欢迎来到海神之光博客之家✅博主简介热爱科研的Matlab仿真开发者修心和技术同步精进个人主页海神之光代码获取方式海神之光Matlab王者学习之路—代码获取方式⛳️座右铭行百里者半于九十。更多Matlab元胞自动机仿真内容点击①Matlab元胞自动机进阶版⛳️关注CSDN海神之光更多资源等你来⛄一、元胞自动机简介1 元胞自动机发展历程最初的元胞自动机是由冯 · 诺依曼在 1950 年代为模拟生物 细胞的自我复制而提出的. 但是并未受到学术界重视.1970 年, 剑桥大学的约翰 · 何顿 · 康威设计了一个电脑游戏 “生命游戏” 后, 元胞自动机才吸引了科学家们的注意.1983 年 S.Wolfram 发表了一系列论文. 对初等元胞机 256 种 规则所产生的模型进行了深入研究, 并用熵来描述其演化行 为, 将细胞自动机分为平稳型, 周期型, 混沌型和复杂型.2 对元胞自动机的初步认识元胞自动机CA是一种用来仿真局部规则和局部联系的方法。典型的元胞自动机是定义在网格上的每一个点上的网格代表一个元胞与一种有限的状态。变化规则适用于每一个元胞并且同时进行。典型的变化规则决定于元胞的状态以及其 4 或 8 邻居的状态。3 元胞的变化规则元胞状态典型的变化规则决定于元胞的状态以及其 4 或 8 邻居的状态。4 元胞自动机的应用元胞自动机已被应用于物理模拟生物模拟等领域。5 元胞自动机的matlab编程结合以上我们可以理解元胞自动机仿真需要理解三点。一是元胞在matlab中可以理解为矩阵中的一点或多点组成的方形块一般我们用矩阵中的一点代表一个元胞。二是变化规则元胞的变化规则决定元胞下一刻的状态。三是元胞的状态元胞的状态是自定义的通常是对立的状态比如生物的存活状态或死亡状态红灯或绿灯该点有障碍物或者没有障碍物等等。6 一维元胞自动机——交通规则定义6.1 元胞分布于一维线性网格上.6.2 元胞仅具有车和空两种状态.7 二维元胞自动机——生命游戏定义7.1 元胞分布于二维方型网格上.7.2 元胞仅具有生和死两种状态.元胞状态由周围八邻居决定.规则骷髅死亡笑脸生存周围有三个笑脸则中间变为笑脸少于两个笑脸或者多于三个中间则变死亡。8 什么是元胞自动机离散的系统: 元胞是定义在有限的时间和空间上的, 并且元 胞的状态是有限.动力学系统: 元胞自动机的举止行为具有动力学特征.简单与复杂: 元胞自动机用简单规则控制相互作用的元胞 模拟复杂世界.9 构成要素1元胞 (Cell)元胞是元胞自动机基本单元状态: 每一个元胞都有记忆贮存状态的功能.离散: 简单情况下, 元胞只有两种可能状态; 较复杂情况下, 元胞具有多种状态.更新: 元胞的状态都安照动力规则不断更新.2网格 (Lattice)不同维网格常用二维网格3邻居 (Neighborhood)4边界 (Boundary)反射型以自己作为边界的状态吸收型不管边界车开到边界就消失5规则状态转移函数定义根据元胞当前状态及其邻居状况确定下一时刻该元胞状态的动力学函数, 简单讲, 就是一个状态转移函数.分类 总和型: 某元胞下时刻的状态取决于且仅取决于它所有邻居 的当前状态以及自身的当前状态.合法型: 总和型规则属于合法型规则. 但如果把元胞自动机 的规则限制为总和型, 会使元胞自动机具有局限性.6森林火灾绿色树木红色火黑色空地。三种状态循环转化树周围有火或者被闪电击中就变成火。空地以概率p变为树木理性分析红为火灰为空地绿是树元胞三种状态的密度和为1火转化为空地的密度等于空地转换为树的密度新长出来的树等于烧没的树f是闪电的概率:远远小于树生成的概率T s m a x T_{smax}T smax是一大群树被火烧的时间尺度程序实现周期性边界条件购进啊其中的数字为编号构建邻居矩阵上面矩阵中的数字编号对应原矩阵相同位置编号的上邻居编号一 一对应同样道理7交通概念车距和密度流量方程守恒方程时空轨迹横轴是空间纵轴为时间红线横线与蓝色交点表示每个时间车的位置。如果是竖线则表示车子在该位置对应的时间宏观连续模型最常用的规则红色条表示速度是满的。1 加速规则不能超过v m a x 2 格 / s v_{max}2格/svmax2格/s2 防止碰撞不能超过车距理论分析结果分析: 密度与流量第一个图横坐标是归一化后的密度纵坐标是车流量。第二个图理论值与CA的结果结果分析: 时空轨迹中间的深色区域是交通堵塞的区域。⛄二、部分源代码function varargout ES(varargin)% ES MATLAB code for ES.fig% ES, by itself, creates a new ES or raises the existing% singleton*.%% H ES returns the handle to a new ES or the handle to% the existing singleton*.%% ES(‘CALLBACK’,hObject,eventData,handles,…) calls the local% function named CALLBACK in ES.M with the given input arguments.%% ES(‘Property’,‘Value’,…) creates a new ES or raises the% existing singleton*. Starting from the left, property value pairs are% applied to the GUI before ES_OpeningFcn gets called. An% unrecognized property name or invalid value makes property application% stop. All inputs are passed to ES_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 ES% Last Modified by GUIDE v2.5 24-Nov-2014 16:51:08% Begin initialization code - DO NOT EDITgui_Singleton 1;gui_State struct(‘gui_Name’, mfilename, …‘gui_Singleton’, gui_Singleton, …‘gui_OpeningFcn’, ES_OpeningFcn, …‘gui_OutputFcn’, ES_OutputFcn, …‘gui_LayoutFcn’, [] , …‘gui_Callback’, []);if nargin ischar(varargin{1})gui_State.gui_Callback str2func(varargin{1});endif