N-WASPAS - Nötrosofik WASPAS

Formül adımları

Analiz motorunun yöntem bildirimindeki (manifest F.steps) adımlar; raporlardaki formüllerle aynı kaynaktır.

1. Build SVN decision matrix

   $${\tilde{x}}_{ij}=(T_{ij},I_{ij},F_{ij})\in [0,1{]}^3,T+I+F\le 3$$
   LaTeX

   \tilde{x}_{ij} = (T_{ij}, I_{ij}, F_{ij}) \in [0,1]^3, \quad T+I+F \le 3

2. Score function

   $$S(\tilde{x})=\frac{1+T-2I-F}{2}$$
   LaTeX

   S(\tilde{x}) = \frac{1+T-2I-F}{2}

3. Normalize weights

   $$\sum _j{w}_j=1$$
   LaTeX

   \sum_j w_j = 1

4. WSM score

   $$Q_i^{(1)}=\sum _j{w}_{j}S({\tilde{x}}_{ij})$$
   LaTeX

   Q_i^{(1)} = \sum_j w_j S(\tilde{x}_{ij})

5. WPM score

   $$Q_i^{(2)}=\prod _{j}S({\tilde{x}}_{ij}{)}^{w_j}$$
   LaTeX

   Q_i^{(2)} = \prod_j S(\tilde{x}_{ij})^{w_j}

6. WASPAS

   $$Q_i=\lambda Q_i^{(1)}+(1-\lambda )Q_i^{(2)},\lambda \in [0,1]$$
   LaTeX

   Q_i = \lambda Q_i^{(1)} + (1-\lambda) Q_i^{(2)}, \quad \lambda \in [0,1]

7. Rank

   $$\text{Rank by aggregated neutrosophic score (descending)}$$
   LaTeX

   \text{Rank by aggregated neutrosophic score (descending)}

Sezgi

Sonucu okuma: Use N-WASPAS when expert assessments involve truth (T), indeterminacy (I), and falsity (F) components.

Sık yapılan hatalar

• T+I+F > 3 (violates SVN constraint)