Abstract. Under the background of the increasingly unified management of natural resources, remote sensing big-data will become the main data source to support a number of major projects. How to sample the natural resources results efficiently and reliably in the process of quality evaluation is always a research hotspot when it comes to the natural resources results involving remote sensing big-data. A sequential quality evaluation model based on root mean square error (RMSprop) optimization algorithm is constructed by theoretical analysis with an numerical experiments to validate the effectiveness of this method.
A Quality Evaluation Model for Distributed Processing Systems of Big Data