nargout[varargout{1:nargout}] gui_mainfcn(gui_State, varargin{:});elsegui_mainfcn(gui_State, varargin{:});end% End initialization code - DO NOT EDIT% — Executes just before ES is made visible.function ES_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 ES (see VARARGIN)% Choose default command line output for EShandles.output hObject;handles.Img 0;handles.ParentImg 0;handles.OffspringImg 0;handles.Parent cell(1, 8);handles.Parent{1} zeros(1, 3); % Birthhandles.Parent{2} zeros(1, 3); % Levelhandles.Parent{3} zeros(1, 3); % number of Pattern Poshandles.Parent{4} cell(1, 3); % PosHhandles.Parent{5} cell(1, 3); % PosWhandles.Parent{6} zeros(1, 3); % Cell Generationhandles.Parent{7} cell(1, 3); % Patternhandles.Offspring cell(1, 8);handles.Offspring{1} zeros(1, 3); % Birthhandles.Offspring{2} zeros(1, 3); % Levelhandles.Offspring{3} zeros(1, 3); % number of Pattern Poshandles.Offspring{4} cell(1, 3); % PosHhandles.Offspring{5} cell(1, 3); % PosWhandles.Offspring{6} zeros(1, 3); % Cell Generationhandles.Offspring{7} cell(1, 3); % Patternhandles.Boundary cell(1, 7); % Birth, Level, # of CellBlocks, MinCAG, MaxCAG, Image Sizehandles.GenerationCount 0;if exist(‘iES’, ‘dir’) ~ 7mkdir(‘iES’);end% Update handles structureguidata(hObject, handles);% UIWAIT makes ES wait for user response (see UIRESUME)% uiwait(handles.figure1);% — Outputs from this function are returned to the command line.function varargout ES_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 structurevarargout{1} handles.output;function BirthVal_Callback(hObject, eventdata, handles)% hObject handle to BirthVal (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 BirthVal as text% str2double(get(hObject,‘String’)) returns contents of BirthVal as a double% — Executes during object creation, after setting all properties.function BirthVal_CreateFcn(hObject, eventdata, handles)% hObject handle to BirthVal (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’);endfunction LevelVal_Callback(hObject, eventdata, handles)% hObject handle to LevelVal (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 LevelVal as text% str2double(get(hObject,‘String’)) returns contents of LevelVal as a double% — Executes during object creation, after setting all properties.function LevelVal_CreateFcn(hObject, eventdata, handles)% hObject handle to LevelVal (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’);endfunction CellBlocksVal_Callback(hObject, eventdata, handles)% hObject handle to CellBlocksVal (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 CellBlocksVal as text% str2double(get(hObject,‘String’)) returns contents of CellBlocksVal as a double% — Executes during object creation, after setting all properties.function CellBlocksVal_CreateFcn(hObject, eventdata, handles)% hObject handle to CellBlocksVal (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’);endfunction