Optimizing Accuracy of the Variety Bitspaces for Weather Forecasting for Early Flight Safety. (March 2019) - Sukemi,; Rianto,; Bambang, BS.; Saputra, Yogi
Abstract: Different types of images when testing will give different results. Between still images and moving images requires speed and accuracy in the computation process. This is due to the availability of time in processing which tends to narrow at any time along with environmental changes. Retesting of processors that have been built through previous research requires the selection of new image data and processes. The selection of the new image refers to a different image and has never been used before. Next, for the new process by applying gaussian filtering selection. The results of the initial stage in testing some new images obtained that the bitspace adder/sub 32 bit (single-operand) accuracy value for cloud image data test without selector was 97.91% in the first cycle and without using filters block. While the architecture with the least significant bit method only produces an accuracy of 0.01% so that there is a very significant difference in accuracy, amounting to 97.90%. The last result if using filters block, the accuracy value is 98.75% at the first cycle with using filters block.