- author = "Frank D. Francone and Larry M. Deschaine and Jeffrey J. Warren",
- title = "Discrimination of munitions and explosives of concern at {F.E. Warren AFB} using linear genetic programming",
- booktitle = "GECCO '07: Proceedings of the 9th annual conference on Genetic and evolutionary computation",
- year = "2007",
- editor = "Dirk Thierens and Hans-Georg Beyer and Josh Bongard and Jurgen Branke and John Andrew Clark and Dave Cliff and Clare Bates Congdon and Kalyanmoy Deb and Benjamin Doerr and Tim Kovacs and Sanjeev Kumar and Julian F. Miller and Jason Moore and Frank Neumann and Martin Pelikan and Riccardo Poli and Kumara Sastry and Kenneth Owen Stanley and Thomas Stutzle and Richard A Watson and Ingo Wegener",
- volume = "2",
- isbn13 = "978-1-59593-697-4",
- pages = "1999--2006",
- address = "London",
-
URL = "
http://gpbib.cs.ucl.ac.uk/gecco2007/docs/p1999.pdf",
-
DOI = "
doi:10.1145/1276958.1277353",
- publisher = "ACM Press",
- publisher_address = "New York, NY, USA",
- month = "7-11 " # jul,
- organisation = "ACM SIGEVO (formerly ISGEC)",
- keywords = "genetic algorithms, genetic programming, Real-World Applications, Discipulus, economics, EM61 MK2, geophysics, linear genetic programming, measurement, MEC, munitions and explosives of concern, unexploded ordnance, UXO, verification",
- abstract = "Removing underground, unexploded bombs, mortars, cannon shells and other ordnance (MEC or UXO) from former military ranges is difficult and expensive. The principal difficulty is discriminating intact, underground ordnance from other metallic items such as fragments of exploded ordnance (Clutter), magnetic rocks, and historic items such as horseshoes, barbed-wire, and refrigerators. This study represents the first, large-scale, blind-test of MEC discrimination technology on production-grade, survey-mode data from the cleanup of a real impact site. The results reported here significantly advance the state-of-the-art in MEC discrimination over alternative forward modelling/ inversion approaches to performing MEC discrimination. We combined Linear Genetic Programming (LGP) and statistical analysis to process data from the cleanup of 600 acres of the F.E.Warren Air Force Base. These data contained almost 30,000 targets of interest identified by geophysicists, including three-hundred thirty-two 75mm projectiles (75mm) and 37mm projectiles (37mm). A little under one-third of the ground truth was held back by the customer for blind-testing. Our task was to discriminate intact 37mm and 75mm from the clutter by ordering the targets from most-likely to be MEC to least-likely to be MEC in what is referred to as a prioritised dig list. We identified all 75mm by 28.2percent of the way through our prioritized dig-list and all 37mm by 64.2percent of the way through the prioritised dig list. Thus, depending on ordnance type, we reduced the number of targets that had to be excavated (false alarms) to clear the entire site by between 35percent and 72percent.",
-
notes = "GECCO-2007 A joint meeting of the sixteenth
international conference on genetic algorithms
(ICGA-2007) and the twelfth annual genetic programming
conference (GP-2007).
ACM Order Number 910071",