MinCAGVal_Callback(hObject, eventdata, handles)% hObject handle to MinCAGVal (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 MinCAGVal as text% str2double(get(hObject,‘String’)) returns contents of MinCAGVal as a double% — Executes during object creation, after setting all properties.function MinCAGVal_CreateFcn(hObject, eventdata, handles)% hObject handle to MinCAGVal (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’);endfunction MaxCAGVal_Callback(hObject, eventdata, handles)% hObject handle to MaxCAGVal (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 MaxCAGVal as text% str2double(get(hObject,‘String’)) returns contents of MaxCAGVal as a double% — Executes during object creation, after setting all properties.function MaxCAGVal_CreateFcn(hObject, eventdata, handles)% hObject handle to MaxCAGVal (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 ImgRead.function ImgRead_Callback(hObject, eventdata, handles)% hObject handle to ImgRead (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)% [filename, user_canceled] imgetfile;% if user_canceled% return;% endfilename ‘lenna.png’;Img imread(filename);handles.Img Img;axes(handles.Original);image(double(handles.Img)/255);guidata(hObject, handles);% — Executes on button press in Sellambda.function Sellambda_Callback(hObject, eventdata, handles)% hObject handle to Sellambda (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)imwrite(handles.ParentImg, [‘iEA/G’, num2str(handles.GenerationCount), ‘.jpg’]);[handles.Offspring, cc] Mutation(handles.Parent, handles.Boundary);guidata(hObject, handles);offspring handles.ParentImg;[offspring(:, :, cc), ta, tb, tc, td, te] GUILogicRule(handles.Img, cc, handles.Offspring{1}(cc), handles.Offspring{2}(cc), handles.Offspring{3}(cc), handles.Offspring{6}(cc), 1, handles.Offspring{4}{cc}, handles.Offspring{5}{cc}, handles.Offspring{7}{cc});axes(handles.mu);image(offspring);handles.GenerationCount handles.GenerationCount 1;handles.OffspringImg offspring;guidata(hObject, handles);set(handles.Generation, ‘string’, strcat(Generation: , num2str(handles.GenerationCount)));% — Executes on button press in Selmu.function Selmu_Callback(hObject, eventdata, handles)% hObject handle to Selmu (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)imwrite(handles.OffspringImg, [‘iEA/G’, num2str(handles.GenerationCount), ‘.jpg’]);[handles.Parent, cc] Mutation(handles.Offspring, handles.Boundary);guidata(hObject, handles);Parent handles.OffspringImg;[Parent(:, :, cc), ta, tb, tc, td, te] GUILogicRule(handles.Img, cc, handles.Parent{1}(cc), handles.Parent{2}(cc), handles.Parent{3}(cc), handles.Parent{6}(cc), 1, handles.Parent{4}{cc}, handles.Parent{5}{cc}, handles.Parent{7}{cc});axes(handles.lambda);image(Parent);handles.GenerationCount handles.GenerationCount 1;handles.ParentImg Parent;guidata(hObject, handles);set(handles.Generation, ‘string’, strcat(Generation: , num2str(handles.GenerationCount)));% — Executes on button press in Start.function Start_Callback(hObject, eventdata, handles)% hObject handle to Start (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)handles.GenerationCount 1;Parent zeros(size(handles.Img));Sz size(handles.Img);Birth str2double(get(handles.BirthVal, ‘string’));Level str2double(get(handles.LevelVal, ‘string’));NumCellBlocks str2double(get(handles.CellBlocksVal, ‘string’));MinCAG str2double(get(handles.MinCAGVal, ‘string’));MaxCAG str2double(get(handles.MaxCAGVal, ‘string’));for cc1:3CellGen randi([MinCAG, MaxCAG]);PosH randi([1, Sz(1)], 1, NumCellBlocks);PosW randi([1, Sz(2)], 1, NumCellBlocks);[Parent(:, :, cc), handles.Parent{6}(cc), handles.Parent{1}(cc), handles.Parent{2}(cc), handles.Parent{3}(cc), handles.Parent{7}{cc}] GUILogicRule(handles.Img, cc, Birth, Level, NumCellBlocks, CellGen, 0, PosH, PosW, 0);handles.Parent{4}{cc} PosH;handles.Parent{5}{cc} PosW;guidata(hObject, handles);endhandles.Boundary{1} Birth;handles.Boundary{2} Level;handles.Boundary{3} NumCellBlocks;handles.Boundary{4} MinCAG;handles.Boundary{5} MaxCAG;handles.Boundary{6} Sz(1);handles.Boundary{7} Sz(2);guidata(hObject, handles);handles.Offspring Mutation(handles.Parent, handles.Boundary);guidata(hObject, handles);offspring zeros(Sz);for cc1:3[offspring(:, :, cc), ta, tb, tc, td, te] GUILogicRule(handles.Img, cc, handles.Offspring{1}(cc), handles.Offspring{2}(cc), handles.Offspring{3}(cc), handles.Offspring{6}(cc), 1, handles.Offspring{4}{cc}, handles.Offspring{5}{cc}, handles.Offspring{7}{cc});endhandles.ParentImg Parent;handles.OffspringImg offspring;guidata(hObject, handles);axes(handles.lambda);image(Parent);axes(handles.mu);image(offspring);set(handles.Generation, ‘string’, strcat(Generation: , num2str(handles.GenerationCount)));⛄三、运行结果⛄四、matlab版本及参考文献1 matlab版本2014a2 参考文献[1]党珊,蒋太刚,巫承军.基于元胞自动机方法的消防疏散仿真研究[J].现代电子技术. 2022,45(21)[2]帅斌,秦梦瑶,许旻昊.基于元胞自动机的高速铁路列车运行仿真研究[J].计算机仿真. 2022,39(08)[3]张睿洋.元胞自动机在两类传染病模型中的应用[J].现代信息科技. 2022,6(10)3 备注简介此部分摘自互联网仅供参考若侵权请联系删除 仿真咨询1 各类智能优化算法改进及应用生产调度、经济调度、装配线调度、充电优化、车间调度、发车优化、水库调度、三维装箱、物流选址、货位优化、公交排班优化、充电桩布局优化、车间布局优化、集装箱船配载优化、水泵组合优化、解医疗资源分配优化、设施布局优化、可视域基站和无人机选址优化2 机器学习和深度学习方面卷积神经网络CNN、LSTM、支持向量机SVM、最小二乘支持向量机LSSVM、极限学习机ELM、核极限学习机KELM、BP、RBF、宽度学习、DBN、RF、RBF、DELM、XGBOOST、TCN实现风电预测、光伏预测、电池寿命预测、辐射源识别、交通流预测、负荷预测、股价预测、PM2.5浓度预测、电池健康状态预测、水体光学参数反演、NLOS信号识别、地铁停车精准预测、变压器故障诊断3 图像处理方面图像识别、图像分割、图像检测、图像隐藏、图像配准、图像拼接、图像融合、图像增强、图像压缩感知4 路径规划方面旅行商问题TSP、车辆路径问题VRP、MVRP、CVRP、VRPTW等、无人机三维路径规划、无人机协同、无人机编队、机器人路径规划、栅格地图路径规划、多式联运运输问题、车辆协同无人机路径规划、天线线性阵列分布优化、车间布局优化5 无人机应用方面无人机路径规划、无人机控制、无人机编队、无人机协同、无人机任务分配6 无线传感器定位及布局方面传感器部署优化、通信协议优化、路由优化、目标定位优化、Dv-Hop定位优化、Leach协议优化、WSN覆盖优化、组播优化、RSSI定位优化7 信号处理方面信号识别、信号加密、信号去噪、信号增强、雷达信号处理、信号水印嵌入提取、肌电信号、脑电信号、信号配时优化8 电力系统方面微电网优化、无功优化、配电网重构、储能配置9 元胞自动机方面交通流 人群疏散 病毒扩散 晶体生长10 雷达方面卡尔曼滤波跟踪、航迹关联、航迹融合
