Advances on Computational Intelligence in Energy 1st ed. 2020(Green Energy and Technology) H c. 400 p. 19
目次
Basic descriptions of computational intelligence algorithms (single, hybrid, ensemble, integrated and etc.- Credible sources of energy datasets.- Applications of computational algorithms in energy.- Practical application of cuckoo search and neural network in the prediction of OECD oil consumption.- Hybrid of Fuzzy systems and particle swarm optimization in the forecasting gas flaring from oil consumption.- Forecasting of OECD gas flaring using Elman neural network and cuckoo search algorithm.- Artificial bee colony and neural network for the forecasting of Malaysia renewable energy.- Soft computing methods in the modelling of OECD carbon dioxide emission from petroleum consumption.- Modelling energy crises based on Soft computing.- The forecasting of WTI and Dubai crude oil prices benchmarks based on soft computing.- A new approach for the forecasting of IAEA energy.- Modelling of gasoline prices using fuzzy multi-criteria decision making.- Soft computing for the prediction of Australia petroleum consumption based on OECD countries.- Future research problems in the area of computational intelligence algorithms in energy.
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