Copula Graphical Models for Wind Resource Estimation
Authors: Kalyan Veeramachaneni, Alfredo Cuesta-Infante, Una-May O'Reilly
IJCAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We compare our models with multiple regression methods, where it achieves higher accuracy with less sensing data sometimes with only 3 months. The industry standard method, multiple regression, achieves a reasonable accuracy with 8 months of data, an industry standard period. Thus we achieve better accuracy at a lower cost. We proceed by describing MCP while introducing notation in Section 2. Section 3 describes the real wind resource estimation scenario and the dataset we utilized throughout this paper to demonstrate our methods. Section 4 describes the copula modeling. Section 5 is the demonstration. |
| Researcher Affiliation | Academia | Kalyan Veeramachaneni CSAIL, MIT Cambridge, MA kalyan@csail.mit.edu Alfredo Cuesta-Infante Universidad Rey Juan Carlos Madrid, Spain alfredo.cuesta@urjc.es Una-May O Reilly CSAIL, MIT Cambridge, MA unamay@csail.mit.edu |
| Pseudocode | No | The paper describes methods in detail but does not include any explicitly labeled pseudocode or algorithm blocks. |
| Open Source Code | No | The paper does not contain any statement about releasing source code or provide a link to a code repository. |
| Open Datasets | Yes | We use airport wind data from the public ASOS (Automated Surface Observing System) database for sources of neighboring-site data. |
| Dataset Splits | No | The paper mentions training data (D3, D6, D8) and test data (second year's dataset), but does not explicitly describe a separate validation set split. |
| Hardware Specification | No | The paper does not provide specific details on the hardware used to run the experiments (e.g., GPU/CPU models, memory). |
| Software Dependencies | No | The paper mentions general mathematical packages like "R or Matlab" but does not specify any software dependencies with version numbers. |
| Experiment Setup | No | The paper describes the general approach and comparison of models but does not provide specific experimental setup details such as hyperparameter values, learning rates, or optimizer settings. |