欢迎来到海神之光博客之家✅博主简介热爱科研的Matlab仿真开发者修心和技术同步精进个人主页海神之光代码获取方式海神之光Matlab王者学习之路—代码获取方式⛳️座右铭行百里者半于九十。更多Matlab元胞自动机仿真内容点击①Matlab元胞自动机进阶版⛳️关注CSDN海神之光更多资源等你来⛄一、元胞自动机简介1 元胞自动机发展历程最初的元胞自动机是由冯 · 诺依曼在 1950 年代为模拟生物 细胞的自我复制而提出的. 但是并未受到学术界重视.1970 年, 剑桥大学的约翰 · 何顿 · 康威设计了一个电脑游戏 “生命游戏” 后, 元胞自动机才吸引了科学家们的注意.1983 年 S.Wolfram 发表了一系列论文. 对初等元胞机 256 种 规则所产生的模型进行了深入研究, 并用熵来描述其演化行 为, 将细胞自动机分为平稳型, 周期型, 混沌型和复杂型.2 对元胞自动机的初步认识元胞自动机CA是一种用来仿真局部规则和局部联系的方法。典型的元胞自动机是定义在网格上的每一个点上的网格代表一个元胞与一种有限的状态。变化规则适用于每一个元胞并且同时进行。典型的变化规则决定于元胞的状态以及其 4 或 8 邻居的状态。3 元胞的变化规则元胞状态典型的变化规则决定于元胞的状态以及其 4 或 8 邻居的状态。4 元胞自动机的应用元胞自动机已被应用于物理模拟生物模拟等领域。5 元胞自动机的matlab编程结合以上我们可以理解元胞自动机仿真需要理解三点。一是元胞在matlab中可以理解为矩阵中的一点或多点组成的方形块一般我们用矩阵中的一点代表一个元胞。二是变化规则元胞的变化规则决定元胞下一刻的状态。三是元胞的状态元胞的状态是自定义的通常是对立的状态比如生物的存活状态或死亡状态红灯或绿灯该点有障碍物或者没有障碍物等等。6 一维元胞自动机——交通规则定义6.1 元胞分布于一维线性网格上.6.2 元胞仅具有车和空两种状态.7 二维元胞自动机——生命游戏定义7.1 元胞分布于二维方型网格上.7.2 元胞仅具有生和死两种状态.元胞状态由周围八邻居决定.规则骷髅死亡笑脸生存周围有三个笑脸则中间变为笑脸少于两个笑脸或者多于三个中间则变死亡。8 什么是元胞自动机离散的系统: 元胞是定义在有限的时间和空间上的, 并且元 胞的状态是有限.动力学系统: 元胞自动机的举止行为具有动力学特征.简单与复杂: 元胞自动机用简单规则控制相互作用的元胞 模拟复杂世界.9 构成要素1元胞 (Cell)元胞是元胞自动机基本单元状态: 每一个元胞都有记忆贮存状态的功能.离散: 简单情况下, 元胞只有两种可能状态; 较复杂情况下, 元胞具有多种状态.更新: 元胞的状态都安照动力规则不断更新.2网格 (Lattice)不同维网格常用二维网格3邻居 (Neighborhood)4边界 (Boundary)反射型以自己作为边界的状态吸收型不管边界车开到边界就消失5规则状态转移函数定义根据元胞当前状态及其邻居状况确定下一时刻该元胞状态的动力学函数, 简单讲, 就是一个状态转移函数.分类 总和型: 某元胞下时刻的状态取决于且仅取决于它所有邻居 的当前状态以及自身的当前状态.合法型: 总和型规则属于合法型规则. 但如果把元胞自动机 的规则限制为总和型, 会使元胞自动机具有局限性.6森林火灾绿色树木红色火黑色空地。三种状态循环转化树周围有火或者被闪电击中就变成火。空地以概率p变为树木理性分析红为火灰为空地绿是树元胞三种状态的密度和为1火转化为空地的密度等于空地转换为树的密度新长出来的树等于烧没的树f是闪电的概率:远远小于树生成的概率T s m a x T_{smax}T smax是一大群树被火烧的时间尺度程序实现周期性边界条件购进啊其中的数字为编号构建邻居矩阵上面矩阵中的数字编号对应原矩阵相同位置编号的上邻居编号一 一对应同样道理7交通概念车距和密度流量方程守恒方程时空轨迹横轴是空间纵轴为时间红线横线与蓝色交点表示每个时间车的位置。如果是竖线则表示车子在该位置对应的时间宏观连续模型最常用的规则红色条表示速度是满的。1 加速规则不能超过v m a x 2 格 / s v_{max}2格/svmax2格/s2 防止碰撞不能超过车距理论分析结果分析: 密度与流量第一个图横坐标是归一化后的密度纵坐标是车流量。第二个图理论值与CA的结果结果分析: 时空轨迹中间的深色区域是交通堵塞的区域。⛄二、部分源代码function varargout ES(varargin)% ES MATLAB code for ES.fig% ES, by itself, creates a new ES or raises the existing% singleton*.%% H ES returns the handle to a new ES or the handle to% the existing singleton*.%% ES(‘CALLBACK’,hObject,eventData,handles,…) calls the local% function named CALLBACK in ES.M with the given input arguments.%% ES(‘Property’,‘Value’,…) creates a new ES or raises the% existing singleton*. Starting from the left, property value pairs are% applied to the GUI before ES_OpeningFcn gets called. An% unrecognized property name or invalid value makes property application% stop. All inputs are passed to ES_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 ES% Last Modified by GUIDE v2.5 24-Nov-2014 16:51:08% Begin initialization code - DO NOT EDITgui_Singleton 1;gui_State struct(‘gui_Name’, mfilename, …‘gui_Singleton’, gui_Singleton, …‘gui_OpeningFcn’, ES_OpeningFcn, …‘gui_OutputFcn’, ES_OutputFcn, …‘gui_LayoutFcn’, [] , …‘gui_Callback’, []);if nargin ischar(varargin{1})gui_State.gui_Callback str2func(varargin{1});endif