1,改進BP神經網絡在股市預測中的應用.2,基于MATLAB工具箱的開采煤層自燃危險性預測.3,基于改進的神經網絡的電力系統負荷預報.4,基于神經網絡的灌溉用水量預測.5,基于遺傳算法改進BP網絡的地表沉陷預計.6,利用遺傳算法改進BP學習算法.7,模糊神經網絡在電力市場短期負荷預測中的應用.8,神經網絡學習算法存在的問題及對策.9,遺傳神經網絡在電力系統短期負荷預測中的應用.10,應用改進BP神經網絡進行用水量預測.11,用遺傳算法改進的BP模型在剎車系統診斷中的應用研究.12,遺傳算法改進的BP神經網絡對汛期三門峽水庫泥沙沖淤量的計算13,基于遺傳算法的人工神經網絡學習算法14.自適應遺傳算法優化管網狀態估計神經網絡模型.15,基于GA_RBF神經網絡的電梯交通流模式識別的研究
標簽：
MATLAB
神經網絡
BP神經網絡
中的應用
上傳時間：
2013-12-27
上傳用戶：chenjjer
一種比較好的抗鋸齒算法
Add myaa.m to your path and enjoy anti-aliased professionally looking graphics in Matlab at any time. Myaa works with any kind of graphic (3-D, plots, scatterplots, ...) and even adds anti-aliasing to text, ui controls and grids. Myaa is ideal for complex, cluttered and saturated plots.
See attached screenshot for a demonstration. More examples included in the code, just run help myaa .
Curiosa:
For those of you who publish your code often, an undocumented anti-aliasing option is included in the snapnow.m function in Matlab. To publish a file called test.m you can do:
opts.figureSnapMethod = antialiased
publish( test.m ,opts)
However, you will have more control over the process using myaa, which is also the best choice when using Matlab interactively.
標簽：
professionally
anti-aliased
graphics
looking
上傳時間：
2016-09-28
上傳用戶：txfyddz
