Probabilistic estimation of suspended sediment load using quantile regression

Probabilistic estimation of suspended sediment load using quantile regression

碩士 === 國立成功大學 === 水利及海洋工程學系 === 102 === Inevitable scatter existed between suspended sediment discharge is caused by variation in sediment supply. However, The sediment rating curve only describes the average relation between streamflow and suspended sediment. This study aims to construct a probabil...

Full description

Bibliographic Details
Main Authors:	Ting-JuChen, 陳亭如
Other Authors:	Jenq-Tzong Shiau
Format:	Others
Language:	zh-TW
Published:	2014
Online Access:	http://ndltd.ncl.edu.tw/handle/06154391033629460624

Similar Items

Probabilistic Hourly Load Forecasting Using Additive Quantile Regression Models
by: Caston Sigauke, et al.
Published: (2018-08-01)

Embedding based quantile regression neural network for probabilistic load forecasting
by: Dahua GAN, et al.
Published: (2018-02-01)

Probabilistic Solar Forecasting Using Quantile Regression Models
by: Philippe Lauret, et al.
Published: (2017-10-01)

Feature selection for probabilistic load forecasting via sparse penalized quantile regression
by: Yi Wang, et al.
Published: (2019-01-01)

Estimation of Suspended Sediment Loads Using Copula Functions
by: Nejc Bezak, et al.
Published: (2017-08-01)

Short-term load probabilistic forecasting based on quantile regression convolutional neural network and Epanechnikov kernel density estimation
by: Hui He, et al.
Published: (2020-12-01)

Probabilistic Water Demand Forecasting Using Quantile Regression Algorithms
by: Langousis, A., et al.
Published: (2022)

Day-Ahead Hierarchical Probabilistic Load Forecasting With Linear Quantile Regression and Empirical Copulas
by: Tianhui Zhao, et al.
Published: (2019-01-01)

Suspended Sediment Load Estimation Using Artificial Neural Network
by: Chia-Hsun Yeh, et al.
Published: (2009)

Unified Quantile Regression Deep Neural Network with Time-Cognition for Probabilistic Residential Load Forecasting
by: Zhuofu Deng, et al.
Published: (2020-01-01)

Penalized Estimation for Quantile Regression
by: 吳國傑
Published: (2011)

Smooth regression quantile estimation
by: Yu, Keming
Published: (1996)

Bayesian bootstrap quantile regression for probabilistic photovoltaic power forecasting
by: Mokhtar Bozorg, et al.
Published: (2020-09-01)

Analysis of Suspended Sediment Loads in Streams and Rivers using Linear Regression and Pearson Correlation
by: Sakwe, Chantal Wase
Published: (2015)

Probabilistic prediction for the ampacity of overhead lines using Quantile Regression Neural Network
by: Jin Xu, et al.
Published: (2020-01-01)

Four Factor Model in Taiwan Stock Returns-Quantile Regression
by: Yen-ju Chen, et al.
Published: (2007)

Comparing quantile regression methods for probabilistic forecasting of NO2 pollution levels
by: Sebastien Pérez Vasseur, et al.
Published: (2021-06-01)

Improving Turbidity-Based Estimates of Suspended Sediment Concentrations and Loads
by: Jastram, John Dietrich
Published: (2014)

Estimation of Suspended Sediment Load Using Artificial Intelligence-Based Ensemble Model
by: Vahid Nourani, et al.
Published: (2021-01-01)

Estimation of rubber price returns using quantile regression
by: Kwadwo Agyei Nyantakyi, et al.
Published: (2015-11-01)

The Japanese Taylor rule estimated using censored quantile regressions
by: Chen, Jau-er, et al.
Published: (2016)

Analysis of Monthly Suspended Sediment Load in Rivers and Streams Using Linear Regression and Similar Precipitation Data
by: Echiejile, Faith
Published: (2021)

Linear Regression Analysis of the Suspended Sediment Load in Rivers and Streams Using Data of Similar Precipitation Values
by: Jamison, Jonathan A.
Published: (2018)

quantile regression
by: Shui-mei Huang, et al.
Published: (2006)

Volatility Forecasting with Quantile Regression and Kernel Estimation
by: Wei-Hwa Peng, et al.
Published: (2011)

Probabilistic Forecasting of Wind Turbine Icing Related Production Losses Using Quantile Regression Forests
by: Jennie Molinder, et al.
Published: (2021-12-01)

ON THE ISSUE OF CALCULATION OF THE SUSPENDED SEDIMENT LOAD DISCHARGE
by: Marina V. Shmakova
Published: (2020-02-01)

Estimating the suspended sediment yield in a river network by means of geomorphic parameters and regression relationships
by: S. Grauso, et al.
Published: (2008-01-01)

Improving estimations in quantile regression model with autoregressive errors
by: Yuzbasi Bahadır, et al.
Published: (2018-01-01)

Bayesian parameter estimation and variable selection for quantile regression
by: Reed, Craig
Published: (2011)

Weighted Quantile Regression
by: Lo, Yi, et al.
Published: (2010)

Prediction of Suspended Sediment Load Using Data-Driven Models
by: Rana Muhammad Adnan, et al.
Published: (2019-10-01)

Using Quantile Regression to Estimate Downside Risk forPortfolio Analysis
by: Chien-Hui Wu, et al.
Published: (2011)

Generalized quantile regression
by: Guo, Mengmeng
Published: (2012)

Canonical quantile regression
by: Portnoy, S.
Published: (2022)

Spatial Quantile Regression
by: Grażyna Trzpiot
Published: (2012-12-01)

Estimation of Unmeasured Radon Concentrations in Ohio Using Quantile Regression Forest
by: Bandreddy, Neel Kamal
Published: (2014)

Symmetric Regression Quantile and Its Application to Robust Estimation for the Nonlinear Regression Model
by: Lin, Li-Ching, et al.
Published: (1997)

Gibrat''s Law：Application of Quantile Regression
by: Ting-Wei Chang, et al.
Published: (2004)

Quantile Regression Post-Processing of Weather Forecast for Short-Term Solar Power Probabilistic Forecasting
by: Luca Massidda, et al.
Published: (2018-07-01)