Search Results for author: Xiaoting Wang

Found 14 papers, 4 papers with code

Comparative Analysis of Learning-Based Methods for Transient Stability Assessment

no code implementations3 Sep 2024 Xingjian Wu, Xiaoting Wang, Xiaozhe Wang, Peter E. Caines, Jingyu Liu

Transient stability and critical clearing time (CCT) are important concepts in power system protection and control.

feature selection

From Black Box to Clarity: AI-Powered Smart Grid Optimization with Kolmogorov-Arnold Networks

no code implementations7 Aug 2024 Xiaoting Wang, Yuzhuo Li, Yunwei Li, Gregory Kish

This work is the first to adopt Kolmogorov-Arnold Networks (KAN), a recent breakthrough in artificial intelligence, for smart grid optimizations.

Kolmogorov-Arnold Networks

Movable Frequency Diverse Array-Assisted Covert Communication With Multiple Wardens

no code implementations26 Jul 2024 Zihao Cheng, Jiangbo Si, Zan Li, Pengpeng Liu, Xiaoting Wang, Naofal Al-Dhahir

In particular, when the frequency constraint is strict, MFDA can further increase the covert rate by adjusting the positions of antennas instead of the frequencies.

Efficient Probabilistic Optimal Power Flow Assessment Using an Adaptive Stochastic Spectral Embedding Surrogate Model

no code implementations19 Jan 2024 Xiaoting Wang, Jingyu Liu, Xiaozhe Wang

This paper presents an adaptive stochastic spectral embedding (ASSE) method to solve the probabilistic AC optimal power flow (AC-OPF), a critical aspect of power system operation.

Maximising Quantum-Computing Expressive Power through Randomised Circuits

1 code implementation4 Dec 2023 Yingli Yang, Zongkang Zhang, Anbang Wang, Xiaosi Xu, Xiaoting Wang, Ying Li

This random-circuit approach presents a trade-off between the expressive power of the variational wavefunction and time cost, in terms of the sampling cost of quantum circuits.

A Comparative Study of Polynomial Chaos Expansion-Based Methods for Global Sensitivity Analysis in Power System Uncertainty Control

no code implementations13 Jul 2023 Xiaoting Wang, Rong-Peng Liu, Xiaozhe Wang, François Bouffard

In contrast, the PCE model built using correlated random inputs directly yields the most accurate ANCOVA indices for global sensitivity analysis.

Management

Prompt-Learning for Cross-Lingual Relation Extraction

1 code implementation20 Apr 2023 Chiaming Hsu, Changtong Zan, Liang Ding, Longyue Wang, Xiaoting Wang, Weifeng Liu, Fu Lin, Wenbin Hu

Experiments on WMT17-EnZh XRE also show the effectiveness of our Prompt-XRE against other competitive baselines.

Relation Relation Extraction +1

MT-SNN: Enhance Spiking Neural Network with Multiple Thresholds

no code implementations20 Mar 2023 Xiaoting Wang, Yanxiang Zhang

Spiking neural networks (SNNs) present a promising energy efficient alternative to traditional Artificial Neural Networks (ANNs) due to their multiplication-free operations enabled by binarized intermediate activations.

Binarization

From Static to Dynamic Structures: Improving Binding Affinity Prediction with Graph-Based Deep Learning

1 code implementation19 Aug 2022 Yaosen Min, Ye Wei, Peizhuo Wang, Xiaoting Wang, Han Li, Nian Wu, Stefan Bauer, Shuxin Zheng, Yu Shi, Yingheng Wang, Ji Wu, Dan Zhao, Jianyang Zeng

Here, an MD dataset containing 3, 218 different protein-ligand complexes is curated, and Dynaformer, a graph-based deep learning model is further developed to predict the binding affinities by learning the geometric characteristics of the protein-ligand interactions from the MD trajectories.

Drug Design Drug Discovery

DIWIFT: Discovering Instance-wise Influential Features for Tabular Data

1 code implementation6 Jul 2022 Dugang Liu, Pengxiang Cheng, Hong Zhu, Xing Tang, Yanyu Chen, Xiaoting Wang, Weike Pan, Zhong Ming, Xiuqiang He

Tabular data is one of the most common data storage formats behind many real-world web applications such as retail, banking, and e-commerce.

feature selection

A Sparse Polynomial Chaos Expansion-Based Method for Probabilistic Transient Stability Assessment and Enhancement

no code implementations9 Jun 2022 Jingyu Liu, Xiaoting Wang, Xiaozhe Wang

This paper proposes an adaptive sparse polynomial chaos expansion(PCE)-based method to quantify the impacts of uncertainties on critical clearing time (CCT) that is an important index in transient stability analysis.

A Data-Driven Uncertainty Quantification Method for Stochastic Economic Dispatch

no code implementations16 Sep 2021 Xiaoting Wang, Rong-Peng Liu, Xiaozhe Wang, Yunhe Hou, François Bouffard

This letter proposes a data-driven sparse polynomial chaos expansion-based surrogate model for the stochastic economic dispatch problem considering uncertainty from wind power.

Uncertainty Quantification

Quantum reinforcement learning in continuous action space

no code implementations19 Dec 2020 Shaojun Wu, Shan Jin, Dingding Wen, Donghong Han, Xiaoting Wang

As an application, our method can solve the quantum state-generation problem in a single shot: it only requires a one-shot optimization to generate a model that outputs the desired control sequence for arbitrary target state.

reinforcement-learning Reinforcement Learning +1

A Data-Driven Sparse Polynomial Chaos Expansion Method to Assess Probabilistic Total Transfer Capability for Power Systems with Renewables

no code implementations27 Oct 2020 Xiaoting Wang, Xiaozhe Wang, Hao Sheng, Xi Lin

The increasing uncertainty level caused by growing renewable energy sources (RES) and aging transmission networks poses a great challenge in the assessment of total transfer capability (TTC) and available transfer capability (ATC).

Computational Efficiency

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