Provincial waste generation prediction using evolutionary-based neuro-fuzzy model: A South Africa case study

Author:

Adeleke Oluwatobi,Jen Tien-Chien

Funder

University of Johannesburg

Publisher

Elsevier BV

Subject

Materials Science (miscellaneous)

Reference40 articles.

1. A machine learning approach for investigating the impact of seasonal variation on physical composition of municipal solid waste;Adeleke;J. Reliab. Intell. Environ.,2022

2. O. Adeleke, S. Akinlabi, T.-C. Jen, and I. Dunmade, “Prediction of Municipal Solid Waste Generation: An Investigation of the effect of clustering techniques and parameters on ANFIS model Performance,” Environ Technol, doi: 10.1080/09593330.2020.1845819.

3. O. Adeleke, S. A. Akinlabi, S. Hassan, and T. Jen, “Predicting the Effect of Seasonal Variation on the Physical Composition of Municipal Solid Waste : A Case Study of the City of Johannesburg”.

4. A hybrid machine-learning model for predicting the waste generation rate of building demolition projects;Cha;J. Clean. Prod.,2022

5. Application of machine learning models to investigate the performance of concrete reinforced with oil palm empty fruit brunch (OPEFB) fibers;Kilani;Asian J. Civil Eng.,2022

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