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IR-Eclat: A new algorithm of incremental R-Eclat for infrequent itemset mining

AIP Conference Proceedings 2023年第1期2484卷

作者： Mustafa Man Nurul Aqilah Ruslan Julaily Aida Jusoh Wan Aezwani Wan Abu Bakar 1Faculty of Ocean Engineering Technology & Informatics Universiti Malaysia Terengganu Terengganu Malaysia 2Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Terengganu Malaysia

The key challenge of association rule mining is to discover and extract a valuable information from databases. However, mining association rule may require repetitious scanning of large databases that leads to the high memory usage and affects the running time. Rare Equivalence Class Transformation (R-Eclat) algorithm is specifically design for infrequent itemset mining. In response to the promising results of mining in speedy processing time and taking consideration of dynamic transaction of data in a database, a new incremental approach is introduced called Incremental R-Eclat (IR-Eclat). This model adopted via relational database engine management system; My Structured Query Language (MySQL) serves as a database engine for testing benchmark datasets. The experimental results on several benchmark datasets indicate that Incremental R-Eclat outperforms the R-Eclat by reducing its running time to process especially in dynamic database as the data is increasing in volume from time to time.

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Fi-Eclat: An enhancement of incremental Eclat algorithm

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AIP Conference Proceedings 2023年第1期2484卷

作者： Mahadi Man Masita Abdul Jalil Wan Aezwani Wan Abu Bakar 1Faculty of Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Terengganu Malaysia 2Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Terengganu Malaysia

Nowadays, there is a large amount of data growth at all organizational scales. To find useful information, the right data mining technique needs to be used. One of the popular techniques is called the equivalence class transformation (Eclat) algorithm which is gaining the benefits of the vertical data format used in the association rule mining technique. However, like horizontal data representation, vertical data still suffering from huge memory consumption. The technique then has been extended by using the Incremental Eclat (i-Eclat) algorithm which is embedded with the incremental approach. Inspired by the dynamic data transactions in a database, a new algorithm has been adopted to optimize the performance of the current algorithm called the Fast Incremental (Fi-Eclat) algorithm. The research proposes an optimization of the performance of the i-Eclat algorithm. It relies on the incremental approach implemented on the database that consists of five (5) benchmark datasets from Frequent Itemset Mining (FIMI). The outcome of the experiment indicates an improvement of 32% in time execution for the proposed algorithm.

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Algorithmic trading system based on technical indicators in artificial intelligence: A review

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AIP Conference Proceedings 2023年第1期2484卷

作者： Zarith Sofia Zulkifli Miswan Surip Hairuddin Mohammad Nurnadiah Zamri Mustafa Mamat Nor Shahirul Umirah Idris 1Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Besut Campus Terengganu Malaysia 2Department of Information Technology Universiti Tun Hussein Onn Muar Johor Malaysia 3Department of Civil Engineering Universiti Tun Hussein Onn Muar Johor Malaysia 4Faculty of Earth Science Universiti Malaysia Kelantan Jeli Campus Malaysia

Due to the advanced and hasty development of technology nowadays, researches in relation to Artificial Intelligence (AI) such as Machine Learning (ML), Genetic Algorithm (GA), Neural Network (NN) and Expert System (ES) are progressively introduced. These AI types are also frequently presented in building a new and profitable Algorithmic Trading System (ATS). Apart from Fundamental Analysis (FA), Technical Analysis (TA) based on Technical Indicators (TIs) is one of the most AI used in the development of ATS. However, there is a lack of research despite the available knowledge on TIs in ATS where AI is implemented. Therefore, this study aims to review the ATS current work comprehensively using TIs in AI. A systematic literature review (SLR) has been performed to achieve the objective of this study. This article analyses the rough and systematic literature search process for 17 selected papers from 2010 to 2020. The analysis depicts that in most published studies, GA with multiple TIs is applied. The result of this study leads to a pertinent suggestion that is aimed for further researches on ATS to be conducted by future researchers and traders.

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Solving nonlinear Burgers’ equation with semi-approximate approach using modified Gauss-Seidel iteration

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AIP Conference Proceedings 2021年第1期2423卷

作者： Nur Farah Azira Zainal Jumat Sulaiman Azali Saudi Nur Afza Mat Ali 1Faculty of Science and Natural Resources Universiti Malaysia Sabah 88400 Kota Kinabalu Sabah Malaysia 2Faculty of Computing and Informatics Universiti Malaysia Sabah 88400 Kota Kinabalu Sabah Malaysia

The main purpose of this article is to investigate the formulation and implementation of Modified Gauss-Seidel (MGS) iteration using semi-approximate approach to solve the one-dimensional (1D) nonlinear Burgers’ equation. To do that, this problem needs to be discretized by using the second-order implicit finite difference scheme and the semi-approximate approach in order to get the second-order semi-approximate implicit approximation equation which leads to a sparse and huge scale linear system. Then, this linear system has been solved via the proposed MGS iteration. Four examples are presented to analyze the performance of MGS iteration. Then numerical experiments have been carried out on four examples of problems to verify the performance of MGS iteration.

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New modification of the Hestenes-Stiefel with strong Wolfe line search

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AIP Conference Proceedings 2021年第1期2355卷

作者： Nur Athira Japri Srimazzura Basri Mustafa Mamat 1Faculty of Applied Sciences & Technology Universiti Tun Hussein Onn Malaysia 86400 Johor Darul Takzim Malaysia. 2Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Campus of Tembila 22200 Terengganu Darul Iman Malaysia.

