Locating Seismic-Sense Stations Through Genetic Algorithm

Items for entering the "HUMIES"

1.	Locating Seismic-Sense Stations Through Genetic Algorithm

2.	Josafath I. Espinosa-Ramos 
	Intelligent Systems Group 
	Faculty of Engineering - La Salle University
	Benjamín Franklin 47 Col. Condesa CP 06140 México, D.F. 
	vjier@prodigy.net.mx
	52 55 57873473

	Roberto A. Vázquez 
	Intelligent Systems Group 
	Faculty of Engineering - La Salle University 
	Benjamín Franklin 47 Col. Condesa CP 06140 México, D.F. 
	ravem@lasallistas.org.mx
	52 55 52789500 ext 2391

3.	Josafath I. Espinosa-Ramos 

4.	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 seismic sense stations at strategical locations to detect earthquakes and issue a timely warning. For this particular research, the implementation of a genetic algorithm was chosen to determine the optimal location of seismic sensing stations in State of Guerrero. The number of earthquakes detected by the network's stations will be used as a reference point with respect to the currently installed seismic alert system (SAS) and will justify the use of genetic algorithms as a designing tool prior to the construction of other networks' stations in other states of Mexico. SAS stations and each solution proposed by 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 time to warn Mexico City.

5.	Criteria
	D) The result is publishable in its own right as a new scientific result independent of the fact that the result was mechanically created.
	F) The result is equal to or better than a result that was considered an achievement in its field at the time it was first discovered.

6.	Since December of 1989, CIRES develops the seismic alert system of Mexico City, SAS.  The primary function of the SAS is to issue a public warning to Mexico City when it detects an earthquake of magnitude greater than 5.0° on the Richter scale. This system is capable of alerting the population up to 60 seconds before the seismic wave reaches Mexico City.  
	In our research, the genetic algorithm provides a better solution for the location of the seismic stations of a simulated alert system. Through several experiments, we observed that the time to alert the population of Mexico City was about 90 seconds, 50% higher than the current configuration of the current SAS.
	Referring to the eight criteria for establishing that an automatically created result is competitive with a human-produced result, locating seismic-sense stations through genetic algorithm satisfies the following two of the eight criteria:

	D) The result is publishable in its own right as a new scientific result independent of the fact that the result was mechanically created.
	F) The result is equal to or better than a result that was considered an achievement in its field at the time it was first discovered.

7.	Josafath I. Espinosa-Ramos, Roberto A. Vazquez; july 2011; Genetic and Evolutionary Computation Conference GECCO 2011, Dublin Ireland.

8.	Any prize money will be divided among the two co-authors. 

9.	It is important to determine the strategical location and construction of sensor stations to detect earthquakes and prevent the population as fast as possible. It gives us the opportunity to execute procedures and actions that reduce the possibility of having a disaster when an earthquake happens, before the seismic weave reaches a specific City. Also, these systems are useful resources that improve the results of designing and practicing simulacrums to reduce seismic vulnerability.