The entropy values for the four criteria are e1=0.99375 for Price or Cost, e2=0.96296 for Storage Space, e3=0.97185 for Camera, and e4=0.97367 for Looks.
Conditions: The example uses 5 alternatives and 4 criteria.; The scaling constant h is 0.621335.; The matrix has been normalized prior to calculation.
The entropy values for the four criteria are e1=0.99375 for Price or Cost, e2=0.96296 for Storage Space, e3=0.97185 for Camera, and e4=0.97367 for Looks.
Conditions: The example uses 5 alternatives and 4 criteria.; The scaling constant h is 0.621335.; The matrix has been normalized prior to calculation.
The entropy formula is ej=−h∑i=1mrijlnrij. The constant h is a scaling factor defined as 1/ln(m), where m is the number of alternatives, ensuring the entropy values are properly scaled.
Conditions: The decision matrix has already been normalized to produce rij.; The natural logarithm ln is used.; m represents the total number of alternatives (rows).
The entropy formula is ej=−h∑i=1mrijlnrij. The constant h is a scaling factor defined as 1/ln(m), where m is the number of alternatives, ensuring the entropy values are properly scaled.
Conditions: The decision matrix has already been normalized to produce rij.; The natural logarithm ln is used.; m represents the total number of alternatives (rows).
The degree of diversification, denoted as dj, is defined as 1−ej. It represents the amount of useful information or distinguishing power provided by a specific criterion among the alternatives.
Conditions: The entropy value ej has already been calculated for the criterion.; The degree of diversification is always a positive real number in this context.
The degree of diversification, denoted as dj, is defined as 1−ej. It represents the amount of useful information or distinguishing power provided by a specific criterion among the alternatives.
Conditions: The entropy value ej has already been calculated for the criterion.; The degree of diversification is always a positive real number in this context.