Serialized Form

Class nrc.fuzzy.AboveModifier implements Serializable


Class nrc.fuzzy.AntecedentCombineOperator implements Serializable


Class nrc.fuzzy.BelowModifier implements Serializable


Class nrc.fuzzy.CompensatoryAndAntecedentCombineOperator implements Serializable

Serialized Fields

gamma

double gamma
The gamma value controls the output of the 'compensatory and' function. By default it is set to 0.562 which apparantly gives good (expected) results according to a study done. Note that by setting gamma to 0 we get the equivalent of the ProductAntecedentCombineOperator.


Class nrc.fuzzy.DoubleVector implements Serializable

Serialized Fields

increment

int increment
The increment amount by which the DoubleVector expands when it reaches capacity and has to insert another double value. This increment value can be set by choosing a constructor that allows you to specify it.


d

double[] d
The array of doubles values. This array is manipulated in such a way that it will expand as required to accomodate the addition of double values after the DoubleVector is created.


index

int index
The current number of double values in the array, and the index of the array at which the next double value should be inserted.


Class nrc.fuzzy.ExtremelyModifier implements Serializable


Class nrc.fuzzy.jess.FuzzyConsole implements Serializable


Class nrc.fuzzy.FuzzyException implements Serializable


Class nrc.fuzzy.jess.FuzzyFactoryImpl implements Serializable


Class nrc.fuzzy.jess.FuzzyFunctions.FuzzyMatch implements Serializable


Class nrc.fuzzy.jess.FuzzyMain implements Serializable


Class nrc.fuzzy.jess.FuzzyRete implements Serializable

Serialized Fields

m_globalContributionOperator

nrc.fuzzy.jess.GlobalContributionOperator m_globalContributionOperator
Determines how global contribution is to be done when a fact with fuzzy values is asserted. There are at least 3 options:
1. fuzzyUnion of the FuzzyValues (default)
2. fuzzySum of the FuzzyValues
3. Replace the FuzzyValues (i.e. no global contribution)

Other operator may be added by users or as part of the system.


m_currentActivation

jess.Activation m_currentActivation

m_currentActivationFuzzyRule

nrc.fuzzy.FuzzyRule m_currentActivationFuzzyRule
Holds a FuzzyRule for current rule activation during the time a rule is firing. It will be null when there is no rule firing and will be set if required when an activation is firing (ie. when there asserts during the rule firing that have fuzzy values in the slots).


Class nrc.fuzzy.FuzzyRule implements Serializable

Serialized Fields

antecedents

nrc.fuzzy.FuzzyValueVector antecedents
A vector of FuzzyValues that represent the antecedents in the rule


conclusions

nrc.fuzzy.FuzzyValueVector conclusions
A vector of FuzzyValues that represent the conclusions in the rule


inputs

nrc.fuzzy.FuzzyValueVector inputs
A vector of FuzzyValues that represent the inputs for the rule


executor

nrc.fuzzy.FuzzyRuleExecutor executor
The FuzzyRuleExecutor that will be used when the rule is executed (fired) to generate the fuzzy value output vector


antecedentCombineOperator

nrc.fuzzy.AntecedentCombineOperator antecedentCombineOperator
The operation used to combine the match values for multiple antecedent/input pairs in this rule (minimum or product)


antecedentsChanged

boolean antecedentsChanged
A flag that is set to true when the antecedents set has changed between rule firings


conclusionsChanged

boolean conclusionsChanged
A flag that is set to true when the conclusion set has changed between rule firings


inputsChanged

boolean inputsChanged
A flag that is set to true when the input set has changed between rule firings


antecedentCombineOperatorChanged

boolean antecedentCombineOperatorChanged
A flag that is set to true when the operation (minimum or product) for combining antecedent/input match values has changed between rule firings


Class nrc.fuzzy.FuzzyRuleException implements Serializable


Class nrc.fuzzy.FuzzyRuleExecutor implements Serializable


Class nrc.fuzzy.FuzzySet implements Serializable

Serialized Fields

set

nrc.fuzzy.SetPoint[] set
This is the heart of the FuzzySet, an array of SetPoints which represent the FuzzySet.


numPoints

int numPoints
The numPoints variable keeps track of the number of points contained in set, the array of SetPoints.


