Future Trend Impact Analysis Based on Adaptive Neuro-Fuzzy Inference System
| Autor: | Kyung-Il Moon, Yong-Gil Kim, Se-Ill Choi |
|---|---|
| Rok vydání: | 2015 |
| Předmět: |
Engineering
Adaptive neuro fuzzy inference system Artificial neural network business.industry Event (computing) Process (engineering) media_common.quotation_subject Estimator computer.software_genre Fuzzy logic Set (abstract data type) Data mining Function (engineering) business computer media_common |
| Zdroj: | The Journal of the Korea institute of electronic communication sciences. 10:499-505 |
| ISSN: | 1975-8170 |
| DOI: | 10.13067/jkiecs.2015.10.4.499 |
| Popis: | Trend Impact Analysis(: TIA) is an advanced forecasting tool used in futures studies for identifying, understanding and analyzing the consequences of unprecedented events on future trends. An adaptive neuro-fuzzy inference system is a kind of artificial neural network that integrates both neural networks and fuzzy logic principles, It is considered to be a universal estimator. In this paper, we propose an advanced mechanism to generate more justifiable estimates to the probability of occurrence of an unprecedented event as a function of time with different degrees of severity using Adaptive Neuro-Fuzzy Inference System(: ANFIS). The key idea of the paper is to enhance the generic process of reasoning with fuzzy logic and neural network by adding the additional step of attributes simulation, as unprecedented events do not occur all of a sudden but rather their occurrence is affected by change in the values of a set of attributes. An ANFIS approach is used to identify the occurrence and severity of an event, depending on the values of its trigger attributes. The trigger attributes can be calculated by a stochastic dynamic model; then different scenarios are generated using Monte-Carlo simulation. To compare the proposed method, a simple simulation is provided concerning the impact of river basin drought on the annual flow of water into a lake. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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