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Alharbi, Yassir ORCID: 0000-0001-6764-030X, Arribas-Bel, Daniel ORCID: 0000-0002-6274-1619 and Coenen, Frans ORCID: 0000-0003-1026-6649 (2023) Forecasting the UN Sustainable Development Goals. In: Communications in Computer and Information Science. Communications in Computer and Information Science, 1854 C . Springer Nature Switzerland, pp. 88-110. ISBN 9783031373190

Alharbi, Yassir ORCID: 0000-0001-6764-030X, Arribas-Be, Daniel and Coenen, Frans ORCID: 0000-0003-1026-6649 (2019) Sustainable Development Goal Attainment Prediction: A Hierarchical Framework using Time Series Modelling. In: 11th International Conference on Knowledge Discovery and Information Retrieval, 2019-9-17 - 2019-9-19.

Coenen, Frans ORCID: 0000-0003-1026-6649, Arribas-Bel, Dan ORCID: 0000-0002-6274-1619 and Alharbi, Yassir ORCID: 0000-0001-6764-030X (2021) Sustainable Development Goal Relational Modelling and Prediction: Introducing The SDG-CAP-EXT Methodology. Journal of Data Intelligence.

Coenen, Frans ORCID: 0000-0003-1026-6649, Alharbi, Yassir ORCID: 0000-0001-6764-030X and Arribas-Bel, Daniel ORCID: 0000-0002-6274-1619 (2020) Sustainable Development Goal Relational Modelling: Introducing the SDG-CAP Methodology. In: International Conference on Big Data Analytics and Knowledge Discovery, 2020-9-14 - 2020-9-17, Bratislava, Slovakia.

Alharbi, Yassir ORCID: 0000-0001-6764-030X, Coenen, frans ORCID: 0000-0003-1026-6649 and Arribas-Bel, Daniel ORCID: 0000-0002-6274-1619 (2020) Sustainable Development Goal Relational Modelling: Introducing the SDG-RMF Methodology. [Internet Publication]

Alharbi, Yassir ORCID: 0000-0001-6764-030X (2023) Sustainable Development Goals Attainment Prediction: A Hierarchical Framework using Time Series Modelling. Doctor of Philosophy thesis, University of Liverpool.

Alharbi, Yassir ORCID: 0000-0001-6764-030X, Arribas-Bel, Daniel ORCID: 0000-0002-6274-1619 and Coenen, Frans ORCID: 0000-0003-1026-6649 (2021) Sustainable Development Goals Monitoring and Forecasting using Time Series Analysis. In: 2nd International Conference on Deep Learning Theory and Applications, 2021-7-7 - 2021-7-9.