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Step 5: Interval weight of each index ([w_{text{IAHP}} ]).
(28 where [w] denotes the comprehensive interval weight, which is a function of θ.
This can be used as the interval weight of the selected index layer.
Step 4: Interval weight of entropy of index ([w_{text{IE}} ]) derivation.
Open image in new window Fig. 5 Flowchart of comprehensive interval weight calculation.
The detailed procedure includes three main parts: IAHP, IE, and comprehensive interval weight, which are presented below.
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Ishibuchi et al. [24] proposed an architecture of Fuzzy Neural Networks (FNN) that have crisp inputs, interval weights and interval outputs for FR analysis.
The method also introduces the notion of weightings in the form of intervals, by which interval samples can be analyzed with a view to delineating the important attributes via the interval weights.
It is the deviation from the centroid of the visited places in a ([t_{1},t_{2}]) interval weighting the contribution of each Place with coordinates (C_{i}) within the set N by the time spent there.
The interval weights of the index and the comprehensive evaluation values of the blocks were obtained using the improved TOPSIS model, with the results shown in Tables 4 and 5.
The plants were dried in oven at 105 °C for 12 h (Mollah et al. 2009) and after half an hour interval the weight was taken to measure the dry mass.
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