====== Forecasting Meeting Minutes for Week of October 25, 2016 ====== 
** Present Tuesday: Austin, Gordon, Brieanna, Jaimie **

** Present Wednesday:  **

===== Updates =====
  * Sharif will meet with us on Wednesday

===== Meeting with Dr. Kuh =====
===== Expectations =====
  * All of this is normalized (w/ Zenith Angle)
  * X' = [X / 1 1 1 1 1 1]
  * X'.T = [X.T | 1]
  * X'*X'.T = [__X*X.T__ | **X1**]
            * [1.T*X.T   | m     ]
  * (X'*X'.T)/m
  *** Mean**: X1/m
  *__ Correlation(R)__ : X*X.T/m
  * Samples along diagonal of correlation matrix should be similar
    * Like toeplitz matrix
      * Right-hand bottom corner needs to be 1
      * Number of columns (m) in array rows (n)
      * Number of times you are doing prediction
      * Estimate 9-5 (8 hours, every 5 mins, 96 solar irradiance times/day *365 days/year= 35040 solar irradiance data points/year)
      * Diagonals same and symmetrical
  * 1's on bottom are for the zenith normalized data
  * Do not need for the statistically normalized data


  * Types of Prediction:
  * Average
  * Persistence: Most recent value for prediction (tap=1)

  * Python programming help from Sharif tomorrow
  * MSE value: D-Y=E(365*96)
  * Inner product of E/entries = 2D array
  * (Sum |E|^2)^.5
  * Root Mean Squared Working this week
    * Training to use same data for RMS
    * Go down with number of taps increasing
      * Take square root of the error
      * (90,000)^.5 = 300
  * Weight for taps
    * Positive values
    * Decrease in value
  * Train on 2011 and test on 2012
  * Train on 2012 and test on 2011
  * RMS graphs for the 2011 (Test and train) and 2012 (test and train)
    * Higher on test than training
    * Can become higher though
    * More time then train based on seasons
      * Winter 2011/2012, Spring 2011/2012, Summer 2011/2012, and Fall 2011/2012
  * Interested in power solar panels will be making