Environmental investment prediction using extended belief rule-based system and evidential reasoning rule
نویسندگان
چکیده
A scientific environmental investment prediction plays a crucial role in controlling pollution and avoiding the blind of management. However effective usually has to fact three challenges about diversiform indicators, insufficient data, reliability models. In present study, new model is proposed using extended belief rule-based system (EBRBS) evidential reasoning (ER) rule, called ensemble EBRBS model, with aim overcome above for better prediction. The consists two components: 1) multiple EBRBSs, which are constructed on basis not only various feature selection methods select representative indicators but also data increment transformation enrich training data; 2) an ER combination method, utilizes rule accommodate weights reliabilities different EBRBSs predicted outputs these have integrated detailed case study then provided validating via extensive experimental comparison analysis based real-world 25 31 provinces China ranged from 2005 2018. results demonstrate that can be used as accurately predict investments. More importantly, obtains high accuracy than some existing models, excellent robustness compared others under situations excessive data.
منابع مشابه
Evidential reasoning rule for evidence combination
Article history: Received 26 January 2013 Received in revised form 9 September 2013 Accepted 13 September 2013 Available online 23 September 2013
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ژورنال
عنوان ژورنال: Journal of Cleaner Production
سال: 2021
ISSN: ['0959-6526', '1879-1786']
DOI: https://doi.org/10.1016/j.jclepro.2020.125661