simplified

boolean simplified
The simplified variable is a boolean used to indicate whether or not the FuzzySet has been 'simplied' (revove extra points in the set -- see the simplifiySet method)


Class nrc.fuzzy.FuzzySetException implements Serializable


Class nrc.fuzzy.jess.FuzzyToken implements Serializable

Serialized Fields

m_theParent

nrc.fuzzy.jess.FuzzyToken m_theParent
The Parent of this token. This attribute is added so that it is possible to traverse the tokens associated with an activation (these hold the facts that matched on the LHS of a rule).


m_extensionData

java.util.Vector m_extensionData
Data needed to support Jess (Fuzzy) Extensions can be carried around in this special Vector. In general this is added to support the need to store 'special' information with facts as they work their way through the rete network. When the RHS of a rule fires the m_token associated with the activation will have a list of all of facts that contributed to the rule's firing. The 'special' information can be added during function calls that are made during the tests that are performed as patterns are matched. In general this information will be attached to the token that holds the fact as it moves through the net to a terminal node. It is required that the data stored be associated with one and only one traversal of the path. Since a token, with its fact, can actually take several paths through the net, it is sometimes necessary that the 'special' data be added to a new token (a copy of the current token with the extension data added to it) so that it becomes a unique token from that point on in the traversal through the net. This allows the system to identify that a new token should be formed and passAlong'd down the net from that point. The original token will be used for other paths without the special data. This is taken care of in various places in the Jess code with the addition of calls to the 'prepare' method. Other extensions can then use the same hooks to record any information required as the facts move through the net. The KEY thing here is that in Jess the 'prepare' method must be called after each pattern is matched AND any tests were done (in particular for the fuzzy extension whenever the fuzzy-match function is called ... but since this is a general mechanism prepare is called whenever any test functions are called ... the prepare function has a single parameter that is true when the pattern test was successful and false when is was not. This lets the extension take action depending on the success of the test(s). In the fuzzy extension the fuzzy-match function puts information in the token in the m_extension slot ... the pattern fuzzy value and the fact fuzzy value pair(s) that matched. If the tests for the pattern were successful then the token is duplicated and the m_extensionData slot of the original token is cleared. If it fails then the m_extensionData slot of the original is cleared (since the info is not needed ... the pattern match failed).


Class nrc.fuzzy.FuzzyValue implements Serializable

Serialized Fields

fuzzyVariable

nrc.fuzzy.FuzzyVariable fuzzyVariable
Holds the FuzzyVariable associated with the FuzzyValue. The fuzzy variable determines the context within which a fuzzy value has meaning. It provides the language (the variable itself, such as temperature, as well as the terms such as hot or cold, and the universe of discourse for the variable) used to describe a fuzzy concept.


linguisticExpression

java.lang.String linguisticExpression
Contains the linguistic expression, or the english phrase which linguistically describes the FuzzyValue. For example, if the FuzzyVariable was temperature, the linguistic term might be any of the following: cold, warm, hot, not cold AND somewhat warm, very warm AND more_or_less hot, etc. The linguistic term very often defines the FuzzyValue, and the FuzzySet contained within the FuzzyValue is then created by applying the modifiers and operations in the linguistic expression to pre-existing terms.


fuzzySet

nrc.fuzzy.FuzzySet fuzzySet
Contains the FuzzySet, or the set of points that give the FuzzyValue mathematical meaning.


Class nrc.fuzzy.FuzzyValueException implements Serializable


Class nrc.fuzzy.FuzzyValueVector implements Serializable

Serialized Fields

increment

int increment
The increment amount by which the FuzzyValueVector expands when it reaches capacity and has to insert another FuzzyValue. This increment value can be set by choosing a constructor that allows you to specify it.


fuzzyValues

nrc.fuzzy.FuzzyValue[] fuzzyValues
The array of FuzzyValue values. This array is manipulated in such a way that it will expand as required to accomodate the addition of FuzzyValues after the FuzzyValueVector is created.


index

int index
The current number of FuzzyValues in the array, and the index of the array at which the next FuzzyValue should be inserted.


