Manual - SwingNN

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SwingNN

User guide


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Contents


SwingNN

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How it Works

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Getting Started

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5

Main Windows

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Grid

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Grid Names

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Network

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Importance

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Graph

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Toolbars

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Main

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View

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Tools

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Dialogs

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Details

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Forecast

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Progressive Forecast

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Discovered Patterns

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Set Function

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Set Grid Range

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Support

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Special files

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Save Grid Details

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3


SwingNN



SwingNN Introduction


Welcome to
SwingNN
, a powerful and easy to use forecasting application.


Using
SwingNN
you can:


1.Import text, csv, spreadsheet, image or binary files into the

Grid.

2.Us
e many editing and pre
-
formatting functions on the grid.

3.Set up any of the grid columns for forecasting.

4.Use the fully automated forecasting facilities.


New Users should do the
Getting Started

exercises.


Neural Planner Software Ltd


SwingNN


How

it Works


Getting Started


Main Windows


Toolbars


Dialogs


4


How it Works

How SwingNN forecasts the future.


The future can never be forecasted with guaranteed accuracy but by using the
SwingNN
methods it is possible to achieve good

results.


The
SwingNN

grid is produced by importing txt, csv, xls, bmp or binary files. The grid
can also be produced manually using the editing facilities. Numeric, text and image
columns can be used together in the same grid.


Only future numeric valu
es can be forecasted. Text and image inputs will influence the
forecasting of the numeric values.


A neural network is created from the grid data. Grid input columns are connected to
network input nodes, grid output columns are connected to network output
nodes and
grid
serial

columns are connected to both network input and output nodes. At least one
serial column is needed for forecasting.


The neural network is trained using the grid example rows. The risk level is set to zero.


After the neural network i
s trained, the serial input values are forced to swing beyond
their limits. The serial output values are forecasted by the neural network. A new neural
network is created and trained using the new inputs and forecasted outputs. The new
neural network is co
mpared with the original neural network. The inputs are adjusted,
another new neural network is created and the risk level is incremented by one. The
process continues until a new neural network agrees with the original one about the
forecasts or the risk
level is too high. The forecasts are added to the grid for you to use.






5


Getting Started

The exercises can be started by clicking the
Getting Started

button on the
Tip of the
Day

or using the menu command
Help > Getting Starte
d...


1.
Pressure

In the first exercise you will forecast a future health problem.

The 'Pressure.tvq' sample is a record of a patient's blood pressure taken every day. The
systolic and diastolic pressures vary quite significantly and they do not always ri
se and
fall together. The patient needs to know if a problem is likely to occur any time in the
near future. The systolic column and diastolic columns are changed to Serial to make the
grid ready to allow rows and future values to be added and tested. 'Act
ion > Forecast'
opens the 'Forecast' dialog. New rows are generated with the forecasted values. The grid
scrolls to show the new rows. The graph of the forecasted systolic values show a future
high blood pressure problem.


2.
Random

This exercise shows th
at
SwingNN
can find trends and forecast future values even if the
data is random. All the columns are already set to 'Serial' so future values can be
forecasted. When forecasting has finished the risk values are indicated. The forecast
value may be wrong f
or any risk. That is to be expected when the initial values are
random.
SwingNN
shows you the risk.


3.

Grocer

Every day a retail grocer collects his stock from the wholesale market and sets the prices
he will charge.
SwingNN
is used to forecast the price
s that he will be charging in the next
few days. All the columns are set to 'Input'. The columns for the food prices that are to be
forecast to changed to 'Serial'. The 'Forecast' toolbar icon is enabled and is clicked to
open the 'Forecast' dialog. 'Value
s to forecast' is changed to 5 and forecasting started.
When forecasting has finished the next days food prices may show some low risk
bargains that could be used as sales leaders without any serious impact on the grocers
profit
.


4.
Shares

Many applicat
ions use neural networks to forecast the price of shares. The forecasts are
often less useful than those of stock market experts. This exercise shows that the forecast
produced by
SwingNN
is a downward price trend. The expert forecasted a similar
downward
trend.



