Automated Author ProfileFernandes, Diego Simões
Fernandes, Diego Simões
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 0.7 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Abstract The objective of this work was to evaluate the performance of five models for estimating solar radiation based on temperature data for dry and wet periods in Goiás State. Climate data from 10 municipalities were used. The models performance for calibration and validation were evaluated by coefficient of determination (R2), root mean square error (RMSE), mean square relative error (RRMSE), the mean absolute error (MAE) and efficiency of model by the Nash-Sutcliff method (EF). Also, the models performance considering all data set for daily and monthly estimated solar radiation were evaluated by Willmott’s agreement coefficient, Camargo’s confidence index, spline smoothing cubic regression and linear regression. It was observed that HG and DCBB models showed the worst performance and CD and DB models the best performance for estimating solar radiation values for Goiás State.
Authors
- Fernandes, Diego Simões ;
- Heinemann, Alexandre Bryan ;
- Amorim, André De Oliveira ;
- Rosidalva Lopes Feitosa Da Paz
Abstract The objective of this work was to evaluate the performance of five models for estimating solar radiation based on temperature data for dry and wet periods in Goiás State. Climate data from 10 municipalities were used. The models performance for calibration and validation were evaluated by coefficient of determination (R2), root mean square error (RMSE), mean square relative error (RRMSE), the mean absolute error (MAE) and efficiency of model by the Nash-Sutcliff method (EF). Also, the models performance considering all data set for daily and monthly estimated solar radiation were evaluated by Willmott’s agreement coefficient, Camargo’s confidence index, spline smoothing cubic regression and linear regression. It was observed that HG and DCBB models showed the worst performance and CD and DB models the best performance for estimating solar radiation values for Goiás State.
Authors
- Fernandes, Diego Simões ;
- Heinemann, Alexandre Bryan ;
- Amorim, André De Oliveira ;
- Rosidalva Lopes Feitosa Da Paz