The following are peer reviewed journal articles and conference proceedings describing the rational for implementing water level forecasts based on artificial neural networks (ANN) (1), the design and optimization of the ANN models (2), and a comparison of the performance of the ANN models with the persistent model and the tide table for two of the main Texas estuaries. More information can be found in other listed DNR articles (4) and presentations (5).

(1) D.T. Cox, P.E. Tissot, and P. Michaud, “Water Level Observations and Short-Term Predictions Including Meteorological Events for Entrance of Galveston Bay, Texas”, Journal of Waterway, Port, Coastal and Ocean Engineering, 128-1 (2002) 21-29. http://wave.oregonstate.edu/Research/Publications/Cox/ctm-ww-02.pdf.

(2) P.E. Tissot, D.T. Cox, and P.R. Michaud, “Optimization and Performance of a Neural Network Model Forecasting Water Levels for the Corpus Christi, Texas, Estuary”, 3rd Conference on the Applications of Artificial Intelligence to Environmental Science, Long Beach, California, February 2003. PDF

(3) P.E. Tissot, D.T. Cox, A. Sadovski, P. Michaud and S. Duff, “Performance and Comparison of Water Level Forecasting Models for the Texas Ports and Waterways” proceedings of the PORTS 2004 Conference, Houston, TX, May 23-26, 2004.PDF

(4) DNR Publications

(5) DNR Presentations