Neural Network Modelling Applied to Flat-Plate Solar Collectors

1. Introduction

Rising energy costs have renewed interest in the efficient utilisation of flat-plate solar collectors within industrial automation. The approach integrates neural network modelling with experimental calibration to improve predictive accuracy. The model reproduces the field observations satisfactorily for all 4 of the sites investigated. The proposed method is simple enough for routine use by practising engineers.

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2. Materials and Methods

The method is described in the printed article, of which the PDF galley is a faithful rendition.

3. Results and Discussion

Results are reported in full in the PDF, together with the figures and tables referenced above.

4. Conclusion

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