Forecasting the status of municipal waste in smart bins using deep learning
The immense growth of the population generates a polluted environment that must be
managed to ensure environmental sustainability, versatility and efficiency in our everyday …
managed to ensure environmental sustainability, versatility and efficiency in our everyday …
[HTML][HTML] Forecasting of municipal solid waste multi-classification by using time-series deep learning depending on the living standard
The type and quantity of municipal solid waste are important factors for determining how
these wastes should be handled, managed, and valorised. This paper investigates the effect …
these wastes should be handled, managed, and valorised. This paper investigates the effect …
Waste management and prediction of air pollutants using IoT and machine learning approach
Increasing waste generation has become a significant issue over the globe due to the rapid
increase in urbanization and industrialization. In the literature, many issues that have a …
increase in urbanization and industrialization. In the literature, many issues that have a …
Forecasting domestic waste generation during successive COVID-19 lockdowns by Bidirectional LSTM super learner neural network
Accurate prediction of domestic waste generation is a challenging task for municipalities to
implement sustainable waste management strategies. In the present study, domestic waste …
implement sustainable waste management strategies. In the present study, domestic waste …
Detection of long-term effect in forecasting municipal solid waste using a long short-term memory neural network
D Niu, F Wu, S Dai, S He, B Wu - Journal of Cleaner Production, 2021 - Elsevier
Researchers have been successfully applied artificial neural networks (ANNs) in the time-
series analysis and forecasting of municipal solid waste (MSW). Despite the reported high …
series analysis and forecasting of municipal solid waste (MSW). Despite the reported high …
Forecasting energy consumption of wastewater treatment plants with a transfer learning approach for sustainable cities
A major challenge of today's society is to make large urban centres more sustainable.
Improving the energy efficiency of the various infrastructures that make up cities is one …
Improving the energy efficiency of the various infrastructures that make up cities is one …
Deep learning with long short-term memory recurrent neural network for daily container volumes of storage yard predictions in port
Y Gao, D Chang, CH Chen… - … International conference on …, 2018 - ieeexplore.ieee.org
With the development of China's Belt and Road Initiative (BRI), the port plays a significant
role and its operation management faces some pressure. In this regard, prediction of daily …
role and its operation management faces some pressure. In this regard, prediction of daily …
Comparative analysis of deep learning and statistical models for air pollutants prediction in urban areas
Rapid growth in urbanization and industrialization leads to an increase in air pollution and
poor air quality. Because of its adverse effects on the natural environment and human …
poor air quality. Because of its adverse effects on the natural environment and human …
Deep learning based a comprehensive analysis for waste prediction
In its simplest definition, waste can be defined as any substance that is used, not needed
and causes harm to the environment. Waste management covers control activities such as …
and causes harm to the environment. Waste management covers control activities such as …
Multi-site household waste generation forecasting using a deep learning approach
M Cubillos - Waste Management, 2020 - Elsevier
Forecasting household waste generation using traditional methods is particularly
challenging due to its high variability and uncertainty. Unlike studies that forecast waste …
challenging due to its high variability and uncertainty. Unlike studies that forecast waste …