateFcns called

% Hint: edit controls usually have a white background on Windows.
%       See ISPC and COMPUTER.
if ispc && isequal(get(hObject,'BackgroundColor'), get(0,'defaultUicontrolBackgroundColor'))
    set(hObject,'BackgroundColor','white');
end


% --- Executes on button press in jiancedian.
function jiancedian_Callback(hObject, eventdata, handles)
% hObject    handle to jiancedian (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)
[filename,pathname]=uigetfile({'*xls;*.xlsx'},'读入测量数据文件');%加载路径的选择
fpath=[pathname,filename];%总的路径
data=xlsread(fpath);%读测量文件
set(handles.guance,'data',data);%写入到表中
setappdata(handles.jiancedian,'data',data);





% --- Executes on button press in fansuan.
function fansuan_Callback(hObject, eventdata, handles)
% hObject    handle to fansuan (see GCBO)
% eventdata  reserved - to be defined in a future version of MATLAB
% handles    structure with handles and user data (see GUIDATA)
 %% 获取参数
% diedai=str2double(get(handles.deidai,'String'));% 进化次数
val=get(handles.popupmenu1,'value'); %这是获取当前选项的位置，从上到下是1,2,3...
str=get(handles.popupmenu1,'string');
W=str{val}; %这个将返回当前选项的内容，若是纯数字用str2num(str(val))
popsize=100; %种群规模  
lenchrom=3;%变量字串长度
maxgen=str2double(get(handles.diedai,'String'));% 进化次数
% maxgen=1000;% 进化次数
popmax=500;% 种群最大值
popmin=-500;% 种群最小值
u1=str2double(get(handles.feng,'String'));
hr=str2double(get(handles.gaodu,'String'));
% % z1=str2double(get(handles.edit3,'String'));
% z1=0;
% Q=str2double(get(handles.edit8,'String'));
dt=getappdata(handles.jiancedian,'data');
d=dt(:,:);
% mGA.data(:,1)=dt(:,2);
% mGA.data(:,2)=dt(:,3);
% % z1=dt(:,3);
% % set(handles.uitable2,'data',data);
%% 开始
bound=[0 20000;popmin popmax;popmin popmax];  %变量范围
for i=1:popsize
    %随机产生一个种群
    GApop(i,:)=Code(lenchrom,bound);       %随机产生个体
%     GApop(i,:)=mGA.data(i,:);  
    %计算适应度
    fitvalue(i)=fitness(GApop(i,:),u1,hr,d,W);            %染色体的适应度
end
% set(handles.uitable2,'data',fitvalue);
%% 找最好的染色体
[bestfitness,bestindex]=min(fitvalue);
xm=GApop(bestindex,:);   %全局最佳
gbest=GApop;                %体最佳
fitnessgbest=fitvalue;       %个体最佳适应度值
xv=bestfitness;   %全局最佳适应度值
% % set(handles.uitable2,'data',xv);
%% 迭代寻优
for i=1:maxgen
        %种群更新 GA选择更新
        GApop=Select(GApop,fitvalue,popsize); % 其中Select为选择算子函数

        % 交叉操作 GA
        pc=i/maxgen; % maxgen  进化次数  
        GApop=Cross(pc,lenchrom,GApop,popsize,bound); % 其中Cross为交叉算子函数

        % 变异操作 GA变异
        pm=i/maxgen;
        GApop=Mutation(pm,lenchrom,GApop,popsize,[i maxgen],bound);

        pop=GApop;
        
      for j=1:popsize
        %适应度值即变量约束条件
        if 1*pop(j,1)+0*pop(j,2)+0*pop(j,3)<=20000 && 1*pop(j,1)+0*pop(j,2)+0*pop(j,3)>=0
            if 0*pop(j,1)+1*pop(j,2)+0*pop(j,3)<=500 && 0*pop(j,1)+1*pop(j,2)+0*pop(j,3)>=-500
               if 0*pop(j,1)+0*pop(j,2)+1*pop(j,3)<=500 && 0*pop(j,1)+0*pop(j,2)+1*pop(j,3)>=-500
                    fitvalue(j)=fitness(pop(j,:),u1,hr,d,W);
               end
            end 
        end             
        %个体最优更新
        if fitvalue(j) < fitnessgbest(j)
            gbest(j,:) = pop(j,:);
            fitnessgbest(j) = fitvalue(j);
        end
        
        %群体最优更新
        if fitvalue(j) < xv
            xm = pop(j,:);
            xv = fitvalue(j);
        end
      end
       QQ(i)=xm(:,1);
       x(i)=xm(:,2);
       y(i)=xm(:,3);
       v(i)=xv;
end

三、运行结果

四、备注

代码下载https://www.cnblogs.com/matlabxiao/p/14883637.html