Computational Intelligence in Cognitive Healthcare Information Systems - Computational Intelligence in Healthcare: Advanced Methodologies - page 350

This publication is an attempt at defining a UBMSS system for the cognitive
analysis of investments on the basis of three key financial indicators, which include:
NPV - net present value (symbol: W1), r - discount rate (W2), IRR - internal rate of
return (W3).
For the proposed UBMSS systems, a sequence grammar of the following form has
been defined:

G = ( Σ , Σ P , S )

INV N T ,

where:

Σ N - the set of non-terminal symbols

Σ N = {INVESTMENT, W1, W2, W3, WEAK_ACCEPT, ACCEPT,

STRONG_ACCEPT, NO_ACCEPT, A, B, C, D, E}
Σ T - the set of terminal symbols

Σ T = { ′ a ′ , ′ b ′ , ′ c ′ , ′ d ′ , ′ e ′ }, and the particular elements were defined as follows:

a = { 0 %} b ∈ ( 0 %, 15 %] c ∈ ( 15 %, 45 %) d ∈ [ 45 %, 100 %)

, , , ,

e ∈ ( − 100 %, 0 %)

(Fig. 12.)

Fig. 12. The set of terminal symbols
Source: own development

S ∈ Σ

, S = INVESTMENT
P - the set of productions shown below:
1. INVESTMENT Æ WEAK_ACCEPT | ACCEPT | STRONG_ACCEPT |
NO_ACCEPT
2. WEAK_ACCEPT Æ W1 W2 W3 //if (w1 & w2 & w3 = weak accept) fi-
nal_decision:= weak accept
3. ACCEPT Æ W1 W2 W3 //if (w1 & w2 & w3 = accept) final_decision := ac-
cept
4. STRONG_ACCEPT Æ W1 W2 W3 //if (w1 & w2 & w3 = strong accept) fi-
nal_decision := strong accept
5. NO_ACCEPT Æ W1 W2 W3 //if (w1 & w2 & w3 =not akcept) fi-
nal_decision := not accept
6. W1 Æ A | B | C | D | E // w1=decision
7. W2 Æ A | B | C | D | E // w2=decision
8. W3 Æ A | B | C | D | E // w3=decision
9. A → a // decision:= weak
10. B → b // decision:= weak
11. C → c // decision:= accept
12. D → d // decision:= strong
13. E → e // decision:= not accept

S - the start symbol,

N