Zainor Ridzuan Yahya
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Zainor Ridzuan Yahya
Official Name
Zainor Ridzuan, Yahya
Alternative Name
Yahya, Zainor Ridzuan
Yahya, Z. R.
Ridzuan Yahya, Zainor
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Scopus Author ID
50862369800
Researcher ID
GNH-4483-2022

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  • Publication
    Artificial bee colony for curve reconstruction using quartic bézier
    (Little Lion Scientific, 2022-03-31)
    Nur' Afifah Rusdi
    ;
    Zainor Ridzuan Yahya
    ;
    Wan Zuki Azman Wan Muhamad
    ;
    Nurshazneem Roslan
    This work presents the use of Artificial Bee Colony Algorithm (ABC) for curve reconstruction using Quartic Bézier. Quartic Bézier curve is rarely used by the researchers in the application of medical images. Therefore, by increasing the degree of the Bézier curve, a better curve with small error can be obtain. The process of curve reconstruction involved was boundary and corner point detection of the medical image, parameterization and curve reconstruction by using ABC. By applying these processes, the fitted Quartic Bézier is obtained. The Sum Square Error (SSE) is used to record the error between the fitted Quartic Bézier curve with the original image. The results of SSE is recorded after the process is repeated 10 times with the average error of 3.4463e03 . Because the final output of the fitted curve resembles the original image, the suggested method can be considered as an option method for curve reconstruction applications. ABC algorithm is an interesting algorithm that can be explored in more detail and can be applied in various problems.
      3  10
  • Publication
    A survey on improvement of Mahalanobis Taguchi system and its application
    ( 2023-11-01)
    Tan L.M.
    ;
    Wan Zuki Azman Wan Muhamad
    ;
    Zainor Ridzuan Yahya
    ;
    Ahmad Kadri Junoh
    ;
    Nor Hizamiyani Abdul Azziz
    ;
    Ramlie F.
    ;
    Harudin N.
    ;
    Abu M.Y.
    ;
    Tan X.J.
    Mahalanobis Taguchi System (MTS) is used for pattern recognition and classification, diagnosis, and prediction of a multivariate data set. Mahalanobis Distance (MD), orthogonal array (OA), and signal-to-noise ratio (SNR) are used in traditional MTS in order to identify and optimize the variables. However, the high correlation among variables shows an effect on the inverse of the correlation matrix that uses in the calculation of MD and hence affects the accuracy of the MD. Therefore, Mahalanobis-Taguchi-Gram-Schmidt (MTGS) system is proposed in order to solve the problem of multicollinearity. The value of MD can be calculated by using the Gram-Schmidt Orthogonalization Process (GSOP). Besides, the computational speed and the accuracy in optimization using OA and SNR are other issues that are concerned the authors. Hence, the combination of MTS and other methods such as Binary Particles Swarm Optimization (BPSO) and Binary Ant Colony Optimization (NBACO) is proposed to improve the computational speed and the accuracy in optimization. The purpose of this paper is to review and summarize some works that developed and used the hybrid methodology of MTS as well as its application in several fields. Moreover, a discussion about the future work that can be done related to MTS is carried out.
      1  41
  • Publication
    Hybrid Mahalanobis Taguchi System with Binary Whale Optimisation Feature Selection for the Wisconsin Breast Cancer Dataset
    (Semarak Ilmu Publishing, 2023)
    Chow Yong Huan
    ;
    Wan Zuki Azman Wan Muhamad
    ;
    Zainor Ridzuan Yahya
    ;
    Nor Hizamiyani Abdul Azziz
    ;
    Tan Chye Lih
    ;
    Tan Xiao Jian
    The Mahalanobis-Taguchi System (MTS) is a statistical approach used in breast cancer research to facilitate early detection and promote efficient treatment. The technique analyses mammogram images for significant features using a multivariate statistical analysis technique. It combines the Mahalanobis distance (MD) and Taguchi's method to determine the differences between benign and malignant samples. While orthogonal array (OA) has been widely used in MTS, it has been criticised for providing suboptimal results due to insufficient coverage of feature combinations during the feature optimisation process. To address this issue, the Binary Whale Optimisation Algorithm (BWOA) is proposed as an improved search algorithm for MTS. This paper aims to develop a novel hybrid method that enhances the efficiency of the Mahalanobis Taguchi System (MTS). The performance of feature selection ability due to different MTS hybrid algorithms were also compared. BWOA simulates the hunting behaviour of humpback whales and works by exploring new regions of the solution space, gradually narrowing the search space, and fine-tuning the solution. MTS-BWOA demonstrated its enhanced capability in feature optimisation compared to traditional MTS methods and has the potential to be applied in other medical imaging domains.
      16  2