A Survey on the Analysis of Dissolved Oxygen Level in Water using Data Mining Techniques

Abstract

Data Mining (DM) is a powerful and a new field having various techniques to analyses the recent real world problems. In DM, environmental mining is one of the essential and interesting research areas. DM enables to collect fundamental insights and knowledge from massive volume of environmental data. The water quality is determining the condition of water in the environment. It represents the concentration and state (dissolved or particulate) of some or all the organic and inorganic material present in the water, together with certain physical characteristics of the water. The Dissolved Oxygen (DO) is one of the important aspects of water quality. The DO is the quantity of gaseous oxygen (O2) incorporated into the water. The DO is essential for keeping the water organisms alive. The amount of DO level in the water can be detected by various methods. The data mining techniques are properly used to find DO Level in the different types of water. A number of DM methods used to analyze the DO level such as Multi-Layer Perceptron, Multivariate Linear Regression, Factor Analysis, and Feed Forward Neural Network. This survey work discusses about such type of methods, particularly used for the analysis of DO level elaborately. Finally, this research suggests the best DM method to find DO level in water by means of a comparative analysis.