An introduction to genetic algorithms
An introduction to genetic algorithms
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Using Genetic Algorithm to Optimize Artificial Neural Network: A Case Study on Earthquake Prediction
WGEC '08 Proceedings of the 2008 Second International Conference on Genetic and Evolutionary Computing
Fourier spectral analysis for unevenly spaced, average value, data
Computers & Geosciences
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Recent studies warn of a possible major earthquake off the coast of State of Guerrero, Mexico, so that, it turns important to alert the population as long as possible and avoid a great disaster. This requires the construction of a network of seismic sensing stations, located at strategical positions, to detect earthquakes and issue a timely warning. In this research, we investigate how a genetic algorithm can be applied to design this network and determine the optimal location of each seismic sensing station. The number of earthquakes detected by the designed network will be used as a reference point with respect to the currently installed seismic alert system (SAS). This metric will justify the use of the genetic algorithms as a designing tool prior to the construction of the network in different regions of Mexico. The SAS stations and each solution proposed by a genetic algorithm underwent a procedure, in which it is simulated the occurrence of earthquakes obtained from the Mexico's National Seismological Service (SSN) database, to determinate its efficiency in terms of the time to warn Mexico City.