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  • Open Access


    Optimal Energy Forecasting Using Hybrid Recurrent Neural Networks

    Elumalaivasan Poongavanam1,*, Padmanathan Kasinathan2, Kulothungan Kanagasabai3

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 249-265, 2023, DOI:10.32604/iasc.2023.030101

    Abstract The nation deserves to learn what India’s future energy demand will be in order to plan and implement an energy policy. This energy demand will have to be fulfilled by an adequate mix of existing energy sources, considering the constraints imposed by future economic and social changes in the direction of a more sustainable world. Forecasting energy demand, on the other hand, is a tricky task because it is influenced by numerous micro-variables. As a result, an macro model with only a few factors that may be predicted globally, rather than a detailed analysis for each of these variables, is… More >

  • Open Access


    Feasible design for electricity generation from Chlorella vulgaris using convenient photosynthetic conditions

    Mahmoud MOUSTAFA1,2*, Tarek TAHA3, Mohamed ELNOUBY4, M.A. ABU-SAIED5, Ali SHATI1, Mohamed AL-KAHTANI1, Sulaiman ALRUMMAN1

    BIOCELL, Vol.42, No.1, pp. 7-12, 2018, DOI:10.32604/biocell.2018.07002

    Abstract Many recent studies are concerned with low cost, easy to handle and alternative renewable energy as a feasible solution for the upcoming crisis of energy shortage. Microalgae are unicellular entities the can only depend on CO2, water and solar power to cover their nutritional needs. The current study is concerned with using algal cells in a polymeric hydrogel, as a cheap source of energy for electricity generation. Chlorella vulgaris has been proved to be a promising algal species for electricity generation, as compared with Micractinium reisseri. PVA hydrogel has been used for the immobilization of both algal species in order… More >

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