This article discusses the use of hybrid approaches that combine one or more models from one or more categories to address the shortcomings of each of the previously discussed single-model categories. Specifically, the article focuses on the use of hybrid approaches for CO emissions forecasting. Examples of hybrid approaches discussed include a framework integrating index decomposition analysis (IDA) along with ANNs and data envelopment analysis (DEA), a model combining a general regression neural network and scenario analysis, a pure deep-learning hybrid, an ensemble Adaptive Neuro-Fuzzy Inference System (ANFIS) learning method, a hybrid approach blending the results of nine different algorithms, a two-step hybrid method, and a single model integrating ANNs, RF, and particle swarm optimization (PSO).
Related Posts
