The neighbourhood algorithm is a two-stage numerical procedure for non-linear geophysical inverse problems. It also has applications as a direct search technique for global optimization.
Have a look at the world Map of people who have used the NA codes since 1st Sept. 2004.
Look at the locations of people who have visited this page since 7th Sept. 2007.
(See TerraWulf homepage for the latest information.)
(See list of papers for details.)
The first, search stage consists of a direct search method in a multidimensional parameter space. The objective is to find points (models) with acceptable (high or low) values of a user supplied objective function. It makes use of geometrical constructs known as Voronoi cells (shown above) in the search and appraisal stages. This algorithm is described in the papers below and implemented in the author's computer package `NA-sampler'. See the NA-sampler user guide for more details.
The second, appraisal stage consists of an algorithm for using the entire ensemble of models produced in stage I, and deriving information from them in the form of Bayesian measures of resolution, covariance and marginal PDF's etc. This algorithm is described in the papers below and implemented in the author's computer package `NA-Bayes'. See the NA-Bayes user guide for more details.
The author's computer package NA-sampler that implements the NA algorithm for the search problem, can be obtained from the author upon request. More details on the direct search code (i.e. what it does, how to use it etc.) are available by looking at the NA-sampler user guide . A separate code implementing the appraisal stage NA-Bayes, is also available. See the NA-Bayes user guide for more details.
Enquires should be directed to the author. If requesting the code then please state your name, institution and a short description of the type of problem you are considering applying it to. Note that, conditions are attached to use of the code and these can be found in the user guide.
In April 2002 the NA sampler package was updated to include In MPI (message passing interface) calls. This allows the forward modelling to be performed on different processors in parallel, e.g. on a Beowulf cluster of linux PCs.
The MPI option is activated by a switch during compilation and is transparent to the user. Tests have shown with that with MPI the forward modelling models in NA can be efficiently carried out on separate processors since minimal communication is required. With MPI and a unix cluster it should be possible to apply NA to problems where the cost of forward modelling is much higher. This is a current direction of research at RSES.
A list of all published papers using the NA (that I'm aware of) can be found here. Many can be downloaded.
The two original papers describing the neighbourhood algorithm are
Geophysical Inversion with a Neighbourhood Algorithm -I.
Searching a parameter space,
Geophysical Inversion with a Neighbourhood Algorithm -II.
Appraising the ensemble,
Please let me know if you publish a paper using the NA and I'll add it to the list.
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Last modified: December 2003.
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