A Metaheuristic Approach to Map Driving Pattern for Analyzing Driver Behavior Using Big Data Analysis

Algorithm 3

Finding the maximum frequent access features from the driver’s usage pattern.

	Input: Mutual Pattern set Sgs. ← Ifs, Structural pattern so.
	Output: Class by category.
	Start
	For each graph Gi from Sgs
	For each domain Di from So
	Calculate the Number of mutual relations it has.
	Nr = ∑Relations€Gi
	Calculate Number of Fuel consideration.
	NIL = ∑Links(Gi) ← ∑Gk(Sgs)
	Calculate the value of speed occurrence.
	ILV = ∑mutual(Links(Gi)) € Di
	Compute the value Brake appearance.
	ELV = = ∑Concept(Links(Gi))) € ∑Concept(Dj)! = Di
	Compute Max mutual weight Slw.
	Slw =
	Compute append frequent weight Ws = ∑Ws(Di) + Slw
	End
	End
	For each domain Di from So
	Process mutual invariance between the feature relation
	Mean Service slw =
	End
	Select the weight Di as continual frequent feature.
	Return class c as Attain c ⟶ CRs pattern class.
	Stop.