Email this article ‘Quality & Popularity’ Prediction Modeling of TV Programme through Fuzzy QFD Approach
Abstract
In this paper we tried to dwell on to the problem of identifying the most important ‘Quality and Popularity contributing factors’, which plays an important role in deciding the ‘Popularity’ of a TV production.
We first tried to identify correctly the most important ‘Quality and popularity’ contributing factors of a TV programme which makes the TV programme more popular and successful, and then applied the knowledge of a most suitable scientific technique i.e. Fuzzy QFD in our situation, which would successfully incorporate these identified factors by establishing a proper correlation between these factors and the relative engineering requirements which used to effects these factors mostly if not considered at the time of production of the TV programme, and lastly we analyze our findings by simulating a most approximate ‘fuzzy inference rule’ based ‘Quality and Popularity’ prediction model.
Our model would rather help in deciding the best combination of identified characteristic, for which ‘Quality & popularity’ of the said TV programme will be predictable on a suitable linguistic scale, and could be kept high by maintaining the minimum required threshold of different identified characteristics.
Keywords
References
[1] Crespo, J., Sicilia, M.A, Garcia, E., Cuadrado J.J, “On Aggregating Second Level Software Estimation Cost Drivers: A Usability Cost Estimation Case Study”, Information Processing and Management of Uncertainty in Knowledge-Based Systems IPMU 2004, 1255- 1260, Perugia Italia.
[2] Harish Mittal, Pardeep Bhatia," Software Maintainability Assessment based on fuzzy logic Technique “ACM SIGSOFT Vol 34 No 3, May 2009.
[3] Hauser, J.R. and Clausing, D. (1996) the House of Quality, IEEE Engineering Management Review, Vol.24, No.1, spring, pp. 24-32
[4] Kaufman, A., GUPTA, M. M. (1985), Introduction the fuzzy arithmetic (New York: van Nostrand Reinhold).
[5] M. Ganesh, Introduction to Fuzzy Sets and Fuzzy Logic, PHI New Delhi 2006.
[6] Martins, A. and Aspinwall, E.M. (2001), Quality function deployment: an empirical study in the UK, Total Quality Management, Vol.12, No.5, pp. 575-588.
[7] Mamdani and Assilian-An Experiment in Linguistic Synthesis with a Fuzzy logic Controller, Int. Jour. of Man-Machine studies, Vol. 7, (1975)].
[8] Omachonu Vincent K. (1991). Total Quality and Productivity Management in Health Care Organization, ASQC Quality Press and Institute of Industrial Engineering, pp.136-150.
[9] Rao Ashok; Carr Lawrance P.; Dambolena Ismael; Kopp Robert J.; Martin John; Rafii Farshad; Schlesinger Phyliss Fineman (1996). Total Quality Management: A Cross Functional Perspective. John Wiley & Sons, Inc. pp.30-32.
[10] Tan K.C.; Xie M.; Chia E. (1998). “Quality Function Deployment and Its Use in Designing Information Technology Systems”. International Journal of Quality & Reliability Management, Vol.15, No.6, pp.634-645.
[11] Zimmermann, H. J., 1986, Fuzzy Sets Theory and its Applications (Netherlands: Kluwer Academic Publisher)
Full Text: PDF