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

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

EP.
2018;
Volume 3, Number 2
: pp. 103-114
Authors:
  1. Qurat-Ul An Sabir
  2. Muhammad Nadeem
  3. Tri Nguyen-Quang
1
Biofluids and Biosystems Modeling Lab (BBML) Department of Engineering, Faculty of Agriculture, Dalhousie University
2
Dalhousie University
3
Biofluids and Biosystems Modeling Lab (BBML) Department of Engineering, Faculty of Agriculture, Dalhousie University

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. The objective of this paper is to use the Artificial Neural Network (ANN) model to simulate the growth of harmful algae under environmental factors that can lead to bloom pattern in two reservoirs of Moncton city (Canada) with the collected data fromtwo years of observation 2016–2017.

 

Artificial Neural Network (ANN)
cyanobacteria
Harmful Algal Blooms (HAB)
Modified Redfield Ratio (MRR)
Supervised learning classifier

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