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Merge branch 'master' of https://github.com/PYFTS/pyFTS

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Petrônio Cândido 2019-05-07 14:06:36 -03:00
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{
"license": "other-open",
"contributors": [
{
"affiliation": "MINDS - Machine Learning and Data Science",
"type": "Researcher",
"name": "Marco Ant\u00f4nio Alves"
},
{
"affiliation": "Federal Institute of Minas Gerais (IFMG), Brazil",
"type": "Researcher",
"name": "Carlos Alberto Severiano Junior"
},
{
"affiliation": "MINDS - Machine Learning and Data Science",
"type": "Researcher",
"name": "Gustavo Linhares Vieira"
},
{
"orcid": "0000-0001-9238-8839",
"affiliation": "Electrical Engineering Dept, Federal University of Minas Gerais (UFMG), Brazil",
"type": "Researcher",
"name": "Frederico Gadelha Guimar\u00e3es"
},
{
"orcid": "0000-0003-2547-3835",
"affiliation": "Federal University of Ouro Preto (UFOP), Brazil",
"type": "Researcher",
"name": "Rodrigo C\u00e9sar Pedrosa Silva"
},
{
"orcid": "0000-0002-0848-9280",
"affiliation": "MINDS - Machine Learning and Data Science",
"type": "Researcher",
"name": "Hossein Javedani Sadaei"
}
],
"language": "eng",
"title": "PYFTS/pyFTS: Stable version 1.6",
"related_identifiers": [
{
"scheme": "url",
"identifier": "https://github.com/PYFTS/pyFTS/tree/pkg1.6",
"relation": "isSupplementTo"
},
{
"scheme": "doi",
"identifier": "10.5281/zenodo.597359",
"relation": "isVersionOf"
}
],
"thesis_university": "Federal University of Minas Gerais (UFMG), Brazil",
"thesis_supervisors": [
{
"orcid": "0000-0001-9238-8839",
"affiliation": "Electrical Engineering Dept, Federal University of Minas Gerais (UFMG), Brazil",
"name": "Frederico Gadelha Guimar\u00e3es"
},
{
"orcid": "0000-0002-0848-9280",
"affiliation": "MINDS - Machine Learning and Data Science",
"name": "Hossein Javedani Sadaei"
}
],
"version": "pkg1.6",
"upload_type": "software",
"keywords": [
"data science",
"time series",
"forecasting",
"fuzzy systems"
],
"publication_date": "2019-05-06",
"creators": [
{
"orcid": "0000-0002-1202-2552",
"affiliation": "IFNMG - Instituto Federal do Norte de Minas Gerais",
"name": "Petr\u00f4nio C\u00e2ndido de Lima e Silva"
},
{
"orcid": "0000-0002-9100-9013",
"affiliation": "IFMG - Instituto Federal de Minas Gerais",
"name": "Carlos Alberto Severiano J\u00fanior"
},
{
"affiliation": "MINDS - Machine Learning and Data Science",
"name": "Marcos Ant\u00f4nio Alves"
},
{
"affiliation": "MINDS - Machine Learning and Data Science",
"name": "Gustavo Linhares Vieira"
},
{
"orcid": "0000-0003-2547-3835",
"affiliation": "UFOP - Universidade Federal de Ouro Preto",
"name": "Rodrigo C\u00e9sar Pedrosa Silva"
},
{
"affiliation": "MINDS - Machine Learning and Data Science",
"name": "Patr\u00edcia Oliveira e Lucas"
},
{
"orcid": "0000-0002-0848-9280",
"affiliation": "MINDS - Machine Learning and Data Science",
"name": "Hossein Javedani Sadaei"
},
{
"orcid": "0000-0001-9238-8839",
"affiliation": "UFMG - Universidade Federal de Minas Gerais",
"name": "Frederico Gadelha Guimar\u00e3es"
}
],
"access_right": "open",
"description": "<p><em><strong>A open source library for Fuzzy Time Series in Python</strong></em>.</p>\n\n<p>For more information:</p>\n\n<ul>\n\t<li>Official site and documentation:<a href=\"https://pyfts.github.io/pyFTS/\"> https://pyfts.github.io/pyFTS/</a></li>\n\t<li>Code repository and issue tracking: <a href=\"https://github.com/PYFTS/pyFTS\">https://github.com/PYFTS/pyFTS</a></li>\n\t<li>A short tutorial on Fuzzy Time&nbsp;Series:\n\t<ul>\n\t\t<li><a href=\"https://towardsdatascience.com/a-short-tutorial-on-fuzzy-time-series-dcc6d4eb1b15\">Part I</a>: Introduction to the Fuzzy Logic, Fuzzy Time Series and the pyFTS library</li>\n\t\t<li><a href=\"https://towardsdatascience.com/a-short-tutorial-on-fuzzy-time-series-part-ii-with-an-case-study-on-solar-energy-bda362ecca6d\">Part II</a>: High order, weighted and multivariate methods and an case study of solar energy forecasting.</li>\n\t\t<li><a href=\"https://towardsdatascience.com/a-short-tutorial-on-fuzzy-time-series-part-iii-69445dff83fb\">Part III</a>: Interval and probabilistic forecasting, non-stationary time series, concept drifts and time variant models.</li>\n\t</ul>\n\t</li>\n\t<li>More example codes: <a href=\"https://github.com/PYFTS/notebooks\">https://github.com/PYFTS/notebooks</a></li>\n</ul>"
}