How AI beats spreadsheets in modelling future volumes for city waste management
Growing cities tend to run out of land for waste management and new landfill sites.
Artificial Intelligence can help city managers create more powerful long-term forecasts of solid waste volumes and landfill requirements, even with missing or inaccurate data.
UJ researchers found that a 10-neuron model produced the best 30-year forecast for municipal solid waste in a growing city.
All over the world, large cities are running out of space for municipal solid waste. Existing landfill sites are rapidly filling up and no-one wants a new site anywhere near their homes or businesses. Meanwhile, taxpayers aren't interested in higher costs for quality waste management either.
One way of significantly extending the working life of existing waste management sites is recycling. Recyling can also reduce unemployment, help to establish a circular economy or move towards zero waste.
But often, households are highly resistant to recycling, or recycling more.
A recent study shows how Artificial Intelligence (AI) can give city waste managers a more powerful way of forecasting landfill requirements for a city in the long term.
The researchers used machine learning to forecast municipal solid waste in a large African city. The forecast shows how much waste there will be in 30 years' time, if levels of recycling stay the same.
Dr Olusola Olaitan Ayeleru and Mr Lanrewaju Ibrahim Fajimi published their research in the END
Artificial Intelligence can help city managers create more powerful long-term forecasts of solid waste volumes and landfill requirements, even with missing or inaccurate data.
UJ researchers found that a 10-neuron model produced the best 30-year forecast for municipal solid waste in a growing city.
All over the world, large cities are running out of space for municipal solid waste. Existing landfill sites are rapidly filling up and no-one wants a new site anywhere near their homes or businesses. Meanwhile, taxpayers aren't interested in higher costs for quality waste management either.
One way of significantly extending the working life of existing waste management sites is recycling. Recyling can also reduce unemployment, help to establish a circular economy or move towards zero waste.
But often, households are highly resistant to recycling, or recycling more.
A recent study shows how Artificial Intelligence (AI) can give city waste managers a more powerful way of forecasting landfill requirements for a city in the long term.
The researchers used machine learning to forecast municipal solid waste in a large African city. The forecast shows how much waste there will be in 30 years' time, if levels of recycling stay the same.
Dr Olusola Olaitan Ayeleru and Mr Lanrewaju Ibrahim Fajimi published their research in the END