Regression using hybrid Bayesian networks: modelling landscape - socioeconomy relationships
Modelling environmental systems becomes a challenge when dealing directly with continuous and discrete data simultaneously. The aim in regression is to give a prediction of a response variable given the value of some feature variables. Multiple linear regression models, commonly used in environmenta...
| Main Authors: | , , , |
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| Format: | info:eu-repo/semantics/article |
| Language: | English |
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Elsevier
2024
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| Subjects: | |
| Online Access: | http://hdl.handle.net/10835/14997 |
| _version_ | 1789406638016299008 |
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| author | Fernández Ropero, Rosa María Aguilera Aguilera, Pedro Fernández Álvarez, Antonio Rumí Rodríguez, Rafael |
| author_facet | Fernández Ropero, Rosa María Aguilera Aguilera, Pedro Fernández Álvarez, Antonio Rumí Rodríguez, Rafael |
| author_sort | Fernández Ropero, Rosa María |
| collection | DSpace |
| description | Modelling environmental systems becomes a challenge when dealing directly with continuous and discrete data simultaneously. The aim in regression is to give a prediction of a response variable given the value of some feature variables. Multiple linear regression models, commonly used in environmental science, have a number of limitations: (1) all feature variables must be instantiated to obtain a prediction, and (2) the inclusion of categorical
variables usually yields more complicated models. Hybrid Bayesian networks are an appropriate approach to solve regression problems without such limitations, and they also provide additional advantages. This methodology
is applied to modelling landscape - socioeconomy relationships for different types of data (continuous, discrete or hybrid). Three models relating socioeconomy and landscape are proposed, and two scenarios of socioeconomic
change are introduced in each one to obtain a prediction. This proposal can be easily applied to other areas in environmental modelling. |
| format | info:eu-repo/semantics/article |
| id | oai:repositorio.ual.es:10835-14997 |
| institution | Universidad de Cuenca |
| language | English |
| publishDate | 2024 |
| publisher | Elsevier |
| record_format | dspace |
| spelling | oai:repositorio.ual.es:10835-149972024-01-09T11:50:41Z Regression using hybrid Bayesian networks: modelling landscape - socioeconomy relationships Fernández Ropero, Rosa María Aguilera Aguilera, Pedro Fernández Álvarez, Antonio Rumí Rodríguez, Rafael Continuous Bayesian Networks Mixtures of Truncated Exponentials Regression, Landscape Socioeconomic Structure Modelling environmental systems becomes a challenge when dealing directly with continuous and discrete data simultaneously. The aim in regression is to give a prediction of a response variable given the value of some feature variables. Multiple linear regression models, commonly used in environmental science, have a number of limitations: (1) all feature variables must be instantiated to obtain a prediction, and (2) the inclusion of categorical variables usually yields more complicated models. Hybrid Bayesian networks are an appropriate approach to solve regression problems without such limitations, and they also provide additional advantages. This methodology is applied to modelling landscape - socioeconomy relationships for different types of data (continuous, discrete or hybrid). Three models relating socioeconomy and landscape are proposed, and two scenarios of socioeconomic change are introduced in each one to obtain a prediction. This proposal can be easily applied to other areas in environmental modelling. 2024-01-09T11:50:41Z 2024-01-09T11:50:41Z 2014 info:eu-repo/semantics/article R.F.Ropero, P.A.Aguilera, A. Fernández, R. Rumí. Regression using hybrid Bayesian networks: Modelling landscape-socioeconomy relationships. Environmental Modelling & Software, 57. pag. 127-137 http://hdl.handle.net/10835/14997 en https://www.sciencedirect.com/science/article/pii/S136481521400067X Attribution-NonCommercial-NoDerivatives 4.0 Internacional http://creativecommons.org/licenses/by-nc-nd/4.0/ info:eu-repo/semantics/openAccess Elsevier |
| spellingShingle | Continuous Bayesian Networks Mixtures of Truncated Exponentials Regression, Landscape Socioeconomic Structure Fernández Ropero, Rosa María Aguilera Aguilera, Pedro Fernández Álvarez, Antonio Rumí Rodríguez, Rafael Regression using hybrid Bayesian networks: modelling landscape - socioeconomy relationships |
| title | Regression using hybrid Bayesian networks: modelling landscape - socioeconomy relationships |
| title_full | Regression using hybrid Bayesian networks: modelling landscape - socioeconomy relationships |
| title_fullStr | Regression using hybrid Bayesian networks: modelling landscape - socioeconomy relationships |
| title_full_unstemmed | Regression using hybrid Bayesian networks: modelling landscape - socioeconomy relationships |
| title_short | Regression using hybrid Bayesian networks: modelling landscape - socioeconomy relationships |
| title_sort | regression using hybrid bayesian networks: modelling landscape - socioeconomy relationships |
| topic | Continuous Bayesian Networks Mixtures of Truncated Exponentials Regression, Landscape Socioeconomic Structure |
| url | http://hdl.handle.net/10835/14997 |
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