Carbon price time series forecasting utilizing an optimized ANFIS model

In the continuous campaign to reduce carbon emissions and mitigate the severe effects of climate change, the strategic use of carbon price forecasting to anticipate future carbon pricing dynamics is a vital strategy. Accurate forecasting of future carbon pricing enables industries to modify their operations, encouraging the adoption of eco-friendly technology and procedures. This coordination of activities, including carbon pricing plans, emission reduction targets, and environmentally friendly behaviors, not only addresses climate change issues but also aligns well with sustainable development goals related to clean energy, climate action, and sustainable economies. To tackle this issue, a hybrid approach is introduced by integrating the Improved Electric Fish Optimization (IEFO) with the Adaptive Neuro-Fuzzy Inference System (ANFIS), creating a robust framework for forecasting the carbon price. The proposed IEFO algorithm, representing an enhanced version of the Electric Fish Optimization (EFO), integrates the searching strategy of the Whale Optimization Algorithm (WOA) to boost exploration capabilities, enabling more effective exploration of new areas and efficient escape from local optima. By strategically combining EFO’s active search with WOA’s localized exploration strategy, the IEFO-ANFIS model excels in capturing intricate carbon price dynamics and enhances forecasting accuracy. The efficacy of the IEFO-ANFIS model is rigorously demonstrated through comprehensive experiments, showing its superior performance across five datasets, namely BeijingETS, CEHD, GuangzhouETS, HubeiETS, and TianjinETS. The results demonstrated the effectiveness of the proposed IEFO-ANFIS model in accurately forecasting carbon prices. Additionally, the results show remarkable performance of the proposed model compared with state-of-the-art models. Moreover, the results show that the proposed IEFO-ANFIS model can assist policymakers in developing efficient carbon pricing plans, supporting a more seamless shift to a low-carbon economy without disrupting markets.