TSK 기반의 ELM 예측기를 이용한 에너지 효율 예측

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염찬욱 김동현 곽근창 김원배 조금배
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Extreme Learning Machine TSK Fuzzy Rule Random Clustering Predictor
This study suggests an ELM model that is based on a TSK fuzzy model and compares its performance projection with the existing ELM model. The TSK based ELM model replaces the in the existing model with a linear function. Additionally, the center of the cluster is haphazardly set. The Weighted value between the hidden layer and input is nonexistent whereas the weighted value between the hidden layer and output apply a linear equation. In order to evaluate the performance of TSK - based ELM predictor, we compared the performance of existing ELM predictor with the energy efficiency problem using building cooling and heating load prediction data. In conclusion, the TSK based ELM model outperformed the current ELM model in performance projection.
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