We describe and analyse Levenberg–Marquardt methods for solving systems of nonlinear equations. More specifically, we first propose an adaptive formula for the Levenberg–Marquardt parameter and analyse the local convergence of the method under Hölder metric subregularity. We then introduce a bounded version of the Levenberg–Marquardt parameter and analyse the local convergence of the modified m...

Accomplishment of optimization technique on Object Oriented design component is a very challenging task. The prior model DyRM has introduced a technique to perform modeling of design reusability under three real-time constraints. The proposed study extends the DyRM model by incorporating optimization using multilayered perception techniques in neural network. The system takes the similar input ...

In this paper, Levenberg-Marquardt (LM) learning algorithm for a single Integrate-and-Fire Neuron (IFN) is proposed and tested for various applications in which a neural network based on multilayer perceptron is conventionally used. It is found that a single IFN is sufficient for the applications that require a number of neurons in different hidden layers of a conventional neural network. Sever...

This paper provides an effective method for parameter extraction of microelectronic devices and elements. A novel method, memetic differential evolution (MDE) algorithm, is proposed in this paper. By combining differential evolution (DE) algorithm, mutations in immune algorithm (IA), and special operators for parameter extraction, MDE possesses characteristics of high accuracy, stability, gener...

Background: Preterm births are babies that are born before 37 weeks of gestation. The premature delivery of babies is regarded as a major global public health issue with those affected at greater risk of developing short and long-term complications. The care provided for premature infants has significantly improved. However, it has had no impact on reducing the prevalence of preterm birth. Ther...

The present report establishes the computational issues that will be considered for the implementation of hybrid optimization approaches oriented to automated parameter estimation problems. The proposed hybrid optimization approaches are based on the coupling of the Simultaneous Perturbation Stochastic Approximation (SPSA) approach (a global and derivative free optimization method) with two loc...

Localization of proteins, a flourishing area in bioinformatics, can help us understand their respective functions. Currently there exist a number of localization approaches based on machine learning algorithms, and support vector machines (SVMs) have been used extensively. However, in terms of kernel optimization, a critical step in SVM design, there is no well-established systematic method so ...