6


Main Windows



Main Windows


Grid


Network


Importance


Graph


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Grid




The Grid view shows all the Examples arranged in rows and all the Input/Outputs
arranged in columns. The first column contains the Exam
ple types and names. The first
row contains the Input/Output types and names. Everything on the Grid can be edited by
moving to the cell containing the value and then pressing the enter key to start the Edit
Grid dialog. The cell can be selected either usi
ng the arrow keys or the mouse. A single
click will select the cell and a double click will start the Edit Grid dialog. A double click
on the Example name cell will select the whole row and a double click on the
Input/Output name cell will select the whole

column. The row or the column can be
deselected by pressing the Esc key.


Creating a New Grid.

A new Grid is created by pressing the new toolbar button or using the
File > New

menu
command. The new Grid will be empty except for a horizontal line, a vertic
al line and an
underline marker that shows the current position in the Grid. New Grid rows and columns
are created at the current position.

Creating the first Example row and Input/Output column


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Press return and a prompt will appear that says "Create new E
xample row?". Answer
Yes. Another prompt will appear that says "Create new Input/Output column?". Answer
Yes again. You will now see that the Grid has one cell containing "?", a row name
containing "T:0" and a column name containing "I:0". The "?" indicate
s that the cell has
no value, the "T:0" indicates that it is a Training Example in row 0 and the "I:0" indicates
that is is an Input in column 0. Press return again and an Edit Grid dialog box will appear
that allows you to enter the cell value. Using the
same dialog you can change the
Input/Output column name, mode and type. The dialog can also be used to change the
Example row name and type.


Creating more Input/Output columns.

Move the marker one cell to the right by pressing the right arrow or tab key.

Now press
the return key and a prompt will appear that says "Create new Input/Output column?".
Answer Yes. Press return again and the Edit Grid dialog box will appear. This time the
Example row will already contain a name and type. You can set the cell va
lue, the
Input/Output name and the type can be set to "I:" for input, "O:" for output, "X:" for
exclude or "S:" for serial. The mode can be set to "Real", "Integer", "Bool" "Text" or
"Image". Any type of Input/Output column can be inserted into the Grid us
ing the
functions on the Insert menu.


Creating more Example rows.

Move the marker one cell down by pressing the down arrow key. Now press the return
key and a prompt will appear that says "Create new Example row?". Answer Yes. Press
return again and the E
dit Grid dialog box will appear. This time the Input/Output column
will already contain a name and type. You can set the cell value, Example name and the
type can be set to T: for training, V: for validating, Q: for querying or X: for exclude.
Any type of
Example row be inserted into the Grid using the functions on the Insert
menu.

Copying Example rows and Input/Output columns.

Double click on the name to select the whole row or column. Cut will remove the
selected row or column and place it on the clipboar
d. Copy will place a copy of the
selected row or column on the clipboard. Paste will insert a copy of the clipboard before
the currently selected row or column. If the clipboard contains a row then Paste will
insert the row into the Grid. If the clipboard
contains a column then Paste will insert a
column into the Grid. The invisible Grid data, limits and defaulted values, will be
regenerated after a Paste column thus any neural network that has already been generated
from the Grid will be invalidated.



Ro
ws names



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The grids rows can have any names. If names are not used the rows are numbered.


Column names




The grid columns can have any names. If names are not used the columns are
numbered.


Grid cells




Grid cells can contain numbers, text or
images. The numbers can be integer, real or
boolean.

Grid


Grid Names


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Grid Names




The meaning of the row and column names.


Serial Column




A serial mode column of Integers. Only serial mode columns are forecasted.


Excluded

Columns




Two excluded columns with real numbers and letters. Excluded columns are not
forecasted.


Row Names





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The original four rows with names.


Swing Forecasts




Four
Swing
forecasted rows. The rows names show the risk level for each row. If t
he
name is
Forecast
it means that there is no risk.


Progressive Forecasts




Progressive
forecasts with row names showing the risk and copies of the original row
names. As forecasting continues copies of the forecasts are used for further forecasts.


