相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。A mixed formulation of B-spline and a new class of spherical Hankel shape functions for modeling elastostatic problems
M. Mohammadi Nia et al.
APPLIED MATHEMATICAL MODELLING (2020)
Aerodynamic characteristics of Straight-bladed Vertical Axis Wind Turbine with a curved-outline wind gathering device
Yan Li et al.
ENERGY CONVERSION AND MANAGEMENT (2020)
Intelligent design based on holographic model using parametric design method
Xiaojun Liu et al.
JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING (2019)
Ensemble Bayesian forecasting system Part II: Experiments and properties
Henry D. Herr et al.
JOURNAL OF HYDROLOGY (2019)
Two-phase extreme learning machines integrated with the complete ensemble empirical mode decomposition with adaptive noise algorithm for multi-scale runoff prediction problems
Xiaohu Wen et al.
JOURNAL OF HYDROLOGY (2019)
Construction of beam elements considering von Karman nonlinear strains using B-spline wavelet on the interval
Shashank Vadlamani et al.
APPLIED MATHEMATICAL MODELLING (2019)
Digital twin for CNC machine tool: modeling and using strategy
Weichao Luo et al.
JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING (2019)
Electricity consumption probability density forecasting method based on LASSO-Quantile Regression Neural Network
Yaoyao He et al.
APPLIED ENERGY (2019)
A study on short-term power load probability density forecasting considering wind power effects
Yaoyao He et al.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS (2019)
Evaluating Probabilistic Forecasts with scoringRules
Alexander Jordan et al.
JOURNAL OF STATISTICAL SOFTWARE (2019)
A data-driven SVR model for long-term runoff prediction and uncertainty analysis based on the Bayesian framework
Zhongmin Liang et al.
THEORETICAL AND APPLIED CLIMATOLOGY (2018)
Short-term power load probability density forecasting based on Yeo-Johnson transformation quantile regression and Gaussian kernel function
Yaoyao He et al.
ENERGY (2018)
Probability density forecasting of wind power using quantile regression neural network and kernel density estimation
Yaoyao He et al.
ENERGY CONVERSION AND MANAGEMENT (2018)
A full ARMA model for counts with bounded support and its application to rainy-days time series
Sonia Gouveia et al.
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT (2018)
Design and evaluation of SVR, MARS and M5Tree models for 1, 2 and 3-day lead time forecasting of river flow data in a semiarid mountainous catchment
Zhenliang Yin et al.
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT (2018)
Bayesian flood forecasting methods: A review
Shasha Han et al.
JOURNAL OF HYDROLOGY (2017)
A new approach for simulating and forecasting the rainfall-runoff process within the next two months
Mohamad Javad Alizadeh et al.
JOURNAL OF HYDROLOGY (2017)
Short-term power load probability density forecasting method using kernel-based support vector quantile regression and Copula theory
Yaoyao He et al.
APPLIED ENERGY (2017)
Probabilistic Prediction for Monthly Streamflow through Coupling Stepwise Cluster Analysis and Quantile Regression Methods
Y. R. Fan et al.
WATER RESOURCES MANAGEMENT (2016)
Comparison of different configurations of quantile regression in estimating predictive hydrological uncertainty
Manoranjan Muthusamy et al.
12TH INTERNATIONAL CONFERENCE ON HYDROINFORMATICS (HIC 2016) - SMART WATER FOR THE FUTURE (2016)
Modeling and forecasting river flows by means of filtered Poisson processes
Mario Lefebvre et al.
APPLIED MATHEMATICAL MODELLING (2015)
Lower Upper Bound Estimation Method Considering Symmetry for Construction of Prediction Intervals in Flood Forecasting
Hairong Zhang et al.
WATER RESOURCES MANAGEMENT (2015)
Constructing prediction interval for artificial neural network rainfall runoff models based on ensemble simulations
K. S. Kasiviswanathan et al.
JOURNAL OF HYDROLOGY (2013)
Performance evaluation of artificial neural network approaches in forecasting reservoir inflow
M. Taghi Sattari et al.
APPLIED MATHEMATICAL MODELLING (2012)
Estimation of predictive hydrological uncertainty using quantile regression: examples from the National Flood Forecasting System (England and Wales)
A. H. Weerts et al.
HYDROLOGY AND EARTH SYSTEM SCIENCES (2011)
River flow time series using least squares support vector machines
R. Samsudin et al.
HYDROLOGY AND EARTH SYSTEM SCIENCES (2011)
An empirical method to improve the prediction limits of the GLUE methodology in rainfall-runoff modeling
Lihua Xiong et al.
JOURNAL OF HYDROLOGY (2008)
Real-time probabilistic forecasting of flood stages
Shien-Tsung Chen et al.
JOURNAL OF HYDROLOGY (2007)
Probabilistic forecasts, calibration and sharpness
Tilmann Gneiting et al.
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY (2007)
Strictly proper scoring rules, prediction, and estimation
Tilmann Gneiting et al.
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION (2007)
Using support vector machines for long-term discharge prediction
Jian-Yi Lin et al.
HYDROLOGICAL SCIENCES JOURNAL (2006)
Assessment of flood forecasting lead time based on generalized likelihood uncertainty estimation approach
A. Heidari et al.
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT (2006)
Using quantile regression to extend an existing wind power forecasting system with probabilistic forecasts
HA Nielsen et al.
WIND ENERGY (2006)
Local linear additive quantile regression
KM Yu et al.
SCANDINAVIAN JOURNAL OF STATISTICS (2004)
Detecting determinism and nonlinearity in riverflow time series
A Porporato et al.
HYDROLOGICAL SCIENCES JOURNAL-JOURNAL DES SCIENCES HYDROLOGIQUES (2003)
Backpropagation of pseudoerrors: Neural networks that are adaptive to heterogeneous noise
ADA Ding et al.
IEEE TRANSACTIONS ON NEURAL NETWORKS (2003)
Bayesian system for probabilistic river stage forecasting
R Krzysztofowicz
JOURNAL OF HYDROLOGY (2002)