alexa An Application Support Vector Machine Model (SVM) Technique For Biochemical Oxygen Demand (BOD) Prediction | 18466
ISSN: 2155-9910

Journal of Marine Science: Research & Development
Open Access

Like us on:

Our Group organises 3000+ Global Conferenceseries Events every year across USA, Europe & Asia with support from 1000 more scientific Societies and Publishes 700+ Open Access Journals which contains over 50000 eminent personalities, reputed scientists as editorial board members.

Open Access Journals gaining more Readers and Citations
700 Journals and 15,000,000 Readers Each Journal is getting 25,000+ Readers

This Readership is 10 times more when compared to other Subscription Journals (Source: Google Analytics)
Recommended Conferences
Share This Page

An application support vector machine model (SVM) technique for biochemical oxygen demand (BOD) prediction

2nd International Conference on Oceanography

A Najah and A El-Shafie

Accepted Abstracts: J Marine Sci Res Dev

DOI: 10.4172/2155-9910.S1.008

Abstract
In this study, Support Vector Machine (SVM) technique has been investigated in prediction of Biochemical Oxygen Demand (BOD). To assess the effect of input parameters on the model, the sensitivity analysis was adopted. To evaluate the performance of the proposed model, three statistical indexes were used, namely; Correlation Coefficient (CC), Mean Square Error (MSE) and Correlation of Efficiency (CE). The principle aim of this study is to develop a computationally efficient and robust approach for predict of BOD which could reduce the cost and labour for measuring these parameters. This research concentrates on the Johor River in Johor State, Malaysia where the dynamics of river water quality are significantly altered .
Biography
Top