Predicting calorific value through proximate analysis of municipal solid waste using soft computing system
Abstract This study investigated the accurate prediction of the calorific value of municipal solid waste (MSW) using soft computing systems, namely artificial neural networks (ANN), adaptive neural fuzzy inference system (ANFIS), support vector machine (SVM), and multi-layer perceptron (MLP). Calori...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-03-01
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| Series: | Discover Applied Sciences |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s42452-025-06643-9 |
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