توضیحات
ABSTRACT
In this paper, adaptive neurob-fuzzy inference system ANFIS is used to assess conditions required for aquatic systems to serve as a sink for metal removal; it is used to generate information on the behavior of heavy metals (mercury) in water in relation to its uptake by bio-species (e.g. bacteria, fungi, algae, etc.) and adsorption to sediments. The approach of this research entails training fuzzy inference system by neural networks. The process is useful when there is interrela-tion between variables and no enough experience about mercury behavior, furthermore it is easy and fast process. Ex-perimental work on mercury removal in wetlands for specific environmental conditions was previously conducted in bench scale at Concordia University laboratories. Fuzzy inference system FIS is constructed comprising knowledge base (i.e. premises and conclusions), fuzzy sets, and fuzzy rules.
INTRODUCTION
The release of heavy metals from industries into the en-vironment has resulted in many problems for both human health and aquatic ecosystems [1,2].Heavy metals re-leased into the environment by technological activities tend to persist indefinitely,circulating and eventually accumulating throughout the food chain, becoming a serious threat to the environment [3]. The presence of heavy metals in the environment is of major concern be- cause of their toxicity,bio-accumulating tendency, threat to human life and the environment [4,5].
Year:2012
Publisher:Journal of Water Resource and Protection
By:Ahmad Qasaimeh, Mohammad Abdallah, Falah Bani Hani
File information: English Language / 8 Page / Size :542 KB
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سال: 2012
ناشر:Journal of Water Resource and Protection
کاری از:Ahmad Qasaimeh, Mohammad Abdallah, Falah Bani Hani
اطلاعات فایل: زبان انگلیسی/ 8 صفحه/ حجم 542 کیلوبایت
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