A Practical Approach To Combustion Process Optimization Using An Improved Immune Optimizer

dc.contributor.author	Miller, A.
dc.contributor.author	Milewski, J.
dc.contributor.author	Warchol, M.
dc.contributor.author	Swirski, K.
dc.contributor.author	Wojdan, K.
dc.date.accessioned	2017-04-06T09:47:51Z
dc.date.available	2017-04-06T09:47:51Z
dc.date.issued	2017-04-06
dc.identifier.issn	2079-6226
dc.identifier.uri	http://journals.jkuat.ac.ke/index.php/sri
dc.identifier.uri	http://hdl.handle.net/123456789/2816
dc.description.abstract	An improved version of the immune inspired optimizer SILO is presented in this paper. The new model identification method allows for utilization of model gains constraints. Moreover the operation of a new Transition State algorithm is analyzed based on a real-life example. The improved version of SILO was implemented in a real power boiler. Results from a real combustion process optimization are presented in this paper.	en_US
dc.description.sponsorship	JKUAT	en_US
dc.language.iso	en	en_US
dc.publisher	COETEC	en_US
dc.relation.ispartofseries	Sustainable Research and Innovation Conference Proceedings;Vol 3 (2011) 2011
dc.subject	Practical Approach To Combustion Process	en_US
dc.subject	Optimization Using An Improved Immune Optimizer	en_US
dc.subject	KENYA	en_US
dc.subject	JKUAT	en_US
dc.title	A Practical Approach To Combustion Process Optimization Using An Improved Immune Optimizer	en_US
dc.type	Article	en_US