This readme.txt file was generated on <20210526> by GENERAL INFORMATION ------------------- 1. Title of Dataset: Neural network Database 2. Authorship: Research Group Solar and Wind Feasibility Technologies (SWIFT), Electromechanical Engineering Department, Universidad de Burgos, 09006 Burgos, Spain. Name: Cristina Alonso Tristán Institution: Departamento de Ingeniería Electromecánica. Universidad de Burgos Email: catristan@ubu.es ORCID: https://orcid.org/0000-0003-4733-7391 Name: Mª Isabel Dieste Velasco Institution: Departamento de Ingeniería Electromecánica. Universidad de Burgos Email: midieste@ubu.es ORCID: https://orcid.org/0000-0002-2077-2097 Name: Montserrat Diez Mediavilla Institution: Departamento de Ingeniería Electromecánica. Universidad de Burgos Email: mdmr@ubu.es ORCID: https://orcid.org/0000-0002-4957-9530 Name: David González Peña Institution: Departamento de Ingeniería Electromecánica. Universidad de Burgos Email: davidgp@ubu.es ORCID: https://orcid.org/0000-0002-9347-4947 Name: María del Carmen Rodríguez Amigo Institution: Departamento de Matemáticas y Computación. Universidad de Burgos Email: cramigo@ubu.es ORCID: https://orcid.org/0000-0002-4639-4979 Name: Diego Granados López Institution: Departamento de Ingeniería Electromecánica. Universidad de Burgos Email: dgranados@ubu.es ORCID: https://orcid.org/0000-0002-9046-7397 DESCRIPTION ----------- 1. Dataset language: English 2. Abstract: The current Matlab file records a neural network to for CIE standard sky classification. Location: Burgos, Spain. 3. Keywords: Artificial Neural Network; Meteorological Database; Burgos; CIE. 4. Date of data collection From: 01/11/2016 To: 31/03/2020 5. Date of dataset publication August (2021) 6. Geographic location/s of data collection Burgos, Escuela Politécnica Superior. ACCESS INFORMATION ------------------ 1. Dataset Creative Commons License: CC BY-SA 4.0 Documentation, data, examples and other materials, unless otherwise stated inside them or their folder, are licensed under the terms of the CREATIVE COMMENTOS ATTRIBUTION-SHAREALIKE 4.0 INTERNATIONAL LICENSE. Code is also made available under the MIT LICENSE. They are described as follows: CREATIVE COMMONS ATTRIBUTION-SHAREALIKE 4.0 INTERNATIONAL LICENSE This work by Solar and Wind Feasibility Technologies is licensed under CC BY-SA 4.0. To view a copy of this license, visit http://creativecommons.org/licenses/by-sa/4.0/ or send a letter to Creative Commons, PO Box 1866, Mountain View, CA 94042, USA. MIT LICENSE Copyright (c) 2020, Diego Granados López Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. 2. Dataset DOI: 10.36443/10259/5896 (http://doi.org/10.36443/10259/5896) 3. Related publication DOI(1): 10.1016/j.solener.2018.04.028 DOI(2): 10.1016/j.solener.2019.11.060 DOI(3): 10.1016/j.solener.2021.02.039 Please include this references if you plan to use this database: [1] A. Suárez-García, D. Granados-López, D. González-Peña, M. Díez-Mediavilla, and C. Alonso-Tristán, “Seasonal caracterization of CIE standard sky types above Burgos, northwestern Spain.,” Sol. Energy, vol. 169, no. January, pp. 24–33, 2018. [2] A. Suárez García and D. Granados López, D. González Peña, “Benchmarking of meteorological indices for sky cloudiness classification using confusion matrices,” Sol. Energy, vol. 195, no. November 2019, pp. 499–513, 2020. [3] D. Granados López, Suárez-García, A., M. Díez-Mediavilla, C. Alonso-Tristán, "Feature selection for CIE standard sky classification", Sol. Energy, vol 218, pp. 95-107, 2021. METHODOLOGICAL INFORMATION -------------------------- 1. Description of methods used for collection-generation of data: The experimental data for this dataset were gathered at Burgos by the research group:Swift. The experimental equipment : - SONA201D All-Sky Camera-Day from Sieltec Canarias - MS-321LR sky scanner, from EKO -CAMPBELL CR3000 datalogger The sky-scanner (EKO) completes a full scan in four minutes. FILE OVERVIEW -------------- - ANN_RGB.mat : Artificial Neural Network for CIE Standard sky-classification (RGB color space) TABULAR DATA-SPECIFIC INFORMATION --------------------------------- 1. File List: File: ANN_RGB.mat, size 100.648 KB - net: Neural network structure. - inputs: Image database in RGB format. - outputs: CIE predicted label. - targets: CIE label (from SKy scanner, [1])