AIMC Topic: Solid Waste

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Verifying the performance of artificial neural network and multiple linear regression in predicting the mean seasonal municipal solid waste generation rate: A case study of Fars province, Iran.

Waste management (New York, N.Y.) Oct 9, 2015
Predicting the mass of solid waste generation plays an important role in integrated solid waste management plans. In this study, the performance of two predictive models, Artificial Neural Network (ANN) and Multiple Linear Regression (MLR) was verifi...
Neural Networks, Computer Models, Theoretical Regression Analysis Seasons Iran Multivariate Analysis Solid Waste Waste Management
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Machine learning predicting sintering temperature for ceramsite production from multiple solid wastes.

Waste management (New York, N.Y.) Jul 15, 2025
An efficient machine learning model was developed to accurately predict the sintering temperature of ceramsite synthesized from various solid waste materials. Based on experimental data from 236 samples, eight key chemical components were defined as ...
Machine Learning Temperature Hot Temperature Solid Waste Ceramics
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