WSEAS Transactions on Environment and Development
Print ISSN: 1790-5079, E-ISSN: 2224-3496
Volume 12, 2016
A Neurofuzzy System for Safer Gas Supply: An Application to Seismic Emergencies
Authors: ,
Abstract: In order to achieve an efficient real-time system for disaster mitigation, the most extensive high-density seismic motions/flow conditions monitoring in Mexico City is being developed. Known as SISES, the proposed system employs a soft coding for evaluating shaking intensity and for setting in operation district remote regulators (valves), strategically installed in the gas supply area. Micromachining technology is used for measuring ground acceleration, detecting abnormal gas flow conditions, and for fuzzy control of regulators. The SISES configuration is designed for high-precision estimations of damage and failures detection in real time. Dynamic neural networks are used for forecasting the surface distribution of seismic motions and for constructing the premises and conclusions for cutting-off or continuing the gas supply, fuzzy logic is employed. The SISES operation is very precise, simple, and highly reliable. Emerging technologies and methodologies are included in SISES conception as a part of the responsibility of gas suppliers and scientific/technologic community to assure safety particularly during severe earthquakes.
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Keywords: seismic emergency systems, safe natural gas supply, PGA prediction, fuzzy logic systems, neural networks, soft data management
Pages: 314-325
WSEAS Transactions on Environment and Development, ISSN / E-ISSN: 1790-5079 / 2224-3496, Volume 12, 2016, Art. #32