An Intelligent Smart Ranked Feature Construction Analysis based on Multi-dimensional Data Streams
1Dr.V. Sellam, K. Sudhars an, K.H. Ajit Baskar and K.H. Ajay Baskar
To determine the consequence of force, load, acceleration, deformation and displacement in structures in an construction through the live images taken in the construction site and improving the quality of the images using Bayesian Sequential Algorithm (BSP)in construction analysis. Generally the construction site should need heavy monitoring done by the engineers for analysing the consequence of force, load, acceleration, deformation and displacement in structures. The data streams which we are using in our proposed system are always has the ability to adapt with the changes caused by the stream where the memory footprint and execution efficiency is decreased. The problem statement is that live images that is used for effective analysing is not so clear and can’t able to find out the accurate datasets in structures. So we are using Bayesian sequencial algorithm to improve the quality of the image. Based on this abstract model we introduce Bayesian Sequential Algorithm. Observation on both low and high dimensional data streams, endorse our proposed algorithm.
Acceleration, Force, Efficiency, Datasets, Data Streams.