The experience of several authors has shown that continuous measurements of the gravity ﬁeld, accomplished through springdevices, are strongly affected by changes of the ambient temperature. The apparent, temperature-driven, gravity changes can beup to one order of magnitude higher than the expected changes of the gravity ﬁeld. Since these effects are frequency-dependentand instrument-related, they must be removed through non-linear techniques and in a case-by-case fashion. Past studies havedemonstrated the effectiveness of a Neuro-Fuzzy algorithm as a tool to reduce continuous gravity sequences for the effect ofexternal temperature changes. In the present work, an upgraded version of this previously employed algorithm is tested againstthe signal from a gravimeter, which was installed in two different sites over consecutive 96-day and 163-day periods. The betterperformance of the new algorithm with respect to the previous one is proven. Besides, inferences about the site and/or seasonaldependence of the model structure are reported.
|Titolo:||A new computational approach to reduce the signal from continuously recording gravimeters for the effect of atmospheric temperature|
|Data di pubblicazione:||2006|
|Citazione:||A new computational approach to reduce the signal from continuously recording gravimeters for the effect of atmospheric temperature / ANDO' B; CARBONE D. - In: PHYSICS OF THE EARTH AND PLANETARY INTERIORS. - ISSN 0031-9201. - 159, 3-4(2006), pp. 247-256.|
|Appare nelle tipologie:||1.1 Articolo in rivista|