An Adaptive Wavelet Neural Network-Based Energy Price Forecasting in Electricity Markets

By Naran M. Pindoriya, S. N. Singh, Sanjaykumar Singh. IEEE Transactions on Power Systems, 2008

306 citations recorded by the source corpus.

Subfields: Electrical and Electronic Engineering, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/c605fbc3a36de73a50cf30bda81c53779ce0f03c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Electrical and Electronic Engineering

1. Mahdi Khodayar
2. Jianhui Wang
3. Robert P. Broadwater
4. Jaesung Jung

In Management Science and Operations Research

1. Jacinta Chan Phooi M’ng
2. M. Mehralizadeh

Citations in the corpus

• Forecasting East Asian Indices Futures via a Novel Hybrid of Wavelet-PCA Denoising and Artificial Neural Network Models (2016, background): “Several studies have proved that Wavelet Transform denoising procedures improve the performance of time series forecasting [34, 35].”
• AWNN-Assisted Wind Power Forecasting Using Feed-Forward Neural Network (2012, background): “Due to its symmetry in shape, having explicit expression, and providing an exact time frequency analysis, it has been considered to be the most appropriate mother wavelet function [22], [24].”