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| Type: | Resource | |
| Storage: | The size of this resource is 199.6 KB | |
| Created: | Apr 28, 2020 at 12:07 a.m. | |
| Last updated: | Apr 28, 2020 at 12:24 a.m. | |
| DOI: | 10.4211/hs.203aa39e82b9423684e754a001530b71 | |
| Citation: | See how to cite this resource |
| Sharing Status: | Published |
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| Views: | 1010 |
| Downloads: | 10 |
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| Comments: | 2 comments |
Abstract
This Resource is created for Homework 5 of CE 59700, course held at 2020 Spring semester in Purdue University. The goal of this homework is to forecast streamflow series by a first order exponential model. USGS gage 03335500, Wabash River at Lafayette, is the target gagee in this homework. Our streamflow forecasting model is built by object-oriented programming skill. The error of prediction is reported with respect to different parameter of model. The further optimization process would be taken in the following class of CE 59700.
Task of HW5 is to split your streamflow dataset into training set and validation set. The prediction made by your model is compared to the validation set split in the beginning. This procedure is known as the training process, which is popular in optimization problem. Create a function to report the mean square error of your model. Fit your model with training set and change alpha value manually. Find the best model which returns the minimum MSE value. Turn in the alpha value and the MSE value you get.
Subject Keywords
Coverage
Spatial
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Additional Metadata
| Name | Value |
|---|---|
| Streamflow | cfs |
| Loss Function | Mean Square Error (MSE) |
| Prediction horizon | 10 days |
| Streamflow forecasting model | First Order Exponential Model |
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
Comments
Pin-Ching Li 3 years, 12 months ago
This is
ReplyPin-Ching Li 3 years, 12 months ago
This is one of the homeworks in CE59700 at 2020 Spring semester in Purdue University.
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