nargout[varargout{1:nargout}] gui_mainfcn(gui_State, varargin{:});elsegui_mainfcn(gui_State, varargin{:});end% End initialization code - DO NOT EDIT% — Executes just before ES is made visible.function ES_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 ES (see VARARGIN)% Choose default command line output for EShandles.output hObject;handles.Img 0;handles.ParentImg 0;handles.OffspringImg 0;handles.Parent cell(1, 8);handles.Parent{1} zeros(1, 3); % Birthhandles.Parent{2} zeros(1, 3); % Levelhandles.Parent{3} zeros(1, 3); % number of Pattern Poshandles.Parent{4} cell(1, 3); % PosHhandles.Parent{5} cell(1, 3); % PosWhandles.Parent{6} zeros(1, 3); % Cell Generationhandles.Parent{7} cell(1, 3); % Patternhandles.Offspring cell(1, 8);handles.Offspring{1} zeros(1, 3); % Birthhandles.Offspring{2} zeros(1, 3); % Levelhandles.Offspring{3} zeros(1, 3); % number of Pattern Poshandles.Offspring{4} cell(1, 3); % PosHhandles.Offspring{5} cell(1, 3); % PosWhandles.Offspring{6} zeros(1, 3); % Cell Generationhandles.Offspring{7} cell(1, 3); % Patternhandles.Boundary cell(1, 7); % Birth, Level, # of CellBlocks, MinCAG, MaxCAG, Image Sizehandles.GenerationCount 0;if exist(‘iES’, ‘dir’) ~ 7mkdir(‘iES’);end% Update handles structureguidata(hObject, handles);% UIWAIT makes ES wait for user response (see UIRESUME)% uiwait(handles.figure1);% — Outputs from this function are returned to the command line.function varargout ES_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 structurevarargout{1} handles.output;function BirthVal_Callback(hObject, eventdata, handles)% hObject handle to BirthVal (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 BirthVal as text% str2double(get(hObject,‘String’)) returns contents of BirthVal as a double% — Executes during object creation, after setting all properties.function BirthVal_CreateFcn(hObject, eventdata, handles)% hObject handle to BirthVal (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’);endfunction LevelVal_Callback(hObject, eventdata, handles)% hObject handle to LevelVal (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 LevelVal as text% str2double(get(hObject,‘String’)) returns contents of LevelVal as a double% — Executes during object creation, after setting all properties.function LevelVal_CreateFcn(hObject, eventdata, handles)% hObject handle to LevelVal (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’);endfunction CellBlocksVal_Callback(hObject, eventdata, handles)% hObject handle to CellBlocksVal (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 CellBlocksVal as text% str2double(get(hObject,‘String’)) returns contents of CellBlocksVal as a double% — Executes during object creation, after setting all properties.function CellBlocksVal_CreateFcn(hObject, eventdata, handles)% hObject handle to CellBlocksVal (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’);endfunction MinCAGVal_Callback(hObject, eventdata, handles)% hObject