Results 271 to 280 of about 24,713,244 (334)

SolarGAN: Multivariate Solar Data Imputation Using Generative Adversarial Network

IEEE Transactions on Sustainable Energy, 2021
Photovoltaic (PV) is receiving increasing attention due to its sustainability and low carbon footprint. However, the penetration level of PV is still relatively low because of its intermittency. This uncertainty can be handled by accurate PV forecasting,
W. Zhang, Yonghong Luo, Ying Zhang, D. Srinivasan   +3 more
semanticscholar   +1 more source

An Ensemble Method for Data Imputation

2019 IEEE International Conference on Healthcare Informatics (ICHI), 2019
Healthcare analytics is transforming the healthcare industry, finding novel and useful patterns in patient data such as electronic health records (EHRs), to provide patients with improved care and service. Researchers train machine learning (ML) algorithms to discover new knowledge by mining patients’ clinical data to provide better care such as ...
Yichen Ding, W. Nick Street, Ling Tong, Shangguan Wang   +3 more
openaire   +1 more source

A Hybrid Data-Driven Framework for Spatiotemporal Traffic Flow Data Imputation

IEEE Internet of Things Journal, 2022
An accurate estimation of missing data in traffic flow is crucial in urban planning, intelligent transportation, economic geography, and other fields. Thus, improving the data quality of traffic flow is a necessary step in data modeling.
Peixiao Wang, T. Hu, Fei Gao, Ru-Xue Wu, Wei Guo, Xinyan Zhu   +5 more
semanticscholar   +1 more source

Privacy-Preserving Data Imputation

Sixth IEEE International Conference on Data Mining - Workshops (ICDMW'06), 2006
In this paper, we investigate privacy-preserving data imputation on distributed databases. We present a privacy-preserving protocol for filling in missing values using a lazy decision tree imputation algorithm for data that is horizontally partitioned between two parties.
Geetha Jagannathan, Rebecca N. Wright
openaire   +1 more source

Bayesian Kernelized Matrix Factorization for Spatiotemporal Traffic Data Imputation and Kriging

IEEE transactions on intelligent transportation systems (Print), 2022
Missingness and corruption are common problems for real-world traffic data. How to accurately perform imputation and prediction based on incomplete or even sparse traffic data becomes a critical research question in intelligent transportation systems ...
Mengying Lei, A. Labbe, Yuankai Wu, Lijun Sun   +3 more
semanticscholar   +1 more source

Latent Factor Analysis Model With Temporal Regularized Constraint for Road Traffic Data Imputation

IEEE transactions on intelligent transportation systems (Print)
Intelligent Transportation Systems (ITSs) are designed to alleviate traffic congestion and provide convenience for travelers or decision-makers. However, the challenge lies in obtaining complete and accurate traffic data because of various factors ...
Hengshuo Yang, Mingwei Lin, Hong Chen, Xin Luo, Zeshui Xu   +4 more
semanticscholar   +1 more source

Diffusion Models for Tabular Data Imputation and Synthetic Data Generation

ACM Transactions on Knowledge Discovery from Data
Data imputation and data generation have important applications across many domains where incomplete or missing data can hinder accurate analysis and decision-making.
Mario Villaizán-Vallelado, Matteo Salvatori, Carlos Segura, Ioannis Arapakis   +3 more
semanticscholar   +1 more source

LLM-Forest: Ensemble Learning of LLMs with Graph-Augmented Prompts for Data Imputation

Annual Meeting of the Association for Computational Linguistics
Missing data imputation is a critical challenge in various domains, such as healthcare and finance, where data completeness is vital for accurate analysis.
Xinrui He, Yikun Ban, Jiaru Zou, Tianxin Wei, Curtiss B. Cook, Jingrui He   +5 more
semanticscholar   +1 more source

Graph Spectral Regularized Tensor Completion for Traffic Data Imputation

IEEE transactions on intelligent transportation systems (Print), 2021
In intelligent transportation systems (ITS), incomplete traffic data due to sensor malfunctions and communication faults, seriously restricts the related applications of ITS. Recovering missing data from incomplete traffic data becomes an important issue
Lei Deng, Xiao-Yang Liu, Haifeng Zheng, Xinxin Feng, Youjia Chen   +4 more
semanticscholar   +1 more source

A Comprehensive Survey on Traffic Missing Data Imputation

IEEE transactions on intelligent transportation systems (Print)
Intelligent Transportation Systems (ITS) are essential and play a key role in improving road safety, reducing congestion, optimizing traffic flow and facilitating the development of smart cities.
Yimei Zhang, Xiangjie Kong, Wenfeng Zhou, Jin Liu, Yanjie Fu, Guojiang Shen   +5 more
semanticscholar   +1 more source