Combining Artificial Intelligence and Systems Thinking Tools to Predict Climate Change

According to systemic definitions, climate change is considered a complex system. Therefore, a systematic tool is needed to model it for the future. Artificial intelligence (AI) tools such as artificial neural networks (ANN) can be useful for predicting future situations based on available data. In the meantime, System thinking (ST) sees events not in a linear fashion, but in the form of feedback loops. Therefore, this tool can help to predict the climate change situation in the future, especially since different policies can be introduced as climate action and their effects can be examined. Therefore, the combination of the two methods of AI and ST can be more useful for predicting the future of climate change and the impact of climate actions than using each of them alone, based on the ability of each of them to define policy and predict based on data. In this research, the two methods of AI and ST and the studies that have been done using these two methods to predict climate change and its related parameters and also their strengths and weaknesses were examined. In the conducted investigations, it can be concluded that the combination of two methods is better than each of the methods alone, and with the help of the combination, a more correct decision can be made for the future of climate change and what climate actions should be taken.