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Vol. XII Issue VIII - August 2010
Project Management eJournal
FEATURED PAPER
Multi-parametric Models for Project Data Mining and Project Planning
By Pavel Barseghyan, PhD
Armenia & USA
Abstract
The main drawback of the statistical methodology of project data mining is the use of single approximation curves to replace the entire system of data, which leads to large errors in the estimation of parameters of new projects, subject to planning.
In this situation, the obvious solution of the problem is to use the families of curves instead of one approximation curve to replace the data. But we must bear in mind that the choice of analytic form of the approximation curves has a significant impact on the accuracy of estimates too. Selection of an appropriate analytical form of approximation curves can be controlled by top-down approach to the data mining process
Another important point in the new methodology for estimating the parameters of the projects is the consideration of the project goals and objectives. In this regard, the selection of such projects, which have the same goals and same priorities of these goals, is important to ensure the high accuracy of estimates.
For this kind of analysis is also important to have a quantitative representation of the hierarchy of project objectives to develop practical criteria for the project similarity by their goals and objectives.
This article is devoted to the development of new methodology of project data mining for the synthesis of projects based on input information on the project complexity, team productivity and the priorities of project objectives.
Key words: Project data mining, critique of data mining statistical methods, top-down methodology of project data mining, project synthesis and planning, TRANSCALE tool for top-down data mining and knowledge extraction.
To read entire paper (click here)
 About the Author Pavel Barseghyan, PhD Author Dr. Pavel Barseghyan is a consultant in the field of quantitative project management, project data mining and organizational science. He is the founder of Systemic PM, LLC, a project management company. Has over 40 years experience in academia, the electronics industry, the EDA industry and Project Management Research and tools development. During the period of 1999-2010 he was the Vice President of Research for Numetrics Management Systems. Prior to joining Numetrics, Dr. Barseghyan worked as an R&D manager at Infinite Technology Corp. in Texas. He was also a founder and the president of an EDA start-up company, DAN Technologies, Ltd. that focused on high-level chip design planning and RTL structural floor planning technologies. Before joining ITC, Dr. Barseghyan was head of the Electronic Design and CAD department at the State Engineering University of Armenia, focusing on development of the Theory of Massively Interconnected Systems and its applications to electronic design. During the period of 1975-1990, he was also a member of the University Educational Policy Commission for Electronic Design and CAD Direction in the Higher Education Ministry of the former USSR. Earlier in his career he was a senior researcher in Yerevan Research and Development Institute of Mathematical Machines (Armenia). He is an author of nine monographs and textbooks and more than 100 scientific articles in the area of quantitative project management, mathematical theory of human work, electronic design and EDA methodologies, and tools development. More than 10 Ph.D. degrees have been awarded under his supervision. Dr. Barseghyan holds an MS in Electrical Engineering (1967) and Ph.D. (1972) and Doctor of Technical Sciences (1990) in Computer Engineering from Yerevan Polytechnic Institute (Armenia). Pavel can be contacted at pavel@systemicpm.com. |
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