Artificial Neural Network (ANN)

MATHEMATICAL SIMULATION FOR ALGAL GROWTH IN THE WATER RESERVOIRS OF MONCTON CITY (NEW BRUNSWICK, CANADA) BY THE SUPERVISED LEARNING CLASSIFIER

Mathematical model is a good approach to deal with the coupling effects of governing parameters in algal bloom growth. Amongmanymodels to deal with combining factors and data-based supervised learning classifiers, the Artificial Neural Network (ANN) has the most significant impact on the development of bloom pattern.

MODIFIED REDFIELD RATIO COMBINED WITH ARTIFICIAL NEURAL NETWORK SIMULATION TO ESTIMATE THE ALGAL BLOOM PATTERN

In previous work (Hushchyna and Nguyen-Quang, 2017), we have introduced the Modified Redfield Ratio (MRR) to estimate algal blooms occurring in Mattatall Lake, Nova Scotia (Canada). The goals of this paper are to test this modified index based on nutrient level to estimate bloom patterns via field experimental data and by the mathematical simulation with a supervised learning model Artificial Neural Network.