Development of Precipitation Forecast Model Based on Artificial Intelligence and Subseasonal Clustering-Reference-Cited by-同舟云学术

Development of Precipitation Forecast Model Based on Artificial Intelligence and Subseasonal Clustering

Published:2019-12 Issue:12 Volume:24 Page:04019053
ISSN:1084-0699
Container-title:Journal of Hydrologic Engineering
language:en
Short-container-title:J. Hydrol. Eng.

Author:

Parviz Laleh¹,Rasouli Kabir²^ORCID

Affiliation:

1. Assistant Professor, Faculty of Agriculture, Azarbaijan Shahid Madani Univ., Tabriz 53714-161, Iran.

2. Research Physical Scientist, Dept. of Geoscience, Univ. of Calgary, 2500 University Dr. NW, Calgary, AB, Canada T2N 1N4 (corresponding author). ORCID: .

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.1943-5584.0001862

Reference68 articles.

1. Comparison of Multivariate Regression and Artificial Neural Networks for Peak Urban Water-Demand Forecasting: Evaluation of Different ANN Learning Algorithms

2. Characteristics of seasonal precipitation isotope variability in Indonesia

3. Pattern Recognition with Fuzzy Objective Function Algorithms

4. Mixture model tests of cluster analysis: Accuracy of four agglomerative hierarchical methods.

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