Multi-Objective Spiking Neural Network for Optimal Wind Power Prediction Interval-Reference-Cited by-同舟云学术

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Multi-Objective Spiking Neural Network for Optimal Wind Power Prediction Interval

Published:2023-05-21 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE International Symposium on Circuits and Systems (ISCAS)
language:
Short-container-title:

Author:

Chen Yinsong¹,Yu Samson¹,Eshraghian Jason K.²,Lim Chee Peng³

Affiliation:

1. School of Engineering, Deakin University,Melbourne,VIC,Australia

2. University of California,Department of Electrical and Computer Engineering,Santa Cruz,CA,USA

3. Institute for Intelligent Systems Research and Innovation, Deakin University,Melbourne,VIC,Australia

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10181241/10181318/10181537.pdf?arnumber=10181537

Reference27 articles.

1. Memristor-Based Binarized Spiking Neural Networks: Challenges and applications

2. Spiking neural network for nonlinear regression;henkes;ArXiv Preprint,2022

3. A spiking neural network based on temporal encoding for electricity price time series forecasting in deregulated markets

4. Event-Based Vision: A Survey

5. Multi-task learning as multi-objective optimization;sener;Advances in neural information processing systems,2018

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Real-Time Traffic Flow Uncertainty Quantification Based on Nonparametric Probability Density Function Estimation;Journal of Transportation Engineering, Part A: Systems;2024-11

2. A novel interval estimation framework for wind power forecasting using multi-objective gradient descent optimization;Sustainable Energy, Grids and Networks;2024-06

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