Design of Self-Constructing Recurrent-Neural-Network-Based Adaptive Control

Hsu, Chun‐Fei; Lin, Chih-Min

doi:10.5772/5538

Recurrent Neural Networks 2008

DOI: 10.5772/5538

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Design of Self-Constructing Recurrent-Neural-Network-Based Adaptive Control

Chun‐Fei Hsu¹,

Chih-Min Lin²

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2023

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Cited by 1 publication

References 23 publications

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Life-Cycle Assessment of Biochemicals with Clear Near-Term Market Potential

Liang

Gracida-Alvarez

Hawkins

et al. 2023

ACS Sustainable Chem. Eng.

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The urgent need for greenhouse gas (GHG) emission reductions to mitigate climate change calls for accelerated biorefinery development and biochemical deployment to the market as structural or functional replacements for chemicals produced from fossil-derived feedstocks. This study evaluated the energy and environmental impacts of 15 biochemicals with clear near-term market potential and their fossil-based counterparts, when applicable, on a cradle-to-gate basis. Three of these chemicals are produced exclusively from biomass; eight are predominantly produced from fossil-derived feedstocks; and four are predominantly produced from biomass. For the 12 cases that can be produced from either feedstock, eight exhibited fossil energy consumption and GHG emission reductions when produced from biomass instead of fossil-derived feedstocks between 41%−85% and 35%−350%, respectively. Water consumption results were mixed because several of the biobased pathways consumed more water. Annually, replacing the predominantly fossil-fuel-based chemicals with biobased alternatives could avoid 120 MMT CO 2 e emissions and save 1,500 PJ of fossil energy. The potential of these chemicals as coproducts in integrated biorefineries was analyzed in terms of market, economics, and environmental effects with an emphasis on GHG emissions. Adipic acid, succinic acid, acrylic acid, propylene glycol, 1,4-butanediol, 1,3-butadiene, furfural, and fatty alcohol are promising coproduct candidates based on their low life-cycle GHG emissions.

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Life-Cycle Assessment of Biochemicals with Clear Near-Term Market Potential

Liang

Gracida-Alvarez

Hawkins

et al. 2023

ACS Sustainable Chem. Eng.

View full text Add to dashboard Cite

show abstract

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Design of Self-Constructing Recurrent-Neural-Network-Based Adaptive Control

Cited by 1 publication

References 23 publications

Life-Cycle Assessment of Biochemicals with Clear Near-Term Market Potential

Life-Cycle Assessment of Biochemicals with Clear Near-Term Market Potential

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