C
ells




The grid cells contain the original and the forecasted values.


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Network




Neural networks are created when they are required for forecasting. Grid input columns
are connected to network input nodes, grid output columns are c
onnected to network
output nodes and grid serial columns are connected to both network input and output
nodes.


Input node




Input nodes are connected to grid input or serial columns.


Output node




Output nodes are connected to grid output or seria
l columns.


Hidden node



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Hidden nodes are connected to input, output or serial nodes.


Connections




Layers of nodes are fully connected to the adjacent layer. A connection can have a
positive or negative weight. The line color shows the polarity
and the thickness shows
the weight value relative to the greatest weight.


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Importance




The importance of each input is the sum of the connection weights from the input node
to the hidden layer.


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Graph




The colum
n values graph.


Scaled Values




The column values are scaled from 0.0 to 1.0


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Trend




The trend over the whole graph.


Value && Average




The blue line is the value of every row for the selected column. The red line is the
running average of a t
enth of the total rows for the selected column.


Row Number or Name




Rows are numbered or named. The names of the rows can be selected on the right click
menu.


Real Values




The real column values.


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Toolbars



Toolbars


Main


Vi
ew


Tools


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Main




The main toolbar is for file access, grid editing and forecasting.


New




New
creates an empty
Grid
.


Open




Open
produces the standard dialog for file navigation and reading.


Import




Import
produces the stan
dard dialog for file selection. The file selected produces an
import dialog appropriate to the file type.


Save




Save
produces the standard file selection and save dialog.


Print




Print
the current
view
.


About




About
displays the application v
ersion and registration status.


Cut



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Cuts
the selected row or column to the clipboard.


Copy




Copies
the selected row or column to the clipboard.


Paste




Pastes
the clipboard contents to the row or column.


Refresh




Refreshes
the current
v
iew
.


Check




Checks
that the grid can be used for forecasting.


Swing




Swing Forecast
opens the
forecasting
dialog to set the serial columns to allow input
and output values to
swing
beyond their limits.


Stop




Stops
forecasting.


Pattern




Pattern
forecasting


Progressive




Progressive Forecast

opens the progressive dialog so that the ranges to use for
forecasting can be set.


Discover




Discover
searches for patterns in the grid and then opens the Discovered Patterns
dialog to allow
patterns to be used.


Delete latest




Delete Latest

deletes the latest copied or forecasted row and cancels the changes to

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the network used while forecasting. If all forecasted rows are deleted the network is also
deleted.


Delete copies




Deletes al
l the copied rows.


Delete forecasts




Deletes all the forecasted rows.


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View




The view toolbar.


Information




Information
about the open file.


Grid




Grid
shows the
grid

with scroll bars if needed.


Network




Network
shows

the latest created
neural network
.


Graph




Graph
shows the select column values
graph
.


Memory




Memory
remembers the currently selected column so it can be compared with any other
column.


Importance




Importance
shows the
importance

of each in
put.


Zoom




Zoom
the current view in or out.


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Tools






Special Files




Special Files

opens the Special Files dialog


Email




Email
opens the Support dialog.


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Dialogs



Dialogs


Details


Forecast


Progressive

Forecast


Discovered Patterns


Set Function


Set Grid Range


Support


Special files


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Details




The
Details
dialog. All the details of the
SwingNN
file.


History button





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Show a list of previous file open and save dates and times.


Save button




Save the
SwingNN
file details to a text file.


Refresh button




Refresh all the information.


Continue button




Close the information dialog and continue using this
SwingNN
file.


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Forecast




The
Forecast
dialog

is used to forecast the values of any serial mode columns.


Forecast type




The two main types of forecast.


Only
Serial

columns can be used to produce forecasts.


Swing
.

Includes the number of rows and forecast period.


Pattern
. Includes the range of

the pattern found.


Rows to forecast





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Enter the maximum number of rows to forecast.


Risk




Enter the maximum acceptable risk level for the forecasts.
SwingNN
may go beyond
this level as it tries to reduce the risk.


Rows to include




Check all
the row types to include in the forecast.


