Case-based reasoning system for assessing water pollution /
نظام معتمد على الحالات لتقييم تلوث المياه
Asmaa Hashem Abdeltawab ; Supervised Osman Mohammed Hegazy , Aboul Ella Hassanien , Nashwa Elbendary
- Cairo : Asmaa Hashem Abdeltawab , 2016
- 83 Leaves : charts ; 30cm
Thesis (M.Sc.) - Cairo University - Faculty of Computers and Information - Department of Information System
Water pollution by organic materials or metals is one of the problems that threaten humanity, both nowadays and over the next decades. Morphological changes in Nile Tilapia 3Oreochromis niloticus3 sh liver and gills can also represent the adaptation strategies to main- tain some physiological functions or to assess acute and chronic expo- sure to chemicals found in water and sediments. This thesis provides an automatic system for assessing water pollution; in Sharkia gover- norate - Egypt, based on microscopic images of sh gills and liver. The proposed system used sh gills and liver as hybrid biomarker to detect water pollution. It utilized case based reasoning (CBR) for indicating the degree of water pollution based on the dierent histopathological changes in sh gills and liver microscopic images. Various performance evaluation metrics; namely, retrieval accuracy, Receiver Operating Characteristic (ROC) curves, F-measure, and G- mean, have been used in order to objectively indicate the true perfor- mance of the system considering the unbalanced data. Experimental results showed that the proposed hybrid biomarker CBR based sys- tem achieved water quality prediction accuracy of 97.9 % using cosine distance similarity measure. Also, it outperformed both SVMs and LDA classiers for the tested microscopic images data set