Paper Title: Levying and Anticipate of a Structural Project using our In-depth Analysis process

Author's name: M.SIVA, Dr. S. ARUMUGAM

In modern world predicting the possible outcome is a huge task and in our day to day life usage of technology becomes the part of our life. A better understanding of how momentum is absorbed into the initial non-negative terms in the pressure expression of a shock wave is made possible by Momentum-incorporated Symmetric Non-negative (MSNS), an analytical and computational tool. We focus on the scenario with negative momentum in particular. Latent Factor Models (LFM) is a statistical method for estimating the association between latent variables derived from a collection of items or instances and observable data, which is the dependent variable. The LFM approach, in essence, enables us to quantify the contribution that each item makes to the estimation of an outcome variable. In recent years, technology has start eddo play a significant role in the area of research. That to the process of construction research and analysis takes a huge part, which becomes more fruitful if we reduce the waiting time through our analysis process and by getting the price estimation. Here Qualitative research was quickly adapted and aided by the technology. This qualitative research is done through the process of Qualitative Data Analysis (QDA) process, which helps in the in-depth analysis. It is also used in statistics, which is also known as the categorical data. Next Theil-Sen estimator, which has been proposed as preferable to least squares estimation due to its high precision in the presence of data. Here we predict the estimation with high efficiency, and accuracy level is very high.

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