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This paper proposes age and periodic replacement last models with continuous, and discrete policies. That is, an operating unit is replaced preventively at time of operation as a strategic policy, or at a number of working cycles to satisfy successive job completion, whichever occurs last. Such policies are named as replacement last, and their expected cost rates and optimal policies are obtained...
The Gaussian radial basis function is widely used in the support vector machine (SVM) due to its attractive characteristics. The parameter (σ) in this kernel is crucial to robust performance of SVM. In this paper, we derive a formula to compute the optimal s under the principle of maximizing the class separability in the kernel space. The most attractive feature of the proposed method is that no optimization...
Failure Modes and Effects Analysis (FMEA) is an effective technique for identifying and eliminating possible failures. FMEA has been widely used in the manufacturing industry and in various phases of the life cycle of a product. The aim of FMEA is to ensure high quality and reliability. Design FMEA (DFMEA) is used to identify and analyze potential failure modes and their associated causes for product...
The bathtub-shaped curve is essential in interpreting the failure rate function for the reliability analysis, and its parameters determine the representation of the bathtub-shaped function. This paper introduces a parameterised bathtub curve that provides an adaptive bathtub-shaped failure rate function (ABF) modelling approach which can be also easily utilised as a universal objective for further...
Linear discriminant analysis (LDA) is a method of feature extraction that has demonstrated successful applications. The selection of the number of discriminant directions (r) is important to LDA, yet little attention is paid in the reported literature. In this paper a method is proposed for determining the optimal r in terms of the classification accuracy of support vector machine. The method is applied...
Recently Li et al. proposed a parameter selection method for Gaussian radial basis function (GRBF) in support vector machine (SVM). In his paper cosine similarity was calculated between two vectors based on the properties of GRBF kernel function. Li's method can determine an optimal sigma in SVM and thus efficiently improve its performance, yet it is limited by only focusing on a fixed original feature...
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