Forecasting Evaporative Loss by Least-Square Support-Vector Regression and Evaluation with Genetic Programming, Gaussian Process, and Minimax Probability Machine Regression: Case Study of Brisbane City-Reference-Cited by-同舟云学术

Forecasting Evaporative Loss by Least-Square Support-Vector Regression and Evaluation with Genetic Programming, Gaussian Process, and Minimax Probability Machine Regression: Case Study of Brisbane City

Published:2017-06 Issue:6 Volume:22 Page:05017003
ISSN:1084-0699
Container-title:Journal of Hydrologic Engineering
language:en
Short-container-title:J. Hydrol. Eng.

Author:

Deo Ravinesh C.¹^ORCID,Samui Pijush²

Affiliation:

1. Senior Lecturer, School of Agricultural, Computational and Environmental Sciences, International Centre for Applied Climate Sciences, Institute of Agriculture and Environment, Univ. of Southern Queensland, Springfield, QLD 4300, Australia (corresponding author). ORCID: .

2. Associate Professor, Dept. of Civil Engineering, NIT Patna, Bihar 800005, India.

Publisher

American Society of Civil Engineers (ASCE)

Subject

General Environmental Science,Water Science and Technology,Civil and Structural Engineering,Environmental Chemistry

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29HE.1943-5584.0001506

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