首页|Applicability of denoising-based artificial intelligence to forecast the environmental externalities
Applicability of denoising-based artificial intelligence to forecast the environmental externalities
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The current study attempts to compare the hybrid artificial intelligence models to forecast the environ-mental externalities in Saudi Arabia.We have used the denoising based artificial intelligence models to construct hybrid models.While comparing the denoising techniques,the CSD-based denoising has out-performed.However,we have used the CSD-based hybrid models.CSD-ANN and CSD-RNN are used for denoising-based artificial intelligence models,whereas CSD-ARIMA is used for denoising-based tradi-tional models.All these models are used to check and compare their performance in terms of level and direction of prediction for PM10.The results show that the CSD-based ANN model has a higher pre-dictability for PM10 levels in Saudi Arabia due to low error values and higher Dstat values.In comparing original and forecasted data,the superiority of CSD-ANN is evident in predicting the PM10 in Saudi Arabia.Hence,this hybrid model can predict the environmental externalities for non-linear and highly noised data.Moreover,the findings can be useful in achieving the sustainable development goal.
NETL
NSTL
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