Limits




Check to allow the forecasted values to go above or below the limits of the current
range.


OK button




Press OK to accept all the settings and close the dialog.


Cancel button




Press Cancel to
reject all the settings and close the dialog.


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Progressive Forecast




An initial network is produced and trained using every row from the
First
to the
Last
.
Another network is produced and trained using the rows from the
S
tart
and then with all
the following rows up to the maximum. A copy of the row being forecast and a new row
are added to the end of the grid. The new row has the forecasted values. This allows the
forecasted values to be compared with the actual values. Mo
re than one forecast can be
produced at every step. The process continues until the maximum steps is reached.
When the process stops the grid is returned to its original state without removing the
added rows. A secondary copy of the grid can be saved along

with the secondary
network.


Total Rows



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The total number of rows in the grid. All rows are counted.


First Training Row




The first row in the grid to use for training the primary network.


Last Training Row




The last row in the grid to use fo
r training the primary network.


Start Forecasting Row




The first row to use for forecasting.


Forecasts per step




The number of forecasts to be produced after each step.


Produce Secondary Network




Check to produce a secondary network.


Secon
dary Network Name




The file name of the secondary network.


Max rows




The maximum number of rows to use for training at each step.


Max steps




The maximum number of steps.


Risk



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Forecasting will stop if the risk level is exceeded and cannot

be reduced.


Ignore stops




Check to ignore all stops during progressive forecasting.


Defaults button




Click
Defaults
to set all the dialog controls to their defaults settings for the grid.


OK button




Click OK to accept all the settings and c
lose the dialog.


Cancel button




Click Cancel to reject all the settings and close the dialog.


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Discovered Patterns




The
Discovered Patterns

dialog is produced after
Action > Discover Patterns

has run.
The dialog will
show any of the patterns that have been discovered in the grid and can
be used to extend or modify the grid with the discoveries.


Set All buttons




The mode of all the grid columns is set to Serial or Exclude.


Pattern Selection




Press the buttons
to find and select a discovered pattern.


Selected Pattern



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The grid start row, end row and column in the currently selected pattern.


Trend




The trend of the values in the currently selected pattern.


Toggle button




The serial mode of the sel
ected column is inverted.


Include in Forecast button




The selected pattern will be included in any forecasts. Every pattern is included by
default.


Exclude from Forecast button




The selected pattern will be excluded for all forecasts.


Copy to E
nd of Grid button




The selected pattern is copied to the end of the grid.


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Set Function




The
Set Function

dialog is opened using the grid, right click, context menu. Functions
can be used on cells, rows, columns or entire grid

ranges
.


Function




The function to execute.


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Fail




Stop the function if any failures occur.


OK button




Press OK to accept all the settings and close the dialog.


Cancel




Press the Cancel to reject all the settings and close the dialog.


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Set Grid Range




The
Set Grid Range

dialog is opened using the grid, right click, context menu. Functions
can be limited to grid ranges.


Rows




The range of rows for the
function
.


Columns




The range of columns for the
f
unction
.


OK button




Press OK to accept the setting and close the dialog.


Cancel button




Press Cancel to reject the settings and close the dialog.


36


Support






FAQ




Press the
FAQ
button to read the online frequently asked
questions.


Emial




Press the
email
button to send an email to support.


37


Special files




Network and grid components are saved to txt or csv files.


What to save




Check the item that are to be saved.


Extension




Select

the file type.


When to save




Select when to save.


OK button



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Press OK to accept the setting and close the dialog.


Cancel button




Press Cancel to reject the setting and close the dialog.

Special files


Save Grid Details


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Save Grid Details




The details to save in the Grid special file.


All Example Rows




Check to save all example rows including copies and forecasts.


Forecasted Rows




Check to save the forecast example rows.


Copied Rows




Check to sav
e the copies of example rows.


Row Number




Check to prefix the example row names with the row numbers.


Min/Max Column Details



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Check to save the minimum and maximum column details at the end of the grid file.


OK button




Click to accept all th
e settings and close the dialog.


Cancel button




Click to reject all the settings and close the dialog.


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