Multitarget prediction using an aim-object-based asymmetric neuro-fuzzy system: A novel approach
| Autor: | Chia Hao Tu, Chunshien Li |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
Structure (mathematical logic)
0209 industrial biotechnology Neuro-fuzzy Computer science Cognitive Neuroscience Fuzzy set Object based Estimator 02 engineering and technology System a Computer Science Applications 020901 industrial engineering & automation Artificial Intelligence 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Algorithm |
| Zdroj: | Neurocomputing. 389:155-169 |
| ISSN: | 0925-2312 |
| DOI: | 10.1016/j.neucom.2019.12.113 |
| Popis: | This paper proposes an aim-object-based asymmetric neuro-fuzzy system that is different from conventional models in two ways. First, this system has an asymmetric structure with different numbers of neurons in the premise and consequent layers. Secondly, with the assistance of the sphere complex fuzzy set, depending on the application, our model can alter the number of outputs. In addition, a hybrid learning algorithm combining the whale optimization algorithm and the recursive least-square estimator is proposed to optimize the proposed model. The results of the experiment show that the proposed model can simultaneously predict multiple targets with fewer parameters and maintain a performance level similar to that of the conventional neuro-fuzzy system. |
| Databáze: | OpenAIRE |
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