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. 2023 Oct 10;9(10):e20839.
doi: 10.1016/j.heliyon.2023.e20839. eCollection 2023 Oct.

Hybrid wavelet/Elman NN model for short term cost prediction utilizing developed deer hunting optimizer

Xiangqiong Huang  1 , Minling Lai  1 , Huiyi Song  1 , Zhicai Tang  1 , Wenjun Cui  1 , Mahdiyeh Eslami  2   3
Affiliations

Hybrid wavelet/Elman NN model for short term cost prediction utilizing developed deer hunting optimizer

Xiangqiong Huang et al. Heliyon. .

Retraction in

Abstract

The cost signal of electricity in the competitive electrical energy marketplaces is of special importance for all planning and operation activities. Also, the price of electricity has an uncertain nature and various factors affect it in the short and long term. Factors active in the electricity market need to accurately and effectively forecast the electricity price signal to manage risk in the market. For estimating future electricity prices, this research suggests a combined procedure on the basis of Elman neural network model and the wavelet transform. The proposed Elman neural network/wavelet transform forecasted the next hour's power price based on the past 24 h' pricing. This research uses an optimized Elman neural network using a developed deer hunting optimizer and the total model is named Elman neural network/developed deer hunting optimization-wavelet transform. In this paper, Data of Zone Preliminary Billing is used for establishing the training of model and forecasting of performance. The method is then compared with some other published works and the outcomes demonstrate the offered approach superiority toward those for the electrical cost predicting.

Keywords: Developed deer hunting optimization algorithm; Elman neural network; Short term electrical cost forecasting.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

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Fig. 1
Updating the best location Z*.
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Fig. 2
Diagram flowchart of the DDHOA.
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Fig. 3
ENN's basic structure.
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Fig. 4
Structure of using the ENN/IDHO-WT model.
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Fig. 5
Electrical power marketplaces (PJM) regulation Zone Preliminary Billing information.
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Fig. 6
All forecasted findings' comparison outcomes.
See this image and copyright information in PMC

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