handle to MinCAGVal (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 MinCAGVal as text% str2double(get(hObject,‘String’)) returns contents of MinCAGVal as a double% — Executes during object creation, after setting all properties.function MinCAGVal_CreateFcn(hObject, eventdata, handles)% hObject handle to MinCAGVal (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’);endfunction MaxCAGVal_Callback(hObject, eventdata, handles)% hObject handle to MaxCAGVal (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 MaxCAGVal as text% str2double(get(hObject,‘String’)) returns contents of MaxCAGVal as a double% — Executes during object creation, after setting all properties.function MaxCAGVal_CreateFcn(hObject, eventdata, handles)% hObject handle to MaxCAGVal (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 ImgRead.function ImgRead_Callback(hObject, eventdata, handles)% hObject handle to ImgRead (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)% [filename, user_canceled] imgetfile;% if user_canceled% return;% endfilename ‘lenna.png’;Img imread(filename);handles.Img Img;axes(handles.Original);image(double(handles.Img)/255);guidata(hObject, handles);% — Executes on button press in Sellambda.function Sellambda_Callback(hObject, eventdata, handles)% hObject handle to Sellambda (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)imwrite(handles.ParentImg, [‘iEA/G’, num2str(handles.GenerationCount), ‘.jpg’]);[handles.Offspring, cc] Mutation(handles.Parent, handles.Boundary);guidata(hObject, handles);offspring handles.ParentImg;[offspring(:, :, cc), ta, tb, tc, td, te] GUILogicRule(handles.Img, cc, handles.Offspring{1}(cc), handles.Offspring{2}(cc), handles.Offspring{3}(cc), handles.Offspring{6}(cc), 1, handles.Offspring{4}{cc}, handles.Offspring{5}{cc}, handles.Offspring{7}{cc});axes(handles.mu);image(offspring);handles.GenerationCount handles.GenerationCount 1;handles.OffspringImg offspring;guidata(hObject, handles);set(handles.Generation, ‘string’, strcat(Generation: , num2str(handles.GenerationCount)));% — Executes on button press in Selmu.function Selmu_Callback(hObject, eventdata, handles)% hObject handle to Selmu (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)imwrite(handles.OffspringImg, [‘iEA/G’, num2str(handles.GenerationCount), ‘.jpg’]);[handles.Parent, cc] Mutation(handles.Offspring, handles.Boundary);guidata(hObject, handles);Parent handles.OffspringImg;[Parent(:, :, cc), ta, tb, tc, td, te] GUILogicRule(handles.Img, cc, handles.Parent{1}(cc), handles.Parent{2}(cc), handles.Parent{3}(cc), handles.Parent{6}(cc), 1, handles.Parent{4}{cc}, handles.Parent{5}{cc}, handles.Parent{7}{cc});axes(handles.lambda);image(Parent);handles.GenerationCount handles.GenerationCount 1;handles.ParentImg Parent;guidata(hObject, handles);set(handles.Generation, ‘string’, strcat(Generation: , num2str(handles.GenerationCount)));% — Executes on button press in Start.function Start_Callback(hObject, eventdata, handles)% hObject handle to Start (see GCBO)% eventdata reserved - to be defined in a future version of MATLAB% handles structure with handles and user data (see GUIDATA)handles.GenerationCount 1;Parent zeros(size(handles.Img));Sz size(handles.Img);Birth str2double(get(handles.BirthVal, ‘string’));Level str2double(get(handles.LevelVal, ‘string’));NumCellBlocks str2double(get(handles.CellBlocksVal, ‘string’));MinCAG str2double(get(handles.MinCAGVal, ‘string’));MaxCAG str2double(get(handles.MaxCAGVal, ‘string’));for cc1:3CellGen randi([MinCAG, MaxCAG]);PosH randi([1, Sz(1)], 1, NumCellBlocks);PosW randi([1, Sz(2)], 1, NumCellBlocks);[Parent(:, :, cc), handles.Parent{6}(cc), handles.Parent{1}(cc), handles.Parent{2}(cc), handles.Parent{3}(cc), handles.Parent{7}{cc}] GUILogicRule(handles.Img, cc, Birth, Level, NumCellBlocks, CellGen, 0, PosH, PosW, 0);handles.Parent{4}{cc} PosH;handles.Parent{5}{cc} PosW;guidata(hObject, handles);endhandles.Boundary{1} Birth;handles.Boundary{2} Level;handles.Boundary{3} NumCellBlocks;handles.Boundary{4} MinCAG;handles.Boundary{5} MaxCAG;handles.Boundary{6} Sz(1);handles.Boundary{7} Sz(2);guidata(hObject, handles);handles.Offspring Mutation(handles.Parent, handles.Boundary);guidata(hObject, handles);offspring zeros(Sz);for cc1:3[offspring(:, :, cc), ta, tb, tc, td, te] GUILogicRule(handles.Img, cc, handles.Offspring{1}(cc), handles.Offspring{2}(cc), handles.Offspring{3}(cc), handles.Offspring{6}(cc), 1, handles.Offspring{4}{cc}, handles.Offspring{5}{cc}, handles.Offspring{7}{cc});endhandles.ParentImg Parent;handles.OffspringImg offspring;guidata(hObject, handles);axes(handles.lambda);image(Parent);axes(handles.mu);image(offspring);set(handles.Generation, ‘string’, strcat(Generation: , num2str(handles.GenerationCount)));⛄三、运行结果⛄四、matlab版本及参考文献1 matlab版本2014a2 参考文献[1]党珊,蒋太刚,巫承军.基于元胞自动机方法的消防疏散仿真研究[J].现代电子技术. 2022,45(21)[2]帅斌,秦梦瑶,许旻昊.基于元胞自动机的高速铁路列车运行仿真研究[J].计算机仿真. 2022,39(08)[3]张睿洋.元胞自动机在两类传染病模型中的应用[J].现代信息科技. 2022,6(10)3 备注简介此部分摘自互联网仅供参考若侵权请联系删除 仿真咨询1 各类智能优化算法改进及应用生产调度、经济调度、装配线调度、充电优化、车间调度、发车优化、水库调度、三维装箱、物流选址、货位优化、公交排班优化、充电桩布局优化、车间布局优化、集装箱船配载优化、水泵组合优化、解医疗资源分配优化、设施布局优化、可视域基站和无人机选址优化2 机器学习和深度学习方面卷积神经网络CNN、LSTM、支持向量机SVM、最小二乘支持向量机LSSVM、极限学习机ELM、核极限学习机KELM、BP、RBF、宽度学习、DBN、RF、RBF、DELM、XGBOOST、TCN实现风电预测、光伏预测、电池寿命预测、辐射源识别、交通流预测、负荷预测、股价预测、PM2.5浓度预测、电池健康状态预测、水体光学参数反演、NLOS信号识别、地铁停车精准预测、变压器故障诊断3 图像处理方面图像识别、图像分割、图像检测、图像隐藏、图像配准、图像拼接、图像融合、图像增强、图像压缩感知4 路径规划方面旅行商问题TSP、车辆路径问题VRP、MVRP、CVRP、VRPTW等、无人机三维路径规划、无人机协同、无人机编队、机器人路径规划、栅格地图路径规划、多式联运运输问题、车辆协同无人机路径规划、天线线性阵列分布优化、车间布局优化5 无人机应用方面无人机路径规划、无人机控制、无人机编队、无人机协同、无人机任务分配6 无线传感器定位及布局方面传感器部署优化、通信协议优化、路由优化、目标定位优化、Dv-Hop定位优化、Leach协议优化、WSN覆盖优化、组播优化、RSSI定位优化7 信号处理方面信号识别、信号加密、信号去噪、信号增强、雷达信号处理、信号水印嵌入提取、肌电信号、脑电信号、信号配时优化8 电力系统方面微电网优化、无功优化、配电网重构、储能配置9 元胞自动机方面交通流 人群疏散 病毒扩散 晶体生长10 雷达方面卡尔曼滤波跟踪、航迹关联、航迹融合
