Maharani Abu Bakar

Universiti Malaysia Terengganu | umt · Applied Mathematics

Deep Neural Networks (DNN) have a long time to be proven as universal function estimators. Recently, researchers have emerged DNN as an approximator for differential equation (DE) solutions which improved the conventional numerical methods without the discretization process. In this paper, we modified the DNN architecture to solve the DE problems b...

This paper discusses the numerical simulations of heat transfer problem, particularly during the welding materials processing. This process highly depends on the temperature to determine the metallurgical properties, the strength, and the sureness of the joint during welding; hence it is desirable to study its heat flow. Finite difference method (F...

Traditionally, partial differential equation (PDE) problems are solved numerically through a discretization process. Iterative methods are then used to determine the algebraic system generated by this process. Recently, scientists have emerged artificial neural networks (ANNs), which solve PDE problems without a discretization process. Therefore, i...

The numerical solution of a ordinary differential equation (ODE) basically describes any physical phenomenon of interest. Traditionally, the numerical solution of ODE is solved by a discretization process using the classical finite difference approximation. Recently, many studies have used deep neural networks (DNN) to approximate ODE solutions wit...

Machine learning (ML) has shown a significant development in the application of several fields such as sciences, engineering, and technology. Its typical supervised and unsupervised learning makes ML desirable for us to use, since it is based on the availability of our data and the research problems. Regarding the prediction data, there are some me...

In this study, we used the fluctuating air temperature dataset. The change is caused by data fluctuations, trend, seasonality, cyclicity and irregularities. The generalized additive model (GAM) data approach is used to describe these phenomena. The aim of this research is to find out the factors that affect the air temperature in the Indian Ocean,...

In this study, the intelligent computational strength of neural networks (NNs) based on the backpropagated Levenberg-Marquardt (BLM) algorithm is utilized to investigate the numerical solution of nonlinear multiorder fractional differential equations (FDEs). The reference data set for the design of the BLM-NN algorithm for different examples of FDE...

In recent studies, several chaos-based secure communication (CBSC) systems are developed and are assumed to be effective and promising tools for balancing communications in wireless applications. The reliability of a wireless communication system is dependent on the synchronization between receiving and transmitting nodes. Therefore, it is crucial...

This study investigates the combination of finite difference method (FDM) and the stabilized Lanczos method to solve various partial differential equation (PDE) problems. This combination is wrapped in the algorithms called hybrid FDMRMEIEMLA and hybrid FDM-RLMinRes. FDM is the discretization method which converts the PDEs into algebraic formula, w...

The average rainfall in Aceh Barat every year is different pattern and it is influenced by several factors. In this paper we used rainfall dataset, which is changing time to time. The change is caused by an element of fluctuate and volatility in the data. The purpose of this study was to find the best ARIMA mixed models as combination with ARCH and...

In the subject of engineering, chaotic convection serves a critical function, for instance, magneto-mechanical devices, lasers, and mechanical and designing electrical circuits, as well as understanding fluid dynamics and oscillatory chemical reactions. Nonlinear chaotic systems, for instance, turbulence and fluid convection, exist up to modest ext...

In this paper, one dimensional mathematical model of convective-conductive-radiative fins is presented with thermal conductivity depending on temperature. The temperature field with insulated tip is determined for a fin in convective, conductive and radiative environments. Moreover, an intelligent soft computing paradigm named as the LeNN-WOA-NM al...

In the present article, mathematical analysis of drilling system with reverse air circulation is presented by a novel hybrid technique of feed forward artificial neural network (ANN) and biogeography based cuckoo search (BHCS) algorithm. A series solution is constructed with unknown weights for the differential equations representing the drilling p...

In this study, a novel application of neurocomputing technique is presented for solving nonlinear heat transfer and natural convection porous fin problems arising in almost all areas of engineering and technology, especially in mechanical engineering. The mathematical models of the problems are exploited by the intelligent strength of Euler polynom...

Evolutionary computing is an exciting sub-field of soft computing. Many evolutionary algorithm based on the Darwinian principles of natural selection are developed under the umbrella of EC in the last two decades. EAs provide a set of optimal solutions in single simulation unlike traditional optimization techniques for dealing with large-scale glob...

