Detecting and Mitigating Adversarial Examples in Regression Tasks: A Photovoltaic Power Generation Forecasting Case Study
With data collected by Internet of Things sensors, deep learning (DL) models can forecast the generation capacity of photovoltaic (PV) power plants. This functionality is especially relevant for PV power operators and users as PV plants exhibit irregular behavior related to environmental conditions....
Main Authors: | Everton Jose Santana, Ricardo Petri Silva, Bruno Bogaz Zarpelão, Sylvio Barbon Junior |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-09-01
|
Series: | Information |
Subjects: | |
Online Access: | https://www.mdpi.com/2078-2489/12/10/394 |
Similar Items
-
Evaluation of Model Quantization Method on Vitis-AI for Mitigating Adversarial Examples
by: Yuta Fukuda, et al.
Published: (2023-01-01) -
Mitigating Overvoltage in Power Grids with Photovoltaic Systems by Energy Storage
by: Landl Sarah, et al.
Published: (2022-01-01) -
Time Series Segmentation Based on Stationarity Analysis to Improve New Samples Prediction
by: Ricardo Petri Silva, et al.
Published: (2021-11-01) -
Survey of Image Adversarial Example Defense Techniques
by: LIU Ruiqi, LI Hu, WANG Dongxia, ZHAO Chongyang, LI Boyu
Published: (2023-12-01) -
ARGAN: Adversarially Robust Generative Adversarial Networks for Deep Neural Networks Against Adversarial Examples
by: Seok-Hwan Choi, et al.
Published: (2022-01-01)