Class nrc.fuzzy.FuzzyVariable implements Serializable

Serialized Fields

name

java.lang.String name
The string name of the fuzzy variable


units

java.lang.String units
The units (such as Degrees C) for the varible


UOD

double[] UOD
The Universe of Discourse (x value range) for the variable


fuzzyTerms

java.util.Hashtable fuzzyTerms
The fuzzy terms described as FuzzyValues are stored in this hash table


Class nrc.fuzzy.FuzzyVariableException implements Serializable


Class nrc.fuzzy.GaussianFuzzySet implements Serializable


Class nrc.fuzzy.jess.GlobalContributionOperator implements Serializable


Class nrc.fuzzy.IncompatibleFuzzyValuesException implements Serializable


Class nrc.fuzzy.IncompatibleRuleInputsException implements Serializable


Class nrc.fuzzy.IntensifyModifier implements Serializable


Class nrc.fuzzy.Interval implements Serializable

Serialized Fields

lowX

double lowX

openFlagLow

boolean openFlagLow

highX

double highX

openFlagHigh

boolean openFlagHigh

nf

java.text.NumberFormat nf


Class nrc.fuzzy.IntervalVector implements Serializable

Serialized Fields

increment

int increment
The increment amount by which the IntervalVector expands when it reaches capacity and has to insert another Interval. This increment value can be set by choosing a constructor that allows you to specify it.


intervals

nrc.fuzzy.Interval[] intervals
The array of Interval values. This array is manipulated in such a way that it will expand as required to accomodate the addition of Intervals after the IntervalVector is created.


index

int index
The current number of Intervals in the array, and the index of the array at which the next Interval should be inserted.


Class nrc.fuzzy.InvalidDefuzzifyException implements Serializable

Serialized Fields

message

java.lang.String message
The message constructed to inform the user, to a greater degree, what has gone wrong.


Class nrc.fuzzy.InvalidFuzzyVariableNameException implements Serializable


Class nrc.fuzzy.InvalidFuzzyVariableTermNameException implements Serializable


Class nrc.fuzzy.InvalidLinguisticExpressionException implements Serializable


Class nrc.fuzzy.InvalidUODRangeException implements Serializable


Class nrc.fuzzy.LarsenProductMaxMinRuleExecutor implements Serializable

Serialized Fields

DOF

double DOF


Class nrc.fuzzy.LeftGaussianFunction implements Serializable

Serialized Fields

defaultNumPoints

int defaultNumPoints
This value is used to determine the number of points that will be in the gaussian-shaped fuzzy set generated by the generateFuzzySet(double leftX, double rightX) method, unless it has a value of < 5, in which case the value of static (class) variable, LeftGaussianFunctionDefaultNumPoints, will be used. This allows each instance of the LeftGaussianFunction to determine its own value for the number of points to be generated. Initially it is set to have the value 0 so that the LeftGaussianFunctionDefaultNumPoints value is used.


Class nrc.fuzzy.LeftGaussianFuzzySet implements Serializable


Class nrc.fuzzy.LeftLinearFunction implements Serializable


Class nrc.fuzzy.LeftLinearFuzzySet implements Serializable


Class nrc.fuzzy.LFuzzySet implements Serializable


Class nrc.fuzzy.LRFuzzySet implements Serializable


Class nrc.fuzzy.MamdaniMinMaxMinRuleExecutor implements Serializable

Serialized Fields

DOF

double DOF


Class nrc.fuzzy.MinimumAntecedentCombineOperator implements Serializable


Class nrc.fuzzy.ModifierFunction implements Serializable

Serialized Fields

m_name

java.lang.String m_name
The string name of the modifier function (as used in linguistic expressions). For example, the modifier function "very" might be used in an expression like "very cold".


Class nrc.fuzzy.Modifiers implements Serializable


Class nrc.fuzzy.MoreorlessModifier implements Serializable


Class nrc.fuzzy.NormModifier implements Serializable


Class nrc.fuzzy.NotModifier implements Serializable


Class nrc.fuzzy.NoXValueForMembershipException implements Serializable

Serialized Fields

yValue

double yValue
The y value for which an x value could not be found


message

java.lang.String message
The message constructed to inform the user, to a greater degree, what has gone wrong.


