Equationless and equation-based trend models of prohibitively complex technological and related forecasts
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26510%2F16%3APU120325" target="_blank" >RIV/00216305:26510/16:PU120325 - isvavai.cz</a>
Result on the web
<a href="http://www.sciencedirect.com/science/article/pii/S0040162516301883" target="_blank" >http://www.sciencedirect.com/science/article/pii/S0040162516301883</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.techfore.2016.07.031" target="_blank" >10.1016/j.techfore.2016.07.031</a>
Alternative languages
Result language
angličtina
Original language name
Equationless and equation-based trend models of prohibitively complex technological and related forecasts
Original language description
PCF (Prohibitively Complex Forecast) models integrate several aspects, e.g. macroeconomic, ecology, sociology, engineering and politics. They are unique, partially subjective, inconsistent, vague and multidimensional. PCFs development suffers from IS (Information Shortage). IS eliminates straightforward application of traditional statistical methods. Oversimplified or highly specific PCFs are sometimes obtained. Artificial Intelligence has developed different tools to solve such problems. Qualitative reasoning is one of them. It is based on the least information intensive quantifiers i.e. trends. There are four different trends i.e. qualitative values and their derivatives: plus/increasing; zero/constant; negative/decreasing; any value / any trend. The paper studies PCF models represented by a set of NODE (nonlinear ordinary differential equations) and models based on EHE (equationless heuristics). An example of EHE is - If GDP is increasing then Research and Development investment is increasing more and more rapidly. Such verbal knowledge item cannot be incorporated into a traditional numerical model and a qualitative model must be used. The following qualitative equation eliminates all positive multiplicative constants A from PCF NODE models: AX = (+)X = X. Numerical values of NODEs constants are therefore qualitatively irrelevant. A solution of a qualitative model is represented by a set of scenarios and a set of time transitions among these scenarios. A qualitative model can be developed under conditions when the relevant quantitative PCF must be heavily simplified. The key information input into PCF EHE model is expert knowledge. A consensus among experts is often not reached because of substantial subjectivity of experts’ knowledge. The case study analyses interactions of three technologies using modified predator / prey model. It is based on three NODEs and three EHEs. NODEs have 463 scenarios and EHEs has 79 scenarios. The results are given in details. No
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
50202 - Applied Economics, Econometrics
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
ISSN
0040-1625
e-ISSN
1873-5509
Volume of the periodical
2016
Issue of the periodical within the volume
111
Country of publishing house
US - UNITED STATES
Number of pages
8
Pages from-to
297-304
UT code for WoS article
000384861200026
EID of the result in the Scopus database
2-s2.0-84999816135