Paper Info
Title
SUGPO: A White Spot Disease Detection in Shrimps Using Hybrid Neural Networks with Fuzzy Logic Algorithm
Abstract
Shrimp is a high-value commodity and one of the major aquaculture species not only in the Philippines but in the world. White Spot Syndrome Virus (WSSV) is a virus that has been infecting shrimp farms and affecting the shrimp productions across the globe. Manual disease inspection among the shrimps is a time consuming process in the management of shrimp farms. Thus, the researchers conducted this study in able to provide a fast disease inspection tool in order to early detect the infection before the disease results to an outbreak. The researchers developed a system that detects the white spot disease among the shrimps. Image processing techniques was utilized in the system as well as Artificial Intelligence algorithms such as Artificial Neural Network (ANN) and Fuzzy Logic. ANN has the ability to learn and classify an input base on its learnings, whereas Fuzzy Logic is known for dealing with uncertainties. The main objective of this study is to determine the accuracy and reliability rate of the tool in detecting the WSSV using the hybrid algorithm of ANN and Fuzzy Logic considering the color of the spot, location of the white spots and the discoloration in the body of the shrimp. For the testing of the system, 50 samples of shrimps were used. The system assessed each samples by analyzing the images of the shrimps. In evaluating a set of Shrimp samples, the system's diagnosis and the expert's diagnosis were compared and analyzed. The researchers used the confusion matrix and the accuracy rate formula for the computation of the accuracy rate and the Test-Retest Reliability equation for the computation of the reliability rate. The result of the tool produced a system performance with 90% accuracy rate and a reliability rate of 0.8 which is equivalent to Good Reliability. Thus, the result of this study shows that ANN and Fuzzy Logic are effective algorithms to utilize in automated disease diagnostics like the white spot disease detection.
Year
DOI
Venue
2018
10.1145/3301551.3301574
Proceedings of the 6th International Conference on Information Technology: IoT and Smart City
Keywords
Field
DocType
Hybrid neural networks, fuzzy logic algorithm, image processing, white spot syndrome, white spot syndrome virus
Hybrid algorithm,Shrimp farming,Confusion matrix,Pattern recognition,Computer science,Fuzzy logic,Image processing,Artificial intelligence,Artificial neural network,White spot syndrome,Shrimp
Conference
ISBN
Citations 
PageRank 
978-1-4503-6629-8
0
0.34
References 
Authors
0
3
Name
Order
Citations
PageRank
Aleta C. Fabregas100.34
Debrelie Cruz200.34
Mark Daniel Marmeto300.34