Enterobacter sp. SWLC2 for biodegradation of chlorpyrifos in the aqueous medium: Modeling of the process using artificial neural network approaches

Aqueous Medium ◽

Artificial Neural ◽

Forest Land Cover Classification Using Statistical and Artificial Neural Network Approaches Applied to IRS LISS ‐ III Sensor

Geocarto International ◽

10.1080/10106040108542192 ◽

2001 ◽

Vol 16 (2) ◽

pp. 39-44 ◽

Cited By ~ 6

Author(s):

Ramanathan Sugumaran

Keyword(s):

Neural Network ◽

Land Cover ◽

Land Cover Classification ◽

Forest Land ◽

Liss Iii ◽

Artificial Neural ◽

Forest Land Cover ◽

Predictive modelling of coniferous forest age using statistical and artificial neural network approaches applied to remote sensor data

International Journal of Remote Sensing ◽

10.1080/014311699211804 ◽

1999 ◽

Vol 20 (14) ◽

pp. 2805-2822 ◽

Cited By ~ 85

Author(s):

J. R. JENSEN, FANG QIU, MINHE JI

Keyword(s):

Neural Network ◽

Coniferous Forest ◽

Predictive Modelling ◽

Sensor Data ◽

Forest Age ◽

Remote Sensor ◽

Artificial Neural ◽

Experimental and Artificial Neural Network Approaches to Predict the Effect of PVA (Poly Vinyl Acetate) on the Rheological Properties of Water and Crude Oil in EOR Processes

10.2118/140680-ms ◽

2010 ◽

Cited By ~ 1

Author(s):

A. Rezaian ◽

A. Kordestany ◽

M. Haghighat Sefat

Keyword(s):

Neural Network ◽

Crude Oil ◽

Rheological Properties ◽

Vinyl Acetate ◽

Artificial Neural ◽

Eor Processes ◽

2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society ◽

Complimentary artificial neural network approaches for prediction of events in the neonatal intensive care unit

10.1109/iembs.2008.4650239 ◽

2008 ◽

Cited By ~ 4

Author(s):

Daphne Townsend ◽

Monique Frize

Keyword(s):

Neural Network ◽

Intensive Care Unit ◽

Intensive Care ◽

Neonatal Intensive Care Unit ◽

Neonatal Intensive Care ◽

Artificial Neural ◽

Modeling of effluent COD in UAF reactor treating cyanide containing wastewater using artificial neural network approaches

Advances in Engineering Software ◽

10.1016/j.advengsoft.2010.04.002 ◽

2010 ◽

Vol 41 (7-8) ◽

pp. 1005-1010 ◽

Cited By ~ 11

Author(s):

Turan Yilmaz ◽

Galip Seckin ◽

Ahmet Yuceer

Keyword(s):

Neural Network ◽

Artificial Neural ◽

COMPARISON OF PROCESS-BASED AND ARTIFICIAL NEURAL NETWORK APPROACHES FOR STREAMFLOW MODELING IN AN AGRICULTURAL WATERSHED

JAWRA Journal of the American Water Resources Association ◽

10.1111/j.1752-1688.2006.tb04475.x ◽

2006 ◽

Vol 42 (3) ◽

pp. 545-563 ◽

Cited By ~ 51

Author(s):

Puneet Srivastava ◽

James N. McNair ◽

Thomas E. Johnson

Keyword(s):

Neural Network ◽

Agricultural Watershed ◽

Artificial Neural ◽

Network Approaches ◽

Streamflow Modeling

Rapid activity prediction of HIV-1 integrase inhibitors: harnessing docking energetic components for empirical scoring by chemometric and artificial neural network approaches

Journal of Computer-Aided Molecular Design ◽

10.1007/s10822-016-9917-0 ◽

2016 ◽

Vol 30 (6) ◽

pp. 471-488 ◽

Cited By ~ 2

Author(s):

Patcharapong Thangsunan ◽

Sila Kittiwachana ◽

Puttinan Meepowpan ◽

Nawee Kungwan ◽

Panchika Prangkio ◽

...

Keyword(s):

Neural Network ◽

Integrase Inhibitors ◽

Activity Prediction ◽

Artificial Neural ◽

Network Approaches ◽

Hiv 1

Quantitative EEG (qEEG) predicts relapse in patients with primary alcoholism — a comparison between multivariate statistics and artificial neural network approaches

Psychiatry Research Neuroimaging ◽

10.1016/s0925-4927(97)81603-4 ◽

1997 ◽

Vol 68 (2-3) ◽

pp. 183-184

Author(s):

G. Winterer ◽

B. Klöppel ◽

A. Heinz ◽

M. Ziller ◽

L.G. Schmidt ◽

...

Keyword(s):

Neural Network ◽

Multivariate Statistics ◽

Quantitative Eeg ◽

Artificial Neural ◽

Classification of Brain Metastases Prognostic Groups Utilizing Artificial Neural Network Approaches

Cureus ◽

10.7759/cureus.115 ◽

2013 ◽

Author(s):

George Rodrigues ◽

Glenn Bauman ◽

Ben J. Slotman ◽

Frank Lagerwaard

Keyword(s):

Neural Network ◽

Brain Metastases ◽

Prognostic Groups ◽

Artificial Neural ◽

Fully-fuzzy supervised classification of sub-urban land cover from remotely sensed imagery: Statistical and artificial neural network approaches

International Journal of Remote Sensing ◽

10.1080/01431160050505883 ◽

2001 ◽

Vol 22 (4) ◽

pp. 615-628 ◽

Cited By ~ 93

Author(s):

J. Zhang ◽

G. M. Foody

Keyword(s):

Neural Network ◽

Land Cover ◽

Supervised Classification ◽

Urban Land ◽

Remotely Sensed Imagery ◽

Urban Land Cover ◽

Artificial Neural ◽