Sains Malaysiana 39(4)(2010): 661–670

Penyelesaian Masalah Data Ketakpastian  Menggunakan Splin-B Kabur

(Solving Problems of Uncertain Data using Fuzzy B-Spline)

Abd. Fatah Wahab*

Jabatan Matematik, Fakulti Sains dan Teknologi

Universiti Malaysia Terengganu, 21030 Kuala Terengganu, Malaysia

Jamaludin Md. Ali & Ahmad Abd. Majid

Sekolah Sains Matematik, Universiti Sains Malaysia, 11800 USM Pulau Pinang, Malaysia

Abu Osman Md. Tap

Jabatan IT, Universiti Islam Antarabangsa Malaysia, 53100 Gombak, Selangor, Malaysia

Received: 15 May 2009 /Accepted: 29 December 2009

ABSTRAK

Pembinaan model geometri berbantukan komputer (CAGD) dengan titik data yang mempunyai ketakpastian adalah sukar dan mencabar. Dalam kertas ini, pembinaan model splin-B kabur sebagai perwakilan matematik bagi lengkung dengan data ketakpastian menggunakan titik kawalan kabur dan titik kawalan penyahkaburan dibincangkan. Lengkung splin-B kabur atau splin-B penyahkaburan kubik untuk masalah data ketakpastian akan diperihalkan dengan menggunakan kaedah penghampiran splin-B kubik yang ditakrif menerusi titik kawalan kabur dan titik kawalan penyahkaburan. Bagi menyelesaikan masalah mengenai titik data ketakpastian pula, kaedah pengkaburan dan penyahkaburan titik data berkomponen kabur (penyahkaburan) beserta modelnya diperkenalkan. Bagi menguji tahap keberkesanan model, beberapa contoh lengkung simulasi data tersebut juga dibincangkan.

Kata kunci: Data ketakpastian; penyahkaburan; splin-B kabur; titik kawalan kabur

ABSTRACT

The construction of a geometric model in Computer Aided Geometrical Design (CAGD) with uncertain data points are difficult and challenging. In this paper, the construction of a fuzzy B-spline model as a mathematical representation for the curve of uncertain data using fuzzy control points and deffuzified control points is discussed. Cubic fuzzy B-spline or defuzzified B-spline curve for uncertainty data problems will be described using the cubic fuzzy B-spline approximation methods which are defined through fuzzy and defuzzification control points. For solving uncertain data, a method of fuzzification and defuzzification of component fuzzy (defuzzify) data point together with their model was introduced. For testing the effectiveness of the model, several examples of curve simulation of the given data are also discussed.

Keywords: Defuzzification; fuzzy B-Splie; fuzzy control points; uncertain data

REFERENCES

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*Corresponding author; email: fatah@umt.edu.my