394 + "display_name": "Python 3 (ipykernel)", 395 + "language": "python", 396 + "name": "python3" 397 + }, 398 + "language_info": { 399 + "codemirror_mode": { 400 + "name": "ipython", 401 + "version": 3 402 + }, 403 + "file_extension": ".py", ...
Figure 4. The flowchart of the PSO algorithm. Since the time interval of control equipment (e.g., blowers and pumps) in the AAO process is 30 min, the control time step Δ𝑡=30 minΔt=30 min. The proposed optimization model was developed in Python. The algorithm parameter configuratio...
Applying wavelets to short-term load forecasting using PSO-based neural networks. IEEE Trans. Power Syst. 2009, 24, 20–27. [CrossRef] 30. Kodogiannis, V.S.; Amina, M.; Petrounias, I. A clustering-based fuzzy wavelet neural network model for short-term load forecasting. Int. J. ...
Applying wavelets to short-term load forecasting using PSO-based neural networks. IEEE Trans. Power Syst. 2009, 24, 20–27. [Google Scholar] [CrossRef] Kodogiannis, V.S.; Amina, M.; Petrounias, I. A clustering-based fuzzy wavelet neural network model for short-term load forecasting. ...
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