Results 1 to 10 of about 23,109 (153)

Probability Interval Prediction of Wind Power Based on KDE Method With Rough Sets and Weighted Markov Chain

IEEE Access, 2018
Research on the uncertainty of wind power has a significant influence on power system planning and decision-making. This paper proposes a novel method for wind power interval forecasting based on rough sets theory, weighted Markov chain, and kernel ...
Xiyun Yang, Xue Ma
exaly   +4 more sources

Support vector data description with kernel density estimation (SVDD-KDE) control chart for network intrusion monitoring

Scientific Reports, 2023
Multivariate control charts have been applied in many sectors. One of the sectors that employ this method is network intrusion detection. However, the issue arises when the conventional control chart faces difficulty monitoring the network-traffic data ...
Muhammad Ahsan, Hidayatul Khusna, Wibawati, Muhammad Hisyam Lee   +3 more
doaj   +2 more sources

Enhancing semantic segmentation in chest X-ray images through image preprocessing: ps-KDE for pixel-wise substitution by kernel density estimation.

PLoS ONE
BackgroundIn medical imaging, the integration of deep-learning-based semantic segmentation algorithms with preprocessing techniques can reduce the need for human annotation and advance disease classification.
Yuanchen Wang, Yujie Guo, Ziqi Wang, Linzi Yu, Yujie Yan, Zifan Gu   +5 more
doaj   +2 more sources

Assessing Urban functional area delineation: POI data and kde analysis in pekanbaru

Computational Urban Science
Accurate delineation of urban spatial extent is essential for planning, yet conventional methods based on land cover and satellite imagery are often time-consuming and may lag behind urban changes.
Zahra Witsqa Maghfira, Ridwan Sutriadi, Ahmad Baikuni Perdana   +2 more
doaj   +2 more sources

Improving classification on imbalanced genomic data via KDE-based synthetic sampling. [PDF]

BioData Min
Class imbalance poses a serious challenge in biomedical machine learning, particularly in genomics, where datasets are characterized by extremely high dimensionality and very limited sample sizes.
Taccaliti E, Aguilar-Ruiz JS.
europepmc   +2 more sources

Smart home economic operation under uncertainty: comparing monte carlo and stochastic optimization using gaussian and KDE-based data

Operations Research Perspectives
This paper investigates optimal day-ahead operation of a building-scale energy hub equipped with photovoltaics and a battery. Electricity demand and PV availability are uncertain and are represented in two ways: (i) thin-tailed normal distributions and ...
Spyros Giannelos, Danny Pudjianto, Goran Strbac   +2 more
doaj   +2 more sources

An Empirical Analysis of KDE-based Generative Models on Small Datasets

Procedia Computer Science, 2021
Ekaterina P. Plesovskaya, Sergey Ivanov
exaly   +2 more sources

Unsupervised Detection of Misinformation in Financial Statements

Proceedings of the International Florida Artificial Intelligence Research Society Conference, 2022
Companies have incentives to hide, omit, or falsify the information reported in financial statements (FS) (e.g., Balance Sheet, Income Statement, Cash Flow Statement) to give a false impression of the company's financial health, assure investors or evade
AKSHADA SHINDE
doaj   +1 more source

Comparison of earthquake-induced shallow landslide susceptibility assessment based on two-category LR and KDE-MLR

Scientific Reports, 2023
Geological hazards caused by strong earthquakes have caused continuous social and economic losses and destruction of the ecological environment in the hazard area, and are mostly manifested in the areas with frequent occurrence of geological hazards or ...
Xinyue Fan, B. Liu, Jie Luo, Ke Pan, Suyue Han, Zhongli Zhou   +5 more
semanticscholar   +1 more source

Location-Based Social Network’s Data Analysis and Spatio-Temporal Modeling for the Mega City of Shanghai, China

ISPRS International Journal of Geo-Information, 2020
The aim of the current study is to analyze and extract the useful patterns from Location-Based Social Network (LBSN) data in Shanghai, China, using different temporal and spatial analysis techniques, along with specific check-in venue categories.
Naimat Ullah Khan, Wanggen Wan, Shui Yu
doaj   +1 more source