1 模型
2 部分代码
%-------------------------------------------------------------------------%% Binary Dragonfly Algorithm (BDA) source codes demo version % %%-------------------------------------------------------------------------%%---Inputs-----------------------------------------------------------------% feat: features% label: labelling% N: Number of dragonflies% T: Maximum number of iterations% Dmax: Maximum velocity% *Note: k-value of KNN & hold-out setting can be modified in jFitnessFunction.m%---Outputs----------------------------------------------------------------% sFeat: Selected features% Sf: Selected feature index% Nf: Number of selected features% curve: Convergence curve%--------------------------------------------------------------------------%% Binary Dragonfly Algorithmclc, clear, close; % Benchmark data set load ionosphere.mat; % Parameter settingN=10;T=100; Dmax=6;% Binary Dragonfly Algorithm[sFeat,Sf,Nf,curve]=jBDA(feat,label,N,T,Dmax);% Plot convergence curvefigure(); plot(1:T,curve); xlabel('Number of iterations');ylabel('Fitness Value'); title('BDA'); grid on;
3 仿真结果
4 参考文献
[1]董海, 徐德珉. 基于蜻蜓算法和最小二乘向量机的小批量生产质量预测[J]. 科技管理研究, 2019, 000(022):256-260.
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