Rainfall is very essential for life and it has complexity process. To obtain the relationship between rainfall in time-spatial of Aceh region and the Indian Ocean Dipole (IOD) phenomenon, we used spectral-analysis and SARIMA model. Identification results show that the rainfall data monthly in Aceh Barat (ABR), Aceh Besar (ABS), Sabang (S) and Aceh...

ASEAN, include Indonesia, Malaysia, Philippines, Singapore, and Thailand, are the countries with ongoing transmission of SARS-COV-2, the virus that causes COVID-19. The confirmed cases in Indonesia and Philippines are the highest ranks among other ASEAN countries such as Malaysia, Thailand, and Singapore. To reduce the spread of the pandemic COVID-...

Support vector regression (SVR) is well known as a regression or prediction tool under the Machine Learning (ML) which preserves all the key features through the training data. Different from general prediction, here, we proposed SVR to predict the new approximate solutions after we generated some iterates using an iterative method called Lanczos a...

Bound-constrained optimization has wide applications in science and engineering. In the last two decades, various evolutionary algorithms (EAs) were developed under the umbrella of evolutionary computation for solving various bound-constrained benchmark functions and various real-world problems. In general, the developed evolutionary algorithms (EA...

In the last two decades, the field of global optimization has become very active, and, in this regard, many deterministic and stochastic algorithms were developed for solving various optimization problems. Among them, swarm intelligence (SI) is a stochastic algorithm that is more flexible and robust and has had the ability to find an optimum soluti...

Conventionally, partial differential equations (PDE) problems are solved numerically through discretization process by using finite difference approximations. The algebraic systems generated by this process are then finalized by using an iterative method. Recently, scientists invented a short cut approach, without discretization process, to solve t...

Lanczos-type algorithms are iterative methods for solving symmetric and unsymmetric systems of linear equations (SLEs) which particularly involve large numbers of variables and equations. One big issue with these algorithms is known as breakdown; it causes the algorithms to fail before obtaining (converging to) a good solution. This obviously reduc...

Data observations often contain anomalous cases, also known as outliers. These may strongly influence the results and form a fundamental problem in statistical data analysis. Generally speaking, an outlier can lead to model misspecification, incorrect analysis results and can make all estimation procedures meaningless. Thus, in this paper, we suppl...

We suggest a new approach to combatting the instability of Lanczos-type algorithms for large scale Systems of Linear Equations (SLE's). It is a modification of the so-called embedded interpolation and extrapolation model in Lanczos-type algorithms (EIEMLA), which enables us to interpolate the sequence of vector solutions generated by a Lanczos-type...

Modified embedding interpolation and extrapolation model in Lanczos-types algorithms (MEIEMLA) is well-known as a strategy to avoid breakdown in Lanczos-type algorithms by taking advantage of the patterns which persistently exist in the iterates generated by a Lanczos-type algorithm. It is the improved EIEMLA by interpolating all vector solutions S...

Breakdown in Lanczos method, or other non-stationary iterative methods, is kind of a latent disease which sustains every time we solve the systems of linear equations (SLEs). A number of approaches to deal with the issue has been investigated. However, the problem is not fully addressed, so far. Here, we propose switching strategy to combat the bre...

A new method to treat the inherent instability of Lanczos-type algorithms is introduced. It enables us to capture the properties of the sequence of iterates generated by a Lanczos-type algorithm by interpolating on this sequence of points. The interpolation model found is then used to generate a point that is outside the range. It is expected that...

Lanczos-type algorithms are well known as effective iterative methods for solving non-symmetric of systems of linear equation (SLE). However, they are fragile when involving a large number of iterations, which is well-known as a breakdown phenomenon. This study introduces modelling Lanczos algorithms through interpolation and extrapolation tools, t...

Breakdown in Lanczos-type algorithms is a common phenomenon which is due to the non-existence of some orthogonal polynomials. It causes the solution process to halt. It is, therefore, important to deal with it to improve the resilience of the algorithms and increase their usability. In this paper, we consider restarting from a number of different a...

Abstrak Sistem antrian merupakan faktor yang penting dalam dunia bisnis karena merupakan salah satu ukuran efisisen atau tidaknya kinerja layanan bisnis. Dalam penelitian ini, kami menganalisa dua jenis sistem antrian : antrian jalur tunggal (single-channel) dan antrian jalur banyak (multiple-channel) yang banyak digunakan di bank. Kami menggunakan...