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dc.creatorJanson, Richard W.en_US
dc.creatorBatur, Celalen_US
dc.creatorKrishna, Lala B.en_US
dc.date.accessioned2006-07-07T18:09:26Z
dc.date.available2006-07-07T18:09:26Z
dc.date.issued1994-06en_US
dc.identifier.citationThe Ohio Journal of Science. v94, n3 (June, 1994), 60-69en_US
dc.identifier.issn0030-0950en_US
dc.identifier.urihttp://hdl.handle.net/1811/23613
dc.descriptionAuthor Institution: Department of Geography, Kent State University, Department of Mechanical Engineering, Department of Mathematical Sciences, University of Akronen_US
dc.description.abstractNeural net methodology has been used to model alternative scenarios of fuel utilization. Regulation and legislation to address the problems of energy related pollution such as acid rain, nuclear waste, greenhouse gases, and tailpipe pollution, will alter fuel input ratios with consequential effects in the energy using sectors. Also, alternative input scenarios using clean coal technology, natural gas, and nuclear power have been modeled. Results indicate that large relative increases of coal or nuclear fuel inputs will cause similar substantial increases in electricity generation, and substitution effects will cause a shift of petroleum uses in final consumption from the commercial and residential sectors to the transport sector. Increasing the gas fuel input relative to other fuels causes little disturbance in using sectors. Incremental increases in fuel consumption maintaining constant relative fuel input shares causes little disturbance. On the other hand, massive increases in fuel consumption inputs maintaining constant input shares is likely to be disastrous public policy.en_US
dc.format.extent798244 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.titleThe Effects on Energy Markets Subjected to Regulatory Changes Using Neural Net Methodologyen_US


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