We proposed another methodology for travel time prediction which is also an efficient and scalable method. We introduced a new technique namely, Cumulative Cloning Average (CCA) there. We hope that researchers or readers will be beneficial by our this efforts. We also published a paper in the “International journal of Data Engineering” about our research. We recommend readers to visit this site .
Recently, our next research paper was published in 14th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES-2010). In that paper, we modified the traditional K-means clustering procedure and our predictor forecasts the travel time more accurately than other existing methods. You can download that paper by clicking MKC
In our recently published research paper (KES 2009-Development of effective travel time using modified moving average–NKC,RPDN,HL,JC–J.D. Velásquez et al. (Eds.): KES 2009, Part I, LNAI 5711, pp. 130–138, 2009. © Springer-Verlag Berlin Heidelberg 2009), we focused two new methods namely: Successive Moving Average (SMA) and Chain Average (CA). Both formulas give a good impact on performance. For understanding detail, you can click Successive Moving Average and Chain Average .
For the purpose of world wide knowledge globalization and sharing, I motivated myself to build this block. I will try to focus the outline of my current research domain as well as the current challenging, interesting and dominating research arena. As I am an oracle certified core DBA (ocp10gdba), posts related with oracle will also be emphasized in this blog. To enrich our country in advance technology and information, no alternation of research is available. Only by research and analysis we can earn proud for our country, tradition as well as our language.
rudrapratapdebnath
Rudra Pratap Deb Nath 