Volume 66 | Issue 8 | Year 2020 | Article Id. IJMTT-V66I8P507 | DOI : https://doi.org/10.14445/22315373/IJMTT-V66I8P507
In Africa, the population of senior citizens (60 years and above) has increased rapidly from 12 million in 1950 to over 64.5 million in 2015. It is projected to reach 103 million by 2030 and 205 million by 2050. Majority of the African senior citizens are living in extreme poverty in rural areas. In the present African society, senior citizens are not given much importance in their families and expected to face sorrow till end of their last breathe. Senior citizens are treated as a burden in their families and given least care by the African society. Therefore, the objective of this paper is to demonstrate how discrimination affects senior citizens livelihoods in the society through Linguistic Delphi Adapted Fuzzy Associative Memories. Using Fuzzy Number and Fuzzy Associative memories, the relationship between causes and effects of the senior citizens discrimination is elucidated. Delphi Adapted Fuzzy Associative Memories (DAFAM) and algorithm was used to gather consensus of opinions, attitudes and choices of the society towards the senior citizens. DAFAM was used with expert’s views to create one relational matrix. The expert’s view deals statistically with several process of feedback from the group that gives the final prediction of consensus. The problem was further adapted to Linguistic Delphi Adapted Fuzzy Associative Memories model to analyse the impact of discrimination of senior citizens to their livelihoods. Finally, it was concluded that the attitude of the people should change towards senior citizens so that the problems faced by them in the society can be lessened.
[1] United Nations, Department of Economic and Social Affairs, Population Division (2015). World Population Ageing 2015 - Highlights (ST/ESA/SER.A/368).
[2] https://www.who.int/news-room/fact-sheets/detail/ageing-and-health Retrieved on 10th January, 2020.
[3] United Nations, Department of Economic and Social Affairs, Population Division (2015). World Population Ageing 2015 (ST/ESA/SER.A/390).
[4] Whitman, N. (1990). The committee meeting alternative: Using the Delphi technique. JONA, 20, 30–36. WHO. 1999. Ageing: Exploding the Myth. WHO, WHO/HSC/AHE/99.1. Geneva.
[5] Zadeh, L. A. (1975). The concept of a linguistic variable and its application to approximate reasoning (Part II). Information Science, 8: 301–357.
[6] Zadeh, L. A. (1965). Fuzzy sets. Information Control, 8(3), 338–353.
[7] Kosko, B. (1997). FUZZY ENGINEERING. Prentice Hall, Upper Sad- dle River, NJ, USA.
[8] Devadoss, A. V. and Christopher, S. (2013). The Effect of Globalisation on Education using Fuzzy Associative Memories. Indo-BhutanInternational Conference on Gross National Happiness, 2, 178-192.
[9] Dalkey, N. and Helmer, O. (1963). An Experimental Application of the Delphi Method to the use of the Experts. Management Science, 9 (3), 458-467.
[10] Hwang, C. L. and Lin, M. J. (1987).Group decision making under multiple criteria: Methods and applications. Springer-Verlag
[11] Khorramshahgol, R. and Moustakis, V. S. (1988). Delphi hierarchy process (DHP): A methodology for priority setting derived from the Delphi method and analytical hierarchy process. European Journal of Operational Research. 137, 347-354.
[12] Skutsch, M. and Hall, D. (1973). Delphi: Potential uses in education planning. In J. L. Barnes, (1987). An international study of curricular organizers for the study of technology. Unpublished doctoral dissertation, Virginia Polytechnic Institute and State University, Blacksburg, Virginia.
[13] Yousuf, M. I. (2007). Using experts opinion through Delphi Technique. Practical Assessment, Research & Evaluation, 12 (4), 1-7.
[14] Rowe, G., Wright, G. and Bolger, F. (1991). The Delphi technique: a re-evaluation of research and theory. Technological Forecasting and Social Change, 39 (3), 235–251.
[15] Prakash, A. P. and Vanathi, N. (2015). Delphi Triangular Fuzzy Cognitive Map (DTFCM). International journal of applied Engineering Research, 10 (80), 250-252.
[16] Thach, E. C. and Murphy, K. L. (1995). Competencies for distance education professionals. Educational Technology Research and Development, 43 (1), 57-79.
[17] Smith, M.A. (1997). Perceptions of Quality in Journalism and Communication Education: A Delphi Study. Journal of the Association for Communication Administration, 1, 32–50.
[18] Brill, J.M., Kim, D. and Branch, R.M. (2001). Visual literacy defined: the results of a Delphi study - can IVLA (operationally) define visual literacy? In R. E. Griffen, V. S. Williams & J. Lee (Eds.), Exploring the visual future: art design, science and technology. (pp. 9-15) Blacksburg, VA: The International Visual Literacy Association.
[19] Addison, T. (2003). E-commerce project development risks: evidence from a Delphi survey. International Journal of Information Management, 23, 25–40.
[20] Beales, R. (2005). Delphi creates fresh CDS challenge: a new cash-settlement method for simplifying credit derivatives faces a stern test with the latest bankruptcy, writes Richard Beales (capital markets & commodities). The Financial Times, p. 43
[21] Landeta, J. (2006). Current validity of the Delphi method in social sciences. Technological Forecasting and Social Change, 73 (5), 467-82.
[22] Grisham, T. (2009). The Delphi Techniques a method for testing complex and multifaceted topics. International Journal of Managing project in Business, 2 (1), 112-130.
[23] Samman, T. A. S. A. and Brahemi, R. M. R. A. (2014). Fuzzy Pert For Project Management. International Journal of Advances in Engineering and Technology, 7 (4), 1150-1160.
[24] Teijlingen, E., Pitchforth, E., Bishop, C. and Russell, E. (2006). Delphi method and nominal group technique in family planning and reproductive health research. J. Fam. Plann. Reprod. Health Care, 32 (4) 249–252.
[25] Murray, T. J., Pipino, L. L. and Gigch, J. P. Van. (1985). A Pilot Study of fuzzy set modification of Delphi. Human System Management, 5, 76–80
[26] Hsu, Y., Lee, C. H. and Kreng, V. E. (2010). The Application of Fuzzy Delphi Method and Fuzzy AHP in lubricant regenerative technology selection. Experts system with Applications, 37 (1), 419-405.
[27] Chen, T. Y. and Ku, T. C. (2008). Importance-Assessing Method with Fuzzy Number-Valued Fuzzy Measures and Discussions on TFNs And TrFNs. International Journal of Fuzzy systems, 10 (2), 92-103.
[28] Devadoss, A. V. and Ajay, D. and Sudha, K. (2014). Delphi Adapted Fuzzy Associative Memories as a multiple expert system and its application to study the impact of climate change on Environment. International Journal of communication and networking system, 3, 256-260.
[29] Yasir, S. and Muhammad, S. (2012). Factors explaining the discrimination and health status of senior citizen: A descriptive study of Chakwal, Pakistan. Journal of International Academic Research, 12, 1-9.
Muluken Admasu, Ashager Adane, "Scrutinizing the Discrimination of African Senior Citizens through Linguistic Delphi Adapted Fuzzy Associative Memories," International Journal of Mathematics Trends and Technology (IJMTT), vol. 66, no. 8, pp. 60-71, 2020. Crossref, https://doi.org/10.14445/22315373/IJMTT-V66I8P507