1. FISH DISEASE DIAGNOSES
By
Doaa Ali Mohammed

2. Scientific Research Group in Egypt
www.egyptscience.net

3. Agenda




Introduction
Example of Fish Disease
Existing computer based diagnoses’ Systems
Conclusions and Current State

4. Introduction
Ecological Footprint

5. Introduction


6. Fish Health Monitoring



7. The different cause of fish disease






8. Examples of fish disease

Ich / Ick

9. Examples of fish disease, cont.

Fin / Tail Rot

10. Examples of fish disease, cont.

Mouth Fungus

11. Examples of fish disease, cont.

Hole-In-The-Head (HITH)

12. Existing computer based diagnoses’
Systems

Expert System for Fish Disease Diagnosis Based
on Fuzzy Neural Network

13. Fuzzy Neural Network

14. Existing computer based diagnoses’ Systems, cont.

Rough Set and FCM Clustering Algorithm

15. Existing computer based diagnoses’ Systems, cont.


16. Existing computer based diagnoses’ Systems, cont.

Rough Set and Classifier Fusion

17. Existing computer based diagnoses’ Systems, cont.


18. Existing computer based diagnoses’ Systems, cont.


Artificial bee colony algorithm and pattern search
hybridized for global optimization
ABC

19. Existing computer based diagnoses’ Systems, cont.



20. Existing computer based diagnoses’ Systems, cont.


Automatic fuzzy partitioning approach using Variable
string length Artificial Bee Colony (VABC) algorithm

21. Existing computer based diagnoses’ Systems, cont.


22. Conclusions
Technique
Accuracy
Time
Complexity
ES based on
Fuzzy neural
network
High
Fast
High
RS based on FCM High
High
High
RST based on
classifier
High
Slow
High
HABC
Higher
Faster
less
VABC
Higher
Faster
Less

23. Current Status


We are in the process of collecting fish pictures and
compare between used techniques.
The benefits of our approach can detect the
optimal solution, high accuracy, fast, and less
complexity.

24. For further questions:
Doaa Ali Mohammed
doaaali.ammar@yahoo.com