Hyperparameters of Baseline Models for Energy Forecasting

Hyperparameters for ten baseline models evaluated in a study proposing a DG-LSTM-SA network for power generation and load demand forecasting. The dataset, authored by Guoqiang Sun and uploaded to figshare, is a 5.5 KB Excel file last updated on June 3, 2026. The models were tested on three real-world energy datasets: NEPOOL, Yichang, and Solar-Energy.

Use Cases

• Benchmarking new forecasting models against established baselines based on the listed hyperparameters.
• Reproducing the comparative study results from the associated research paper.
• Analyzing the relationship between model configuration and performance in energy prediction tasks.
• Training educational models on energy forecasting using documented baseline settings.

Strengths

• Hyperparameters are documented for ten distinct baseline models, providing a comparative foundation.
• The dataset is associated with a published research methodology evaluated on three real-world datasets.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• The dataset's small size (5.5 KB) suggests it contains only configuration parameters, not raw time-series data.

Provenance

Source

Guoqiang Sun

Collection Method

Likely extracted or defined as part of a machine learning research project.

Freshness

Last updated 2026-06-03 17:32:02; freshness should be verified.