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H. Altıparmak et al.
the negative impacts of climate change need to be identified. In this way, strategies
to combat potential problems caused by future climate change can be established
Keywords Environmental problems · Climate change · Global warming ·
Artificial neural network · Prediction
9.1 Introduction
The prediction of future climate change is the most important attribute to forecast
because most industries as well as agricultural sectors are largely dependent on
climate conditions. Since the ancient times, climate prediction has been one of the
fascinating and interesting domains. It is used to predict and warn about various
natural disasters that are caused due to changes in climate conditions. Due to the
confusing nature of the atmosphere, greater computational power is required for
solving complex equations related to the prediction of changes in atmospheric conditions. Climate forecasting may be less accurate because of the difference between
historical data and future events. With the help of these models we can minimize this
error to predict the most correct outcome.
The steps involved in predicting the climate are as follows:
1. Data collection, such as maximum and minimum temperature
2. Data assimilation.
3. Data analysis
4. Numerical climate prediction
The effects of climate change include high average temperatures, extreme and
frequent climate events and rising sea levels, which are expected to lead to an increase
in disease and mortality, as well as negative impacts on safe food supply, clean water
and sanitation.
Rising sea levels are threatening access to land in coastal areas, particularly lowlying islands. Land used for agriculture will no longer be usable, as saltwater contaminates soil and fresh water supplies. People are forced to migrate inland, causing health
issues including increased infectious diseases.
Rising temperatures and other effects of climate change are creating fertile ground
for disease-carrying insects. Mosquitoes, which spread diseases including malaria,
dengue and Zika, are particularly sensitive to changes in temperature and humidity.
9.2 Aim of the Study
The aim of this study is to create an artificial neural network that predicts future
climate changes and their effects by using climate change data from previous years.
With the development of the artificial neural network, possible future situations will
be predicted accurately and efficiently.
H. Altıparmak et al.
the negative impacts of climate change need to be identified. In this way, strategies
to combat potential problems caused by future climate change can be established
Keywords Environmental problems · Climate change · Global warming ·
Artificial neural network · Prediction
9.1 Introduction
The prediction of future climate change is the most important attribute to forecast
because most industries as well as agricultural sectors are largely dependent on
climate conditions. Since the ancient times, climate prediction has been one of the
fascinating and interesting domains. It is used to predict and warn about various
natural disasters that are caused due to changes in climate conditions. Due to the
confusing nature of the atmosphere, greater computational power is required for
solving complex equations related to the prediction of changes in atmospheric conditions. Climate forecasting may be less accurate because of the difference between
historical data and future events. With the help of these models we can minimize this
error to predict the most correct outcome.
The steps involved in predicting the climate are as follows:
1. Data collection, such as maximum and minimum temperature
2. Data assimilation.
3. Data analysis
4. Numerical climate prediction
The effects of climate change include high average temperatures, extreme and
frequent climate events and rising sea levels, which are expected to lead to an increase
in disease and mortality, as well as negative impacts on safe food supply, clean water
and sanitation.
Rising sea levels are threatening access to land in coastal areas, particularly lowlying islands. Land used for agriculture will no longer be usable, as saltwater contaminates soil and fresh water supplies. People are forced to migrate inland, causing health
issues including increased infectious diseases.
Rising temperatures and other effects of climate change are creating fertile ground
for disease-carrying insects. Mosquitoes, which spread diseases including malaria,
dengue and Zika, are particularly sensitive to changes in temperature and humidity.
9.2 Aim of the Study
The aim of this study is to create an artificial neural network that predicts future
climate changes and their effects by using climate change data from previous years.
With the development of the artificial neural network, possible future situations will
be predicted accurately and efficiently.