Performance Evaluation of Various Functions for Kernel Density Estimation

Journals Menu

Follow SCIRP

	customer@scirp.org
	+86 18163351462(WhatsApp)
	1655362766

	Paper Publishing WeChat

Open Journal of Applied Sciences

ISSN Print: 2165-3917
ISSN Online: 2165-3925
www.scirp.org/journal/ojapps
E-mail: ojapps@scirp.org

Google-based Impact Factor: 1
Citations

Journals Menu

"Performance Evaluation of Various Functions for Kernel Density Estimation"
written by Youngsung Soh, Yongsuk Hae, Aamer Mehmood, Raja Hadi Ashraf, Intaek Kim,
published by Open Journal of Applied Sciences, Vol.3 No.1B, 2013

has been cited by the following article(s):

Google Scholar
CrossRef

[1]	Unleashing the power of three-dimensional kernel density estimation for Doppler Velocimeter data despiking
	Measurement, 2024

[2]	Estimation of Finite Population Totals Based on a Robust Nonparametric Feedforward Backpropagation Neural Network
	2024

[3]	CINT City Net-Zero tool: a method to quantitatively assess carbon data in urban areas
	… on Technology and …, 2023

[4]	Predicting the amount of medical waste using kernel-based SVM and deep learning methods for a private hospital in Turkey
	Sustainable Chemistry and Pharmacy, 2023

[5]	Determination of the impacts of urban-planning of the urban land area using GIS hotspot analysis
	… and Electronics in …, 2023

[6]	Human food provisioning impacts the social environment, home range and fitness of a marine top predator
	Animal Behaviour, 2022

[7]	Accessibility of park green space in Wuhan, China: implications for spatial equity in the post-COVID-19 era
	International journal of …, 2022

[8]	Decoupling residents and dispersers from detection data improve habitat selection modelling: the case study of the wolf in a natural corridor
	Ethology Ecology & …, 2022

[9]	A note on density estimation via the hyperbolic secant kernel estimator
	Journal of Information …, 2022

[10]	Motion detection in a color video sequence with an application to monitoring a baby
	Electronic …, 2022

[11]	Improved Data Interpretation through Identification of Time Series Periodicity Changes
	2022

[12]	A New Way of Data Analysis and Rating of the Blood Oxygen Saturation Variability
	2021 IEEE 12th …, 2021

[13]	The Gumbel kernel for estimating the probability density function with application to hydrology data
	Journal of Data, Information …, 2021

[14]	Forecasting risk of crop disease with anomaly detection algorithms
	2021

[15]	Assessment of land degradation using machine‐learning techniques: A case of declining rangelands
	2021

[16]	Generating accurate in silico predictions of acute aquatic toxicity for a range of organic chemicals: Towards similarity-based machine learning methods
	2021

[17]	2.2 Loss Functions for Neural Networks
	Alanis, 2020

[18]	Object Motion Detection Methods for Real-Time Video Surveillance: A Survey with Empirical Evaluation
	2020

[19]	A Kernel Density Estimation Based Loss Function and its Application to ASV-Spoofing Detection
	2020

[20]	Kernel alapú balesetsűrűsödési helyek keresése a gyakorlatban
	2019

[21]	Paragangliomas of the Head and Neck: Local Control and Functional Outcome Following Fractionated Stereotactic Radiotherapy
	2019

[22]	Data‐driven approach for fault detection and isolation in nonlinear system
	International Journal of Adaptive Control and Signal Processing, 2018

[23]	Novel data mining framework for object detection in video surveillance system using cellular logic array
	2018

[24]	Brain Volume Reduction after Whole-Brain Radiotherapy: Quantification and Prognostic Relevance
	Neuro-Oncology, 2017

[25]	Automatic Lane-level Road Network Graph-generation from Floating Car Data
	GI_Forum, 2016

[26]	Revisiting the Distance Duality Relation using a non-parametric regression method
	Journal of Cosmology and Astroparticle Physics, 2016

[27]	Automatic lane-level road network graph-generation from Floating Car Data Page
	2016

[28]	Revisiting the Distance Duality Relation using LOESS and SIMEX
	arXiv preprint arXiv:1511.09223, 2015

[29]	Bridging the gap between anomaly detection and fraud prevention On how to use anomaly detection, visualization, and user-interaction techniques to enable …


[30]	Desarrollo de un algoritmo para detección de anomalías con base en estimación de densidad basada en kernels, matrices de densidad y medidas cuánticas

