{rfName}
Es

Indexed in

License and use

Citations

Altmetrics

Grant support

The Universidad de Valladolid supported this study with the predoctoral contracts of 2020, co-funded by Santander Bank. This work has been financed also by the Spanish Ministry of Science and Innovation, under project PID2020-113533RB-C33. The Universidad de Valladolid also supported this study with ERASMUS+ KA-107. Finally, we have to thank the MOVILIDAD DE DOCTORANDOS Y DOCTORANDAS UVa 2023 from the University of Valladolid.

Analysis of institutional authors

Mateo-Romero, Hector FelipeCorresponding Author

Share

March 11, 2025
Publications
>
Proceedings Paper
No

Estimation of the Performance of Photovoltaic Cells by Means of an Adaptative Neural Fuzzy Inference Model

Publicated to:Communications in Computer and Information Science. 1938 174-188 - 2024-01-01 1938(), DOI: 10.1007/978-3-031-52517-9_12

Authors: Mateo-Romero, Hector Felipe; Carbono dela Rosa, Mario Eduardo; Hernandez-Callejo, Luis; Gonzalez-Rebollo, Miguel Angel; Cardenoso-Payo, Valentin; Alonso-Gomez, Victor; Martinez-Sacristan, Oscar; Gallardo-Saavedra, Sara

Affiliations

Univ Nacl Autonoma Mexico, Mexico City, DF, Mexico - Author
Univ Valladolid, Valladolid, Spain - Author

Abstract

This paper presents an Adaptive Neuro-fuzzy Inference System capable of predicting the output power of photovoltaic cells using their electroluminescence image and their IV curve. The input consists of 3 different features: the number of black pixels, grey pixels and white pixels. ANFIS combines the learning capabilities of Artificial Neural Networks with the comprehensible rules of Fuzzy Logic, being optimal for this problem, as demonstrated by the metrics of MAE of 0.064 and MSE of 0.009, which are better than the performance of other tested methods such as Support Vector Machines or Linear Regressor.

Keywords

AnfiAnfisElectroluminescenceFuzzy logicMachine learningPhotovoltaicSystems

Quality index

Bibliometric impact. Analysis of the contribution and dissemination channel

The work has been published in the journal Communications in Computer and Information Science, Q4 Agency Scopus (SJR), its regional focus and specialization in Computer Science (Miscellaneous), give it significant recognition in a specific niche of scientific knowledge at an international level.

Impact and social visibility

From the perspective of influence or social adoption, and based on metrics associated with mentions and interactions provided by agencies specializing in calculating the so-called "Alternative or Social Metrics," we can highlight as of 2025-07-08:

  • The use of this contribution in bookmarks, code forks, additions to favorite lists for recurrent reading, as well as general views, indicates that someone is using the publication as a basis for their current work. This may be a notable indicator of future more formal and academic citations. This claim is supported by the result of the "Capture" indicator, which yields a total of: 13 (PlumX).

Leadership analysis of institutional authors

This work has been carried out with international collaboration, specifically with researchers from: Mexico.

There is a significant leadership presence as some of the institution’s authors appear as the first or last signer, detailed as follows: First Author (MATEO ROMERO, HECTOR FELIPE) .

the author responsible for correspondence tasks has been MATEO ROMERO, HECTOR FELIPE.