forecasting:meeting_minutes_october_18_2016

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forecasting:meeting_minutes_october_18_2016 [2016/10/19 02:43]
jobatake
forecasting:meeting_minutes_october_18_2016 [2021/09/19 21:59] (current)
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   * 3D plot: 2011, 2012 normalized and unnormalized for comparison   * 3D plot: 2011, 2012 normalized and unnormalized for comparison
   * LA more variation, but smoother   * LA more variation, but smoother
- 
   * Moving Average and Decimation/​Downsample   * Moving Average and Decimation/​Downsample
 +  * D and X from 2011:
 +  * X = 8:00-4:00 (input data)
 +  * D = 9:00-5:00 (normalized and downsampled,​ column)
 +  * Y = Least Squares Equation = W.T(X) row = X.T(W) column
 +  * Unnormalized = D bar, Y bar
 +    * Statistical:​
 +      * Y - sig*Y + m
 +      * D - sig*D + m
 +    * Zenith:
 +      * Y*cos(theta)
 +      * D*cos(theta)
 +  * W = (XX.T)^(-1)*XD <= XX.T*W = XD
 +  * E^2 Averaged = (D-Y)^2 for every time
 +  * MSE = 1/m (||D-Y||)^2
 +  * Don't need r bc cancel
   * Ask Seyed what he did for decimation/​downsample   * Ask Seyed what he did for decimation/​downsample
     * 1) Average and down sample     * 1) Average and down sample
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       * 8:01-8:10 moving average       * 8:01-8:10 moving average
       * Then downsample       * Then downsample
-  * <del>Filter then normalize?</​del>​ +  * Filter then normalize 
-  * Normalize then filter!+  * <del>Normalize then filter</​del>​
     * **Normalization:​ mean then deviation**     * **Normalization:​ mean then deviation**
-    * Zenith Angle Normalizationzenith ​angle, ​then filter+    * Zenith Angle FilterZenith ​angle is from the 5th minute5 irradiance is averaged 
 +      * Bias term 
 +        * Number of taps is # present + number before 
 +          * 1 tap = present 
 +          * 2 tap = present + future (5 mins in our case) 
 +        * In weight matrix 
 +          * Row of 1's to the matrix to get bias term
     * Statistical normalization:​ -mean/​deviation     * Statistical normalization:​ -mean/​deviation
 +      * Standard normalization 0 mean
 +  * Estimate will need to be given back after the normalization
   * 3D plot for both zenith and stat normalization   * 3D plot for both zenith and stat normalization
 +  * Plot MSE 
 +    * y = MSE, x = # taps 
 +    * Train error goes down, test error decreases until flattens or increases 
 +  * Check 2012 MSE test against 2011 MSE train 
 +    * Keep 2011 W 
 +    * Get new X, D to compute new Y 
 +  * Flip: 2011 MSE test against 2012 MSE train 
 +  * Correlation is 3D plot 
 +    * R=(1/​m)XX.T= 10x10 matrix that is symmetric
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