Raimo P Hämäläinen
Biographic Data
| ID | 6540398 |
|---|---|
| NAME | Raimo P Hämäläinen |
| GIVEN NAMES | Raimo P |
| FAMILY NAME | Hämäläinen |
| SIGNATURE | HÄMÄLÄINEN R P |
| AFFILIATIONS | University of Helsinki |
| ORCID | 0000-0002-4285-0092 |
| VERIFIED | Yes |
| TOTAL WORKS | 5 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 5 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 1989 |
| LATEST PUBLICATION YEAR | 2023 |
| H-INDEX | 0 |
A Competency Framework for Participatory Modeling
Participatory modeling (PM) is a craft that is often learned by training ‘on the job’ and mastered through years of practice. There is little explicit knowledge available on identifying and documenting the skills needed to perform PM. In the modeling literature, existing attempts to identify relevant competencies have focused on the specific technical skills required for specific technical model development. The other skills required to organize …
Design Gaming for Learning Systems Intelligence in Socio‐Emotional Systems
Peer reviewed
The threat of weighting biases in environmental decision analysis
Notes on the weighting biases in value trees
The variation in the structure of value trees can have undesirable effects on the attribute weights. Earlier experiments suggest that an attribute receives a higher weight if it is presented at an upper level in a value tree or if it is split into subattributes. Here we show that it is flawed to make conclusions about the biases at the individual level based on the averages of weights across large groups of subjects. Averages do not describe indi…
Project Selection by an Integrated Decision Aid
No prominent works on this page.
Project Selection by an Integrated Decision Aid
Notes on the weighting biases in value trees
The variation in the structure of value trees can have undesirable effects on the attribute weights. Earlier experiments suggest that an attribute receives a higher weight if it is presented at an upper level in a value tree or if it is split into subattributes. Here we show that it is flawed to make conclusions about the biases at the individual level based on the averages of weights across large groups of subjects. Averages do not describe indi…
The threat of weighting biases in environmental decision analysis
Design Gaming for Learning Systems Intelligence in Socio‐Emotional Systems
Peer reviewed
A Competency Framework for Participatory Modeling
Participatory modeling (PM) is a craft that is often learned by training ‘on the job’ and mastered through years of practice. There is little explicit knowledge available on identifying and documenting the skills needed to perform PM. In the modeling literature, existing attempts to identify relevant competencies have focused on the specific technical skills required for specific technical model development. The other skills required to organize …
Computer Science (4 works) · Complex Systems and Decision Making (3 works) · Psychology (3 works) · Artificial Intelligence (2 works) · Econometrics (2 works) · Engineering (2 works) · Knowledge management (2 works) · Mathematics (2 works) · Multi-Criteria Decision Making (2 works) · Political science (2 works)