dokumen.tips_pattern-planning-assistance-through-technical-evaluation-of-relevance-numbers

Слайд 2

PATTERN

Normative forecasting
Relevance tree method
Goal-oriented forecasting method where one establishes a future need

PATTERN Normative forecasting Relevance tree method Goal-oriented forecasting method where one establishes
and recedes backwards to the present and to the technologies needed to achieve the objective of the future.

Слайд 3

Basic form of relevance tree

Basic form of relevance tree

Слайд 4

Characteristics for forming the relevance tree:

There is hierarchy in the

Characteristics for forming the relevance tree: There is hierarchy in the relevance
relevance tree
Branches represent goals and subgoals
All relevant subgoals for each goal have to be identified
Each branch must be well defined so that there are no overlaps

Слайд 5

PATTERN

PATTERN has been used by the Honeywell Corporation for military, space and

PATTERN PATTERN has been used by the Honeywell Corporation for military, space and medical purposes.
medical purposes.

Слайд 6

PATTERN is based on:

Goal identification
Recognizing the relevance of set goals

PATTERN is based on: Goal identification Recognizing the relevance of set goals
in relation to criteria (means ranking, e.g. setting goals priority)
Recognizing technological alternatives necessary for achieving the goal

Слайд 7

Steps for PATTERN

Model description, recognizing the goals and hierarchy of the relevance

Steps for PATTERN Model description, recognizing the goals and hierarchy of the
tree
Recognize criteria
Determine relevance numbers – with participation of experts; selected exploratory, intuitive methods can be used
Data processing and final results – calculating relevance numbers, goals priority, ranking of technological alternatives

Слайд 8

Basic terms

Goals A, B,C...j...N
Criteria α, β, …, x, …, v.
Levels 1,

Basic terms Goals A, B,C...j...N Criteria α, β, …, x, …, v.
2, 3...i...n
Criteria weights
Wα, Wβ, …, Wx, …, Wv.
Contribution marks of the goal j to criteria x - element weights
Sjα, Sjβ, …, Sjx, …, Sjv.
Based on the relevance tree primary matrix has to be made for each expert

Слайд 9

Primary matrix

Primary matrix

Слайд 10

Basic terms

Based on the primary matrix the final primary matrix has to

Basic terms Based on the primary matrix the final primary matrix has
be calculated
The elements of final primary matrix are average values of responding elements in primary matrixes

Слайд 11

Basic terms

A panel of experts can be asked to weight the importance

Basic terms A panel of experts can be asked to weight the
of each criterium in relation to the others
The panel could be asked to weight the contribution of each element/goal to criteria – element weights

Слайд 12

Conditions for primary and final primary matrix
Sum of criteria weights is 1
Sum

Conditions for primary and final primary matrix Sum of criteria weights is
of contribution marks of goals to each criterium is 1

Слайд 13

Partial relevance numbers (relevance of goal j for criterium x)
Local relevance numbers

Partial relevance numbers (relevance of goal j for criterium x) Local relevance
(relevance of goal j at level i)

Слайд 14

Condition – Sum of local relevance numbers at one level has to

Condition – Sum of local relevance numbers at one level has to be 1
be 1

Слайд 15

Cumulative direct relevance number – Relevance of goal j for main goal,

Cumulative direct relevance number – Relevance of goal j for main goal, whole relevance tree
whole relevance tree
Имя файла: dokumen.tips_pattern-planning-assistance-through-technical-evaluation-of-relevance-numbers.pptx
Количество просмотров: 20
Количество скачиваний: 0