IMPORTANT: You must have Java Runtime Environment (JRE) setup to be able to run the application
- Main Screen contains Train and Test buttons

-- Train Screen
--- You can add new record to the database to be included in further training
	But you need to follow the given format 'dd.mm.yyyy r1,r2,r3,r4,r5,r6'
	where r(1~6) are the lottery result for that record
--- Specify number of Hidden neurons (Open Range)
	Note: Increasing number of Hidden neurons more than regular will lead to slow performance
--- Specify learning rate (Recommended Range 0.4~0.7 but you can specify yours)
--- Specify Maximum Learning Iterations (Open Range)
	Note: The higher the maximum iterations, the more accurate the results are.
	Note: The higher the maximum iterations, the slower the training
	For best performance choose in range 500~5000
--- You can Pause and Resume at any time during the training
	During the pause you can save the best structure the network has reached
--- You can monitor progress at anytime, However duo to the load of updating the interface with progress
	this will slow down the training speed, so it's recommened to check the progress only when required
	then  uncheck it speed up the training

--- ATTENTION: Remember always to save the structure after the training to be used in testing

-- Test Screen
--- You must select a valid structure to be able to test your input
	Note: If you don't have a valid structure then you will have to train the network first
--- Specify your date in correct format (dd.mm.yyyy) where dd in range (1~31), mm in range (1~12)
	yyyy in range (1900~3000)
--- Start testing button will produce the expect lottery based on the current network structure
--- By default the current day date will be loaded into the date field