- 1.Brockwell, Peter J., and Richard Davis, Time Series ~ Theo~and Methods, Springer-Verlag 1987. Google ScholarDigital Library
- 2.Broomhead, D.$. and Gregory P. King, "Extracting Qualitative Dynamics from Experimental Data", P~ zoD, ~986. Google ScholarDigital Library
- 3.Casdagli, Martin, "Nonlinear Prediction of Chaotic Time Series", Ph~ p335 (1989).Google Scholar
- 4.Cryer, Jonathan, Time Series Analys~, PWS-Kent Publishing Company, 1986. Google ScholarDigital Library
- 5.Farmer, J. Dc~e and John Siclorowich, "Exploiting Chaos to Predict the Future and Reduce Noise", LA-UR- 88-901 (1988).Google Scholar
- 6.He, Xiangclong and Alan Lapedes, ~Nonlinear Modeling and Prediction By Successive Apprc~imation Using Radial Basis Functions", Technical Report LA-UR- 91-1375, Los Alamos National Laboratory (1991).Google Scholar
- 7.Jones, R.D., Y.C. Lee, C.W. Barnes, G.W. Flake, K. Lee, P.S. Lewis, and S. Qian, "Function Approximation and Time Series Prediction with Neural Networks", LA-UR- 90.21 (1989).Google Scholar
- 8.Jones, R.D., Y.C. Lee, S. Qian, C.W. Barnes, K.R. Bisset, G.M. Bruce, G.W. Flake, K. Lee, L.A. Lee, W.C. Mead, M.K. O'Rourke, i.J. Poll, and L.E. Triode, "Nonlinear Adaptive Networks' A Little Theory, A Few Applications", LA-UR-91-273 (1990).Google Scholar
- 9.Kadirkamanathan, V., M. Niranjan, and F. Fallside, "Sequential Adaptation of Radial Basis Function Neural Networks and its Application to Time-Series Prediction" NIPS 90. Google ScholarDigital Library
- 10.Lapedes, Alan and Robert Farber, "Nonlinear Signal Processing Using Neural Networks- Prediction and System Modeling", Technical Report LA-UR.87-2662, Los Alamos National Laboratory (1987).Google Scholar
- 11.Mahuli, Suhas, R.Russell Rhinehart, and James B. Riggs, "Experimental Demonstration of Nonlinear Modelbased In-line Control of pH", Submitted to the Journal o_.. f Process Contro!, November, 1991. Presented at the 1991 AIChE Annual Meeting, Los Angeles, CA, November, 1991, paper 149g.Google Scholar
- 12.Mead, W.C., R.D. Jones, Y.C. Lee, C.W. Barnes, G.W. Flake, L.A. Lee, M.K. O'Rourke, "Prediction of Chaotic Time Series Using CNLS-Net-Example: The Mackey-Glass Equation", LA-UR-91-720, 1991.Google Scholar
- 13.Moody, John and Christian Darken, "Fast Learning in Networks of Locally Tuned Processing Units", Neural Computation, Vol 1 (1989)p281.Google ScholarDigital Library
- 14.Pineda, Fernando, "Generalization of Rack- Propagation to Recurrent Neural Networks", Ph._.~_L.~! Review Letters, Vol. 59, Number 19, November 9, 1987.Google Scholar
- 15.Weigend, Andreas, Bernardo Huberman and David Rumelhart, "Predicting the Future' A Connectionist Approach" International Journal of Neural Systems, Voi. 1 (1990) p193.Google Scholar
- 16.Williams, RJ. and D. Zipser, "A Learning Algorithm for Continually Running Fully Recurrent Neural Networks", Neural Computation, Vol. 1 (2), 1989.Google ScholarDigital Library
- 17.Williams, Gayion, R. Russell Rhinehart, and .lames Riggs, "In-Line Process-Model-Based Control of Wastewater pH Using Dual Base Injection", Ind~ Chem. Res., 1990, Vol. 29, p1254.Google ScholarCross Ref
Index Terms
- Predicting acid concentrations in processing plant effluent: an application of time series prediction using neural networks
Recommendations
Soft-sensing estimation of plant effluent concentrations in a biological wastewater treatment plant using an optimal neural network
We develop a neural-network-based soft sensor to predict effluent concentrations.We estimate primary variables from secondary variables in activated sludge process.Principal component analysis is applied to optimal selection of sensor input vector.The ...
Predicting Intrinsically Disordered Regions Based on the Structural Bias of Amino Acid Dimers
ICBCB 2018: Proceedings of the 2018 6th International Conference on Bioinformatics and Computational BiologyDue to many important functions of intrinsically disordered proteins, it has already become hotter and hotter research topic to distinguish intrinsically disordered regions from amino acid sequences. To accurately predict intrinsically disordered ...
River acid mine drainage: sediment and water mapping through hyperspectral Hymap data
The Odiel River Huelva, southwest Spain carries acidic water originating from mine waste contamination, including massive sulphide ore deposits. As the river approaches the coastal estuary, tidal factors influence both sediment and water dynamics. As ...
Comments