Pauline Ong

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Modification of the intensification and diversification approaches in the recently developed cuckoo search algorithm (CSA) is performed. The alteration involves the implementation of adaptive step size adjustment strategy, and thus enabling faster convergence to the global optimal solutions. The feasibility of the proposed algorithm is validated against(More)
0957-4174/$ see front matter 2011 Elsevier Ltd. A doi:10.1016/j.eswa.2011.04.164 ⇑ Corresponding author. Tel.: +60 046533940; fax: E-mail address: (Z. Zainuddin). 1 Artificial neural network (ANN), central nervous sy (CT), distance similarity level (DSL), fuzzy c-mean algorithm (GA), glioma (GLO), k-means clustering (KM point symmetry-based(More)
In clinical practice, diagnostic dilemmas are frequently encountered in discriminating the heterogeneous cancers into distinct types. This paper reports an improved machine learning approach based on the wavelet neural network (WNN), which associates a feature selection method, namely, the conditional T-test. It is used in the development of cancer(More)
This paper investigates the feasibility and effectiveness of wavelet neural networks (WNNs) in the task of epileptic seizure detection. The electroencephalography (EEG) signals were first pre-processed using discrete wavelet transforms (DWTs). This was followed by the feature selection stage, where two sets of four representative summary statistics were(More)
Specifying the number and locations of the translation vectors for wavelet neural networks (WNNs) is of paramount significance as the quality of approximation may be drastically reduced if initialization of WNNs parameters was not done judiciously. In this paper, an enhanced fuzzy C-means algorithm, specifically the modified point symmetry–based fuzzy(More)
Wavelet neural networks (WNNs) were used to investigate the influence of operational variables in the soda-ethanol pulping of oil palm fronds (viz. NaOH concentration (10-30%), ethanol concentration (15-75%), cooking temperature (150-190 oC), and time (60-180 min)) on the resulting pulp and paper properties (viz. screened yield, kappa number, tensile index,(More)
Designing a wavelet neural network (WNN) needs to be done judiciously in attaining the optimal generalization performance. Its prediction competence relies highly on the initial value of translation vectors. However, there is no established solution in determining the appropriate initial value for the translation vectors at this moment. In this paper, we(More)