Gregoire, In order to answer your question, you should first define a criterion (when is a network 'optimal'?). If the criterion is to minimise the spatially averaged kriging variance (or something similar) then you might conisder the work done by Jan Willem van Groenigen in the 90s. He used a numerical optimisation approach (i.e., simulated annealing), which takes computer time but is very flexible and can handle irregulary shaped areas as well as situations in which there are given, fixed, prior locations. If the criterion is to minimise the maximum distance from any point in the area to the nearest sampling point, then you can use a technique described by Dick J Brus, which is very fast. Dick adapted the k-means cluster algorithm for this purpose. Gerard
-----Original Message----- From: Gregoire Dubois [mailto:[EMAIL PROTECTED] Sent: Thu 12/01/2006 18:17 To: 'Michel BOBBIA' Cc: ai-geostats@unil.ch Subject: RE: [ai-geostats] Optimization of monitoring networks Dear Michel, Good idea ! I remember some of Werner Müller's papers and presentations but, as far as I remember, he was not considering the impact of complex border effects coming from the shape of the borders of the monitored area and was mainly talking about optimizing sensor locations considering the spatial correlation of the monitored phenomenon. Does his book discuss optimization regardless of the monitored phenomenon? I guess answers to my question can be found in the field of mathematical morphology but had no chance so far to find anything useful to me. I guess people installing emitters/antennas for mobile phones have answers to my question.. Thanks, Gregoire __________________________________________ Gregoire Dubois (Ph.D.) European Commission (EC) Joint Research Centre (JRC) WWW: http://www.ai-geostats.org <http://www.ai-geostats.org/> "The views expressed are purely those of the writer and may not in any circumstances be regarded as stating an official position of the European Commission." -----Original Message----- From: Michel BOBBIA [mailto:[EMAIL PROTECTED] Sent: 12 January 2006 17:23 To: ai-geostats@unil.ch Subject: Re: [ai-geostats] Optimization of monitoring networks Hello I have buy a book that seems to deal with this subject : Werner G. Müller Collecting Spatial Date Optimum Design of Experiments for Random Fields second edition Physica-Verlag (Springer) Unfortunatly, my knowledge in design of experiments is not enough to understand the book, but I am reading it carefully... However, I am interested in any solution/information to this problem ! Regards Michel BOBBIA Air Normand ----- Original Message ----- From: Gregoire Dubois <mailto:[EMAIL PROTECTED]> To: ai-geostats@unil.ch Sent: Thursday, January 12, 2006 3:00 PM Subject: [ai-geostats] Optimization of monitoring networks Dear list, I am looking for references (and possibly software) on network optimization. The variable monitored has no importance and I am looking for references and topological algorithms. A question I have is the following: given an area A with a particular shape (e.g. defined by country borders) and a number of stations N (e.g. for mobile phone emitters), how do I define the optimal locations for these stations? Thanks for any hints. Gregoire __________________________________________ Gregoire Dubois (Ph.D.) European Commission (EC) Joint Research Centre (JRC) Institute for Environment and Sustainability (IES) TP 441, Via Fermi 1 21020 Ispra (VA) ITALY Tel. +39 (0)332 78 6360 Fax. +39 (0)332 78 5466 Email: [EMAIL PROTECTED] WWW: http://www.ai-geostats.org <http://www.ai-geostats.org> WWW: http://rem.jrc.cec.eu.int <http://rem.jrc.cec.eu.int> "The views expressed are purely those of the writer and may not in any circumstances be regarded as stating an official position of the European Commission." _____ * By using the ai-geostats mailing list you agree to follow its rules ( see http://www.ai-geostats.org/help_ai-geostats.htm ) * To unsubscribe to ai-geostats, send the following in the subject or in the body (plain text format) of an email message to [EMAIL PROTECTED] Signoff ai-geostats
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