Wave energy evolution: Knowledge structure, advancements, challenges and future opportunities
Harnessing energy from ocean waves presents a promising solution to combating global
climate change in the marine environment, significantly contributing to mitigation efforts …
climate change in the marine environment, significantly contributing to mitigation efforts …
Robustness with query-efficient adversarial attack using reinforcement learning
A measure of robustness against naturally occurring distortions is key to safety, success, and
trustworthiness of machine learning models on deployment. We propose an adversarial …
trustworthiness of machine learning models on deployment. We propose an adversarial …
Rl-cam: Visual explanations for convolutional networks using reinforcement learning
Abstract Convolutional Neural Networks (CNNs) are state-of-the-art models for computer
vision tasks such as image classification, object detection, and segmentation. However …
vision tasks such as image classification, object detection, and segmentation. However …
Benchmark generation framework with customizable distortions for image classifier robustness
We present a novel framework for generating adversarial benchmarks to evaluate the
robustness of image classification models. The RLAB framework allows users to customize …
robustness of image classification models. The RLAB framework allows users to customize …
Reinforcement learning for sustainable energy: A survey
K Ponse, F Kleuker, M Fejér, Á Serra-Gómez… - arXiv preprint arXiv …, 2024 - arxiv.org
The transition to sustainable energy is a key challenge of our time, requiring modifications in
the entire pipeline of energy production, storage, transmission, and consumption. At every …
the entire pipeline of energy production, storage, transmission, and consumption. At every …
Reinforcement learning based black-box adversarial attack for robustness improvement
We propose a Reinforcement Learning (RL) based adversarial Black-box attack (RLAB) that
aims at adding minimum distortion to the input iteratively to deceive image classification …
aims at adding minimum distortion to the input iteratively to deceive image classification …
Skip training for multi-agent reinforcement learning controller for industrial wave energy converters
S Sarkar, V Gundecha, S Ghorbanpour… - 2022 IEEE 18th …, 2022 - ieeexplore.ieee.org
Recent Wave Energy Converters (WEC) are equipped with multiple legs and generators to
maximize energy generation. Traditional controllers have shown limitations to capture …
maximize energy generation. Traditional controllers have shown limitations to capture …
Optimization of latching control for duck wave energy converter based on deep reinforcement learning
In the field of wave energy extraction, employing active control strategies amplifies the Wave
Energy Converter's (WEC) response to wave motion. In this regard, a numerical simulation …
Energy Converter's (WEC) response to wave motion. In this regard, a numerical simulation …
[PDF][PDF] Robustness with Black-Box Adversarial Attack using Reinforcement Learning.
A measure of robustness against naturally occurring distortions is key to the safety, success,
and trustworthiness of machine learning models on deployment. We investigate an …
and trustworthiness of machine learning models on deployment. We investigate an …
Function approximation for reinforcement learning controller for energy from spread waves
S Sarkar, V Gundecha, S Ghorbanpour… - arXiv preprint arXiv …, 2024 - arxiv.org
The industrial multi-generator Wave Energy Converters (WEC) must handle multiple
simultaneous waves coming from different directions called spread waves. These complex …
simultaneous waves coming from different directions called spread waves. These complex …