{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:39:54Z","timestamp":1760240394115,"version":"build-2065373602"},"reference-count":41,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2019,5,31]],"date-time":"2019-05-31T00:00:00Z","timestamp":1559260800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>The complexity of solar radiation fluctuations received on the ground is nowadays of great interest for solar resource in the context of climate change and sustainable development. Over tropical maritime area, there are small inhabited islands for which the prediction of the solar resource at the daily and infra-daily time scales are important to optimize their solar energy systems. Recently, studies show that the theory of the information is a promising way to measure the solar radiation intermittency. Kolmogorov complexity (KC) is a useful tool to address the question of predictability. Nevertheless, this method is inaccurate for small time series size. To overcome this drawback, a new encoding scheme is suggested for converting hourly solar radiation time series values into a binary string for calculation of Kolmogorov complexity (KC-ES). To assess this new approach, we tested this method using the 2004\u20132006 satellite hourly solar data for the western part of the Indian Ocean. The results were compared with the algorithmic probability (AP) method which is used as the benchmark method to compute the complexity for short string. These two methods are a new approach to compute the complexity of short solar radiation time series. We show that KC-ES and AP methods give comparable results which are in agreement with the physical variability of solar radiation. During the 2004\u20132006 period, an important interannual SST (sea surface temperature) anomaly over the south of Mozambique Channel encounters in 2005, a strong MJO (Madden\u2013Julian oscillation) took place in May 2005 over the equatorial Indian Ocean, and nine tropical cyclones crossed the western part of the Indian Ocean in 2004\u20132005 and 2005\u20132006 austral summer. We have computed KC-ES of the solar radiation time series for these three events. The results show that the Kolmogorov complexity with suggested encoding scheme (KC-ES) gives competitive measure of complexity in regard to the AP method also known as Solomonoff probability.<\/jats:p>","DOI":"10.3390\/e21060552","type":"journal-article","created":{"date-parts":[[2019,5,31]],"date-time":"2019-05-31T11:59:56Z","timestamp":1559303996000},"page":"552","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Algorithmic Probability Method Versus Kolmogorov Complexity with No-Threshold Encoding Scheme for Short Time Series: An Analysis of Day-To-Day Hourly Solar Radiation Time Series over Tropical Western Indian Ocean"],"prefix":"10.3390","volume":"21","author":[{"given":"Miloud","family":"Bessafi","sequence":"first","affiliation":[{"name":"Faculty of Sciences and Technology, University of La R\u00e9union, Laboratoire d\u2019Energ\u00e9tique, d\u2019Electronique et Proc\u00e9d\u00e9s, 15 Avenue Ren\u00e9 Cassin, Sainte-Clotilde, 97715 La R\u00e9union, France"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8380-1844","authenticated-orcid":false,"given":"Dragutin T.","family":"Mihailovi\u0107","sequence":"additional","affiliation":[{"name":"Faculty of Agriculture, University of Novi Sad, Dositej Obradovic Sq. 8, 21000 Novi Sad, Serbia"},{"name":"ACIMSI\u2014Center for Meteorology and Environmental Modeling, University of Novi Sad, 21000 Novi Sad, Serbia"}]},{"given":"Peng","family":"Li","sequence":"additional","affiliation":[{"name":"Faculty of Sciences and Technology, University of La R\u00e9union, Laboratoire d\u2019Energ\u00e9tique, d\u2019Electronique et Proc\u00e9d\u00e9s, 15 Avenue Ren\u00e9 Cassin, Sainte-Clotilde, 97715 La R\u00e9union, France"}]},{"given":"Anja","family":"Mihailovi\u0107","sequence":"additional","affiliation":[{"name":"ACIMSI\u2014Center for Meteorology and Environmental Modeling, University of Novi Sad, 21000 Novi Sad, Serbia"}]},{"given":"Jean-Pierre","family":"Chabriat","sequence":"additional","affiliation":[{"name":"Faculty of Sciences and Technology, University of La R\u00e9union, Laboratoire d\u2019Energ\u00e9tique, d\u2019Electronique et Proc\u00e9d\u00e9s, 15 Avenue Ren\u00e9 Cassin, Sainte-Clotilde, 97715 La R\u00e9union, France"}]}],"member":"1968","published-online":{"date-parts":[[2019,5,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2254","DOI":"10.1016\/j.rser.2017.08.066","article-title":"Forecasting daily global solar irradiance generation using machine learning","volume":"82","author":"Sharma","year":"2018","journal-title":"Renew. 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