Induced Extended Fuzzy Clustering Method (IEFCLM) for Uncertainty
Srimathi V1, Bennilo Fernandes J2
1Srimathi V, Department of Mathematics, Guru Nanak College, Chennai (Tamil Nadu), India.
2Bennilo Fernandes J, Department of ECE, Koneru Lakshmaiah Education Foundation, (Andhra Pradesh) India.
Manuscript received on 01 May 2019 | Revised Manuscript received on 15 May 2019 | Manuscript published on 30 May 2019 | PP: 1150-1152 | Volume-8 Issue-7, May 2019 | Retrieval Number: G6345058719/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The Act 1995 seriously started taking policy decisions to rehabilitate the PWDs by allotting funds and implementing programs, though not to the full satisfaction of PWDs. The rural PWDs are yet to be sensitized on their rights as per the Act. Assuring by a NGO in Melmalayanur District found over eighty percent of PWDs not having the basic Natural ID card, require for availing and rehabilitation measures. In this paper the difficulties faced by the rural deprived PWDs were analyzed using Induced Extended Fuzzy Clustering Model (IEFCLM). There are four sections. Section one describes the PWDs, giving the historical background. Section two gives the methodology of hidden pattern of Induced Extended Fuzzy Clustering method. Section three discussesthe study using IEFCLM. Fourth section givesthe result of the study.
Keyword: Fuzzification, Induced FCM, Extended FCM, Algorithm, Persons with Disabiblites.
Scope of the Article: Clustering.