Class nrc.fuzzy.Parameters implements Serializable


Class nrc.fuzzy.PIFuzzySet implements Serializable


Class nrc.fuzzy.PlusModifier implements Serializable


Class nrc.fuzzy.ProductAntecedentCombineOperator implements Serializable


Class nrc.fuzzy.RectangleFuzzySet implements Serializable


Class nrc.fuzzy.RFuzzySet implements Serializable


Class nrc.fuzzy.RightGaussianFunction implements Serializable

Serialized Fields

defaultNumPoints

int defaultNumPoints
This value is used to determine the number of points that will be in the gaussian-shaped fuzzy set generated by the generateFuzzySet(double leftX, double rightX) method, unless it has a value of < 5, in which case the value of static (class) variable, LeftGaussianFunctionDefaultNumPoints, will be used. This allows each instance of the LeftGaussianFunction to determine its own value for the number of points to be generated. Initially it is set to have the value 0 so that the RightGaussianFunctionDefaultNumPoints value is used.


Class nrc.fuzzy.RightGaussianFuzzySet implements Serializable


Class nrc.fuzzy.RightLinearFunction implements Serializable


Class nrc.fuzzy.RightLinearFuzzySet implements Serializable


Class nrc.fuzzy.SetPoint implements Serializable

Serialized Fields

x

double x
The x value of this SetPoint.


y

double y
The membership value (graphically, the y value) of the point x in a FuzzySet.


Class nrc.fuzzy.SFunction implements Serializable

Serialized Fields

defaultNumPoints

int defaultNumPoints
This value is used to determine the number of points that will be in the S-shaped fuzzy set generated by the generateFuzzySet(double leftX, double rightX) method, unless it has a value of < 3, in which case the value of static (class) variable, sFunctionDefaultNumPoints, will be used. This allows each instance of the SFunction to determine its own value for the number of points to be generated. Initially it is set to have the value 0 so that the sFunctionDefaultNumPoints value is used. If the number is even it will be set to the next higher odd value (to maintain symmetry for the S curve).


Class nrc.fuzzy.SFuzzySet implements Serializable


Class nrc.fuzzy.SimilarityByAreaOperator implements Serializable


Class nrc.fuzzy.SimilarityByPossibilityOperator implements Serializable


Class nrc.fuzzy.SimilarityOperator implements Serializable


Class nrc.fuzzy.SingletonFuzzySet implements Serializable


Class nrc.fuzzy.SlightlyModifier implements Serializable


Class nrc.fuzzy.SomewhatModifier implements Serializable


Class nrc.fuzzy.StringVector implements Serializable

Serialized Fields

s

java.lang.String[] s

index

int index


Class nrc.fuzzy.jess.SumGlobalContributionOperator implements Serializable


Class nrc.fuzzy.TrapezoidFuzzySet implements Serializable


Class nrc.fuzzy.TriangleFuzzySet implements Serializable


Class nrc.fuzzy.TsukamotoRuleExecutor implements Serializable

Serialized Fields

DOF

double DOF


Class nrc.fuzzy.jess.UnionGlobalContributionOperator implements Serializable


Class nrc.fuzzy.VeryModifier implements Serializable


Class nrc.fuzzy.XValueOutsideUODException implements Serializable


Class nrc.fuzzy.XValuesOutOfOrderException implements Serializable

Serialized Fields

prevValue

double prevValue
The value previous to the x value which is out of order.


currentValue

double currentValue
The x value which is out of order. It has been identified as the x value that is out of order because its value is less than the x value previous to it.


message

java.lang.String message
The message constructed to inform the user, to a greater degree, what has gone wrong.


Class nrc.fuzzy.YValueOutOfRangeException implements Serializable

Serialized Fields

yValue

double yValue
The y value whose range is outside the strict acceptable range of 0.0 to 1.0 inclusive, or [0.0, 1.0].


message

java.lang.String message
The message constructed to inform the user, to a greater degree, what has gone wrong.


Class nrc.fuzzy.ZFunction implements Serializable

Serialized Fields

defaultNumPoints

int defaultNumPoints
This value is used to determine the number of points that will be in the Z-shaped fuzzy set generated by the generateFuzzySet(double leftX, double rightX) method, unless it has a value of < 3, in which case the value of static (class) variable, zFunctionDefaultNumPoints, will be used. This allows each instance of the ZFunction to determine its own value for the number of points to be generated. Initially it is set to have the value 0 so that the zFunctionDefaultNumPoints value is used. If the number is even it will be set to the next higher odd value (to maintain symmetry for the Z curve).


Class nrc.fuzzy.ZFuzzySet implements Serializable