Neuro-fuzzy(NF)-based adaptive flood warning system for Bangladesh. Hossain, M., Turna, T., Soheli, S., & Kaiser, M. In 2014 International Conference on Informatics, Electronics and Vision, ICIEV 2014, 2014.
abstract   bibtex   
We have proposed neuro-fuzzy (NF) based flood warning system in this paper. The input data have been collected using wireless sensor network (WSN). The proposed model has collected input parameters, such as rainfall, river water level and river water flow, from a specific site and send the data to decentralized node. Based on the inputs, Adaptive Neuro-Fuzzy Inference System (ANFIS) model has determined the flood possibility index. All the decentralized nodes forward the pre-processed information to the centralized node for further processing. Depending on the last ten years data, The centralized node has compared the flood possibility index with the last ten years data stored in a database and then calculated flood persistence index by linguistic term Red, Yellow or Green on a GIS map. This model may also serve as a tool for real time flood monitoring and flood warning. © 2014 IEEE.
@inproceedings{
 title = {Neuro-fuzzy(NF)-based adaptive flood warning system for Bangladesh},
 type = {inproceedings},
 year = {2014},
 identifiers = {[object Object]},
 keywords = {Flood Persistency,Flood Possibility,Flood Warning System,Neuro Fuzzy,Wireless Sensor Network},
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 created = {2018-08-01T22:39:57.127Z},
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 abstract = {We have proposed neuro-fuzzy (NF) based flood warning system in this paper. The input data have been collected using wireless sensor network (WSN). The proposed model has collected input parameters, such as rainfall, river water level and river water flow, from a specific site and send the data to decentralized node. Based on the inputs, Adaptive Neuro-Fuzzy Inference System (ANFIS) model has determined the flood possibility index. All the decentralized nodes forward the pre-processed information to the centralized node for further processing. Depending on the last ten years data, The centralized node has compared the flood possibility index with the last ten years data stored in a database and then calculated flood persistence index by linguistic term Red, Yellow or Green on a GIS map. This model may also serve as a tool for real time flood monitoring and flood warning. © 2014 IEEE.},
 bibtype = {inproceedings},
 author = {Hossain, Md.E. and Turna, T.N. and Soheli, S.J. and Kaiser, M.S.},
 booktitle = {2014 International Conference on Informatics, Electronics and Vision, ICIEV 2014}
}

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