[1]	Comparison of Different Bandwidth Determination Methods in Kernel Equating Bartın University Journal of Faculty of Education, 2025 DOI:10.14686/buefad.1392156

[2]	Geo-spatial analysis of transit planning for sustainable tourism development in Bangkok, Thailand Journal of Asian Architecture and Building Engineering, 2024 DOI:10.1080/13467581.2024.2366808

[3]	Unleashing the power of three-dimensional kernel density estimation for Doppler Velocimeter data despiking Measurement, 2024 DOI:10.1016/j.measurement.2023.114053

[4]	CINT City Net-Zero Tool: A Method to Quantitatively Assess Carbon Data in Urban Areas 2023 IEEE International Symposium on Technology and Society (ISTAS), 2023 DOI:10.1109/ISTAS57930.2023.10305975

[5]	Determination of the impacts of urban-planning of the urban land area using GIS hotspot analysis Computers and Electronics in Agriculture, 2023 DOI:10.1016/j.compag.2023.107935

[6]	Accessibility of Park Green Space in Wuhan, China: Implications for Spatial Equity in the Post-COVID-19 Era International Journal of Environmental Research and Public Health, 2022 DOI:10.3390/ijerph19095440

[7]	Human food provisioning impacts the social environment, home range and fitness of a marine top predator Animal Behaviour, 2022 DOI:10.1016/j.anbehav.2022.02.005

[8]	Decoupling residents and dispersers from detection data improve habitat selection modelling: the case study of the wolf in a natural corridor Ethology Ecology & Evolution, 2022 DOI:10.1080/03949370.2021.1988724

[9]	A note on density estimation via the hyperbolic secant kernel estimator Journal of Information and Optimization Sciences, 2022 DOI:10.1080/02522667.2022.2084244

[10]	A note on density estimation via the hyperbolic secant kernel estimator Journal of Information and Optimization Sciences, 2022 DOI:10.1080/02522667.2022.2084244

[11]	Generating accurate in silico predictions of acute aquatic toxicity for a range of organic chemicals: Towards similarity-based machine learning methods Chemosphere, 2021 DOI:10.1016/j.chemosphere.2021.130681

[12]	A New Way of Data Analysis and Rating of the Blood Oxygen Saturation Variability 2021 IEEE 12th International Conference on Electronics and Information Technologies (ELIT), 2021 DOI:10.1109/ELIT53502.2021.9501109

[13]	The Gumbel kernel for estimating the probability density function with application to hydrology data Journal of Data, Information and Management, 2021 DOI:10.1007/s42488-021-00058-y

[14]	Forecasting Risk of Crop Disease with Anomaly Detection Algorithms Phytopathology®, 2021 DOI:10.1094/PHYTO-05-20-0185-R

[15]	Smart Systems and IoT: Innovations in Computing Smart Innovation, Systems and Technologies, 2020 DOI:10.1007/978-981-13-8406-6_63

[16]	A Kernel Density Estimation Based Loss Function and Its Application to ASV-Spoofing Detection IEEE Access, 2020 DOI:10.1109/ACCESS.2020.3000641

[17]	Assessment of land degradation using machine‐learning techniques: A case of declining rangelands Land Degradation & Development, 2020 DOI:10.1002/ldr.3794

[18]	Paragangliomas of the Head and Neck American Journal of Clinical Oncology, 2019 DOI:10.1097/COC.0000000000000614

[19]	Paragangliomas of the Head and Neck American Journal of Clinical Oncology, 2019 DOI:10.1097/COC.0000000000000614

[20]	Data-driven approach for fault detection and isolation in nonlinear system International Journal of Adaptive Control and Signal Processing, 2018 DOI:10.1002/acs.2931

[21]	Data‐driven approach for fault detection and isolation in nonlinear system International Journal of Adaptive Control and Signal Processing, 2018 DOI:10.1002/acs.2931

[22]	Brain volume reduction after whole-brain radiotherapy: quantification and prognostic relevance Neuro-Oncology, 2017 DOI:10.1093/neuonc/nox150

[23]	Revisiting the Distance Duality Relation using a non-parametric regression method Journal of Cosmology and Astroparticle Physics, 2016 DOI:10.1088/1475-7516/2016/07/026

Follow SCIRP

	customer@scirp.org
	+86 18163351462(WhatsApp)
	1655362766

	Paper Publishing WeChat

Open Journal of Applied Sciences

Open Journal of Applied Sciences

Journals Menu

Home

About SCIRP

Service

Policies