Analysing neural model(FCM)

I have attached a sample source code of my project. My scope is to developed,tested and validate using an example case of a complex system.The example case chosen in this research is indoor room cooling system which consists variables such as temperature inside,humidity inside,cfm of ceiling fan,temperature outside and humidity outside.These multiple variables of dataset described as complex system where the real influence between these variables is unknown.Here, I am using unsupervised differential Hebbian learning rule to test the noisy data in column 5. I have gain the neural model but I do not know how to read and analysing the neural model (FCM). Can help me with this? Just a rough idea enough for me to write in result and discussion part in my thesis.Thank you.

[Greg Heath]

NN trn/val/tst data division terminology:

data = design + test

design = train + validation

train:

 1. Estimate weight and bias values for multiple designs
 2. Estimate biased and degree-of-freedom-adjusted training performances

validation:

 1. Stops training when validation error minimizes
 2. Used to rank designs
    a. Weed out failed designs as outliers
    b. Obtain resulting summary performance stats(min/median/mean/std/max)

test:

 1. Uses the "best" design ( e.g.,min(mseval) ) to obtain an UNBIASED estimate of unseen data (generalization).
 2. Uses all acceptable designs to estimate UNBIASED summary statistics of performance on unseen data

[Greg Heath]

Unclear explanation

1. No attached source code

2. What are fcm and cfm?

 >>lookfor fcm
    fcm not found.
 >>lookfor cfm
    cfm not found.

3. Input variables?

4. Output variables?

5. Please explain: "Here, I am using unsupervised differential Hebbian learning rule to test the noisy data in column"

[Alagesan]

sorry for the long delay. This is my source code.

[Alagesan]

FCM is fuzzy cognitive map while cfm ( cubic feet per minute used for ceiling fan to calculate its air velocity)