Look into the future with the help of OpenWebGIS opengis.dlinkddns. Analysis and time series prediction subsystem in OpenWebGIS. For analyzing and forecasting of time series the method of singular spectrum analysis (SSA en.wikipedia.org/wiki/Singular_spectrum_analysis) is used in OpenWebGIS . Using an integral part of this method in OpenWebGIS, you can obtain the singular decomposition of the matrix. The results of Singular value decomposition of matrix (SVD-decomposition en.wikipedia.org/wiki/Singular_value_decomposition) can be used for other tasks of mathematical analysis. In OpenWebGIS SVD-decomposition algorithm is implemented on the basis of LINPACK (LAPACK) https://en.wikipedia.org/wiki/LINPACK. The version of the algorithm on the C programming language is translated into the programming language Javascript. In order to start the work with subsystem of analysis and time series prediction you need to select the menu item Calculations-> Time and matrix analysis. In many cases objects or processes and natural phenomena around us are the source of large amounts of diverse information, which can be collected and analyzed. The collected data often can be represented in the form of time series. For their effective research it is advisable to use an automated analysis, including forecasting of spatial and temporal distribution of various objects and settings. To analyze the dynamics of the time series and forecasting spatial-temporal distribution of objects in OpenWebGIS a powerful and fast-paced method of singular spectrum analysis is used. This method has some advantages in the prediction of irregular, non-stationary time series, taking place in the statistical observations of the actual technogenic or natural objects. OpenWebGIS provides visual interactive way to work with this method for the analysis and prediction of time series. The method of SSA (SSA) is used to decompose time series into additive components, which allows to solve the following tasks: - Selection of the trend in the changes of the processes under study; - Periodicities discovering in objects changes and their distribution; - Smoothing of the series, excluding the random errors (noise). In OpenWebGIS it is possible to analyze and predict the time series which have a spatial reference (coordinate) and those which do not have such binding (in this case, simply add the data columns coordinates having, for example a zero value). The results of the analysis and prediction of sea surface temperature in the region bounded by the following coordinates: Longitude 10W to 20W, Latitude 30N to 36N are shown in the attached screenshots. The temperature data: iridl.ldeo.columbia.edu/SOURCES/.IGOSS/.nmc/.Reyn_SmithOIv2/.monthly/.sst/T/463.5/643.5/RANGE/ngridtable/dataselection.html?limit.X.value=10W+to+20W&limit.Y.value=30N+to+36N&limit.T.value=Jan+2000+to+Aug+2013
Posted on: Thu, 09 Oct 2014 08:43:35 +0000
Trending Topics
Recently Viewed Topics
© 2015