000			02214cam a2200301zu 4500
001			88964012
003			FRCYB88964012
005			20250429182436.0
006			m o d
007			cr un
008			250429s2018 fr | o|||||0|0|||eng d
020			_a9780128128473
035			_aFRCYB88964012
040			_aFR-PaCSA _ben _c _erda
100	1		_aPoznyak, Tatyana
245	0	1	_aOzonation and Biodegradation in Environmental Engineering _bDynamic Neural Network Approach _c['Poznyak, Tatyana', 'Chairez Oria, Jorge Isaac', 'Poznyak, Alexander S.']
264		1	_bElsevier Science _c2018
300			_a p.
336			_btxt _2rdacontent
337			_bc _2rdamdedia
338			_bc _2rdacarrier
650		0	_a
700	0		_aPoznyak, Tatyana
700	0		_aChairez Oria, Jorge Isaac
700	0		_aPoznyak, Alexander S.
856	4	0	_2Cyberlibris _uhttps://international.scholarvox.com/netsen/book/88964012 _qtext/html _a
520			_aOzonation and Biodegradation in Environmental Engineering: Dynamic Neural Network Approach gives a unified point-of-view on the application of DNN to estimate and control the application of ozonation and biodegradation in chemical and environmental engineering. This book deals with modelling and control design of chemical processes oriented to environmental and chemical engineering problems. Elimination in liquid, solid and gaseous phases are all covered, along with processes of laboratory scale that are evaluated with software sensors and controllers based on DNN technique, including the removal of contaminants in residual water, remediation of contaminated soil, purification of contaminated air, and more. The book also explores combined treatments using both ozonation and biodegradation to test the sensor and controller. - Defines a novel researching trend in environmental engineering processes that deals with incomplete mathematical model description and other non-measurable parameters and variables - Offers both significant new theoretical challenges and an examination of real-world problem-solving - Helps students and practitioners learn and inexpensively implement DNN using commercially available, PC-based software tools
999			_c1327187 _d1327187