Global solar irradiation prediction using a multi-gene genetic programming approach

@article{Pan2014GlobalSI,
  title={Global solar irradiation prediction using a multi-gene genetic programming approach},
  author={Indranil Pan and Daya Shankar Pandey and Saptarshi Das},
  journal={ArXiv},
  year={2014},
  volume={abs/1403.0623}
}
In this paper, a nonlinear symbolic regression technique using an evolutionary algorithm known as multi-gene genetic programming (MGGP) is applied for a data-driven modelling between the dependent and the independent variables. The technique is applied for modelling the measured global solar irradiation and validated through numerical simulations. The proposed modelling technique shows improved results over the fuzzy logic and artificial neural network (ANN) based approaches as attempted by… 
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References

SHOWING 1-10 OF 56 REFERENCES
A linear genetic programming approach for the prediction of solar global radiation
TLDR
The results indicate that the LGP models give precise estimations of the solar global radiation and significantly outperform traditional angstrom’s model.
Modeling global solar radiation using Particle Swarm Optimization (PSO)
Solar resource estimation using artificial neural networks and comparison with other correlation models
Artificial Neural Network (ANN) based models for estimation of monthly mean daily and hourly values of solar global radiation are presented in this paper. Solar radiation data from 13 stations spread
ANN-based modelling and estimation of daily global solar radiation data: A case study
In this paper, an artificial neural network (ANN) models for estimating and modelling of daily global solar radiation have been developed. The data used in this work are the global irradiation HG,
A new multi-gene genetic programming approach to nonlinear system modeling. Part I: materials and structural engineering problems
This paper presents a new approach for behavioral modeling of structural engineering systems using a promising variant of genetic programming (GP), namely multi-gene genetic programming (MGGP). MGGP
Prediction of monthly mean daily global solar radiation using Artificial Neural Network
In this study, a multilayer feed forward (MLFF) neural network based on back propagation algorithm was developed, trained, and tested to predict monthly mean daily global radiation in Tamil Nadu,
Artificial Neural Network based Prediction of Solar Radiation for Indian Stations
TLDR
An ANN model is developed which can be used to predict solar radiation at any given location in India and it is found that RMSE in the ANN model varies 0.0486–3.562 for Indian region.
...
1
2
3
4
5
...