000			03779nam a22005775i 4500
001			978-1-84628-073-3
003			DE-He213
005			20161121231016.0
007			cr nn 008mamaa
008			100301s2005 xxk| s |||| 0|eng d
020			_a9781846280733 _9978-1-84628-073-3
024	7		_a10.1007/b138332 _2doi
050		4	_aTK1-9971
072		7	_aTJK _2bicssc
072		7	_aTEC041000 _2bisacsh
082	0	4	_a621.382 _223
100	1		_aZhang, Runtong. _eauthor.
245	1	0	_aFuzzy Control of Queuing Systems _h[electronic resource] / _cby Runtong Zhang, Yannis A. Phillis, Vassilis S. Kouikoglou.
264		1	_aLondon : _bSpringer London, _c2005.
300			_aX, 175 p. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
505	0		_aFuzzy Logic -- Knowledge and Fuzzy Control -- Control of the Service Activities -- Control of the Queue Discipline -- Control of the Admission of Customers -- Coordinating Multiple Control Policies -- Applications of Fuzzy Queuing Control to the Internet -- Closure.
520			_aEvery day we experience the annoyance of having to queue. The phenomenon is becoming more prevalent in our increasingly congested and urbanised society. Not only the visible queues in traffic jams, airport check in desks and supermarkets, but the more common invisible queues caused by voice calls and data packets in optical and wireless channels. Queues cost us time, money and resources; so what is the solution to our greater demand for services than there are facilities? Queuing control plays a crucial role in manufacturing and communication networks around the world. This pioneering approach, using fuzzy control to solve queuing control problems, determines explicit solutions to various types of control in queuing systems. The bulk of results have been developed over the past decade and are presented here together for the first time. 21 detailed case studies demonstrate an efficient departure from classical techniques. Unique work creating a new Research and Development topic. Multidisciplinary approach that will benefit researchers and students throughout the fields of artificial intelligence, operations research, optimal control, Internet techniques, communications and traffic control industries. Equipped with an extensive bibliography for easy reference and scope for further study. Existing practical problems, especially those that are unresponsive to conventional control techniques, are solved with the introduction of this novel approach. A systematic framework of the ‘fuzzy control of queuing networks’ is developed through each individual case.
650		0	_aEngineering.
650		0	_aComputer communication systems.
650		0	_aArtificial intelligence.
650		0	_aControl engineering.
650		0	_aRobotics.
650		0	_aMechatronics.
650		0	_aEngineering economics.
650		0	_aEngineering economy.
650		0	_aElectrical engineering.
650	1	4	_aEngineering.
650	2	4	_aCommunications Engineering, Networks.
650	2	4	_aControl, Robotics, Mechatronics.
650	2	4	_aInformation Systems Applications (incl. Internet).
650	2	4	_aArtificial Intelligence (incl. Robotics).
650	2	4	_aComputer Communication Networks.
650	2	4	_aEngineering Economics, Organization, Logistics, Marketing.
700	1		_aPhillis, Yannis A. _eauthor.
700	1		_aKouikoglou, Vassilis S. _eauthor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9781852338244
856	4	0	_uhttp://dx.doi.org/10.1007/b138332
912			_aZDB-2-ENG
950			_aEngineering (Springer-11647)
999			_c507210 _d507210