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Explainability of a Deep Neural Network Model for Prediction of Solar Panels Generation: Comparative Study Cover

Explainability of a Deep Neural Network Model for Prediction of Solar Panels Generation: Comparative Study

Journal of Automation, Mobile Robotics and Intelligent Systems
Volume 20 (2026): Issue 1 (March 2026)
By: ,   and    
Open Access
|Mar 2026
Figures & tables

Figures & Tables

Figure 1.

Model architecture

Figure 2.

Explanation obtained with LIME

Figure 3.

Explanation obtained with SHAP

Figure 4.

Explanation obtained with Integrated Gradients

Figure 5.

Explanation obtained with Saliency Maps

Figure 6.

Fidelity values of methods

Figure 7.

Method Continuity Values

DOI: https://doi.org/10.14313/jamris-2026-008 | Journal eISSN: 2080-2145 | Journal ISSN: 1897-8649
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Language: English
Page range: 79 - 84
Submitted on: Apr 13, 2024
Accepted on: Jan 24, 2025
Published on: Mar 31, 2026
Published by: Łukasiewicz Research Network – Industrial Research Institute for Automation and Measurements PIAP
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
LIME,
SHAP,
Integrated Gradients,
Time Series Saliency
Related subjects:
Computer sciences,
Artificial intelligence,
Engineering,
Electrical engineering,
Control engineering, metrology and testing,
Mechanical engineering,
Fundamentals of mechanical engineering

© 2026 Rosalís Amador García, María Matilde García Lorenzo, Rafael E. Bello Pérez, published by Łukasiewicz Research Network – Industrial Research Institute for Automation and Measurements PIAP
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.

Volume 20 (2026): Issue 1 (March 2026)
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