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

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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.

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A Modified Artificial Bee Colony Based Test Suite Generation Strategy for Uniform T-Way Testing

2020-03-20 , Rashid Ali M.S.A. , Rozmie Razif Othman , Zainor Ridzuan Yahya , Mohd Zamri Zahir Ahmad

Today, t-way testing has been widely known with the ability to reduce test suite size compared to exhaustive testing. At the same time, it has been proven by many researchers to provide maximum bug detection capability. Thus, various t-way strategies were developed since the past three decades. The paper proposed a new test generation strategy, named Modified Artificial Bee Colony T-Way Test Suite Generation (MABCTS). It supports uniform strength t-way testing. Experimentation results are compared with present strategies and produced comparable results. Since t-way testing is considered an NP-hard problem, there are no strategies that can be demanded to produce the best results.

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Hybrid Mahalanobis Taguchi System with Binary Whale Optimisation Feature Selection for the Wisconsin Breast Cancer Dataset

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.

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