Short-Term Electricity-Load Forecasting Using a TSK-Based Extreme Learning Machine with Knowledge Representation
Abstract
:1. Introduction
2. ELM as an Intelligent Predictor
- Randomly assign hidden node parameters .
- Calculate the hidden-layer output matrix .
- Calculate the output weights using a LSE:
3. Design of TSK-Based ELM for Short-Term Electricity-Load Forecasting
3.1. TSK-ELM Architecture and Knowledge Representation
3.2. TSK-ELM’s Fast Learning and Hybrid-Learning
4. Experimental Results
4.1. Training and Testing Data Sets
4.2. Experiments and Results
5. Conclusions
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Method | No. of Node | RMSE (Training) | RMSE (Testing) |
---|---|---|---|
LR [33] | - | 1044.5 | 928.98 |
RBFN(CFCM) [30] | 100 | 983.64 | 926.43 |
LM [29] | 100 * | 1005.61 | 980.59 |
IRBFN [31] | 450 | 647.10 | 450.60 |
ELM (ReLU) [34] | 260 | 620.35 | 586.11 |
ELM (Sigmoid) [21] | 270 | 451.56 | 438.52 |
ELM (RBF) [21] | 300 | 449.88 | 433.99 |
ELM (sin) [21] | 270 | 443.16 | 435.07 |
TSK-ELM (FCM) | 36 * | 468.79 | 450.60 |
TSK-ELM(SC) | 36 * | 487.38 | 478.79 |
TSK-ELM (without learning) | 36 * | 402. 89 | 400.86 |
TSK-ELM (with learning) | 5 * | 409.31 | 398.58 |
10 * | 359.24 | 349.61 | |
36 * | 292.93 | 331.16 |
Method | No. of Node | MAPE(%)-Training | MAPE(%)-Testing |
---|---|---|---|
ELM (ReLU) [34] | 300 | 2.94 | 2.87 |
ELM (Sig) [21] | 290 | 2.18 | 2.15 |
ELM (RBF) [21] | 300 | 2.23 | 2.19 |
ELM (sin) [21] | 300 | 2.16 | 2.14 |
ANFIS [35] | 36 * | 3.32 | 3.27 |
TSK-ELM (without learning) | 36 * | 2.01 | 1.99 |
TSK-ELM (with learning) | 5 * | 1.96 | 1.95 |
10 * | 1.72 | 1.70 | |
36 * | 1.38 | 1.49 |
Method | No. of Node | MAE(MWh)-Training | MAE (MWh)-Testing |
---|---|---|---|
ELM (ReLU) [34] | 300 | 445.54 | 427.08 |
ELM (Sig) [21] | 290 | 331.06 | 320.69 |
ELM (RBF) [21] | 300 | 338.91 | 326.21 |
ELM (sin) [21] | 300 | 328.71 | 319.18 |
ANFIS [35] | 36 * | 500.84 | 483.11 |
TSK-ELM (without learning) | 36 * | 306.62 | 298.21 |
TSK-ELM (with learning) | 5 * | 300.53 | 292.14 |
10 * | 264.65 | 257.19 | |
36 * | 213.72 | 227.48 |
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Yeom, C.-U.; Kwak, K.-C. Short-Term Electricity-Load Forecasting Using a TSK-Based Extreme Learning Machine with Knowledge Representation. Energies 2017, 10, 1613. https://doi.org/10.3390/en10101613
Yeom C-U, Kwak K-C. Short-Term Electricity-Load Forecasting Using a TSK-Based Extreme Learning Machine with Knowledge Representation. Energies. 2017; 10(10):1613. https://doi.org/10.3390/en10101613
Chicago/Turabian StyleYeom, Chan-Uk, and Keun-Chang Kwak. 2017. "Short-Term Electricity-Load Forecasting Using a TSK-Based Extreme Learning Machine with Knowledge Representation" Energies 10, no. 10: 1613. https://doi.org/10.3390/en10101613