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200 00$aArtificial intelligence, machine learning, and optimization tools for smart cities $edesigning for sustainability /$fPanos M. Pardalos, Stamatina Th. Rassia, Arsenios Tsokas, editors
210  1$aCham, Switzerland :$cSpringer,$d[2022]
210  4$d©2022
215   $a1 online resource (239 pages)
225 1 $aSpringer optimization and its applications ;$vVolume 186
311 08$aPrint version: Pardalos, Panos M. Artificial Intelligence, Machine Learning, and Optimization Tools for Smart Cities Cham : Springer International Publishing AG,c2022 9783030844585 
410  0$aSpringer optimization and its applications ;$vVolume 186.
606   $aArtificial intelligence
606   $aCiutats intel·ligents$2thub
606   $aInnovacions tecnològiques$2thub
606   $aIntel·ligència artificial$2thub
608   $aLlibres electrònics$2thub
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615  7$aCiutats intel·ligents
615  7$aInnovacions tecnològiques
615  7$aIntel·ligència artificial
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200 12$aA new method for analyzing near-field faraday probe data in hall thrusters /$fWensheng Huang [and four others]
210  1$aCleveland, Ohio :$cNational Aeronautics and Space Administration, Glenn Research Center,$dAugust 2013.
215   $a1 online resource (22 pages) $ccolor illustrations
225 1 $aNASA/TM ;$v2013-216567
300   $aTitle from title screen (viewed Oct. 27, 2014).
300   $a"August 2013."
300   $a"Prepared for the 49th Joint Propulsion Conference and Exhibit cosponsored by AIAA, ASME, SAE, and ASEE San Jose, California, July 14-17, 2013."
300   $a"AIAA-2013-4118."
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606   $aElectric propulsion$2nasat
606   $aNear fields$2nasat
606   $aElectrostatic probes$2nasat
606   $aData processing$2nasat
606   $aIteration$2nasat
606   $aGround tests$2nasat
615  7$aHall thrusters.
615  7$aElectric propulsion.
615  7$aNear fields.
615  7$aElectrostatic probes.
615  7$aData processing.
615  7$aIteration.
615  7$aGround tests.
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