The method of the nonlinear conjugate gradient is widely used in solving large-scale unconstrained optimization since been proven in solving optimization problems without using large memory storage. In this paper, we proposed a new modification of the Hestenes-Stiefel conjugate gradient parameter that fulfils the condition of sufficient descent using a strong Wolfe-Powell line search. Besides, the conjugate gradient method with the proposed conjugate gradient also guarantees low computation of iteration and CPU time by comparing with other classical conjugate gradient parameters. Numerical results have shown that the conjugate gradient method with the proposed conjugate gradient parameter performed better than the conjugate gradient method with other classical conjugate gradient parameters.

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Background subtraction on gait videos containing illumination variates

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AIP Conference Proceedings 2018年第1期2016卷

作者： Amalina Ibrahim Wan-Noorshahida Mohd-Isa Chiung Ching Ho 1Faculty of Computing and Informatics Multimedia University 63100 Cyberjaya Malaysia

We present a fuzzy-based decision embedded in in rule-based methods that spontaneously changes pixel intensity for every frame in a given by evaluating both hue type and level of intensity prior to the feature extraction step. The term fuzzy is to answer such question as “How low or high is the frame brightness that is categorized as bright or dark type of frame?” and vice versa. In comparison to normal background subtraction and hard-based decision, the designed fuzzy mechanism intents to demonstrate an enhancement or unravel the visibility of illumination discrepancy which has been video analysis’s nemesis. Thus, we illustrate the development in post-processing phase via applying the results onto gait recognition task. The following results are measured and compared by percentage value of Correct Classification Rate (CCR) for each approach. More than one thousands of hand-held recorded videos and static surveillance videos were acquired as experiment samples.

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Optimal geospatial features for sales analytics

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AIP Conference Proceedings 2018年第1期2016卷

作者： Hui-Jia Yee Choo-Yee Ting Chiung Ching Ho 1Faculty of Computing and Informatics Multimedia University Persiaran Multimedia 63100 Cyberjaya Selangor Malaysia

Location analytics has been employed to capture insights about business, retail, disaster planning, public safety, conservation of energy, and many more. Despite the success of location analytics in various domains, obtaining a set of optimal features or criteria for analysis purposes remained a challenge. Hence, feature selection plays an important role in obtaining the optimal features as it determines the valuable and significant factors to be included in the final analytical dataset. In this light, feature selection was proposed to optimize the geospatial features to predict sales as well as recommendation for locations when establishing new outlets. In this study, sales data for a certain telecommunication company was used. This paper ends with the results of empirical experiments and recommendation of location characteristics that optimize yearly sales.

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Hybrid BFGS-ZMRI methods with global convergence properties

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AIP Conference Proceedings 2018年第1期1974卷

作者： Zubai’ah Zainal Abidin Nurul ‘Aini Siti Farhana Husin Mohd Rivaie Mustafa Mamat 1Faculty of informatics and Computing Universiti Sultan Zainal Abidin (UniSZA) Terengganu Malaysia 2Department of Computer Sciences and Mathematics Universiti Teknologi Mara (UiTM) Terengganu Malaysia

In this paper, we focus on the steepest descent and quasi-Newton method in solving unconstrained optimization problem. Therefore, we develop a new search direction for hybrid BFGS-ZMRI method with global convergence properties. Based on the numerical result, our method shows significant improvement in the number of iteration and CPU time.

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Numerical evaluation of poisson image blending problem using AOR iteration via five-point Laplacian operator

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AIP Conference Proceedings 2018年第1期1974卷

作者： Eng Jeng Hong Azali Saudi Jumat Sulaiman 1Faculty of Science and Natural Resources Universiti Malaysia Sabah 88400 Kota Kinabalu Sabah Malaysia 2Knowledge Technology Research Unit Faculty of Computing and Informatics Universiti Malaysia Sabah 88400 Kota Kinabalu Sabah Malaysia 3Faculty of Science and Natural Resources Universiti Malaysia Sabah 88400 Kota Kinabalu Sabah Malaysia

Poisson equation has been widely applied in mathematics and engineering fields. It is a famous equation which is extensively used in image processing problem. The purpose of this study is to examine the potency of the Accelerated Over Relaxation (AOR) iterative method for Poisson image blending problem. In order to do the comparative analysis, the implementation of Gauss-Seidel (GS), Successive Over Relaxation (SOR) and AOR iterative methods are carried out to get the numerical solution of the equation that is generated by applying the five-point Laplacian operator. Numerical results are analyzed on the basis of two key criteria, the number of iterations and computational time. Lastly, it can be shown that AOR iterative method has superiority in solving Poisson image blending problem as compared with the other two methods because the iterative method eventually required lower number of iterations and lesser computational time.

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A new modification of conjugate gradient method with global convergence properties

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AIP Conference Proceedings 2018年第1期2013卷

作者： Mahmoud Dawahdeh Mustafa Mamat Ahmad Alhawarat Mohd Rivaie 1Faculty of Informatics and Computing Universiti Sultan Zainal Abidin Kuala Terengganu Malaysia 2Department of Mathematics College of Science Isra University Amman Jordan 3Department of Computer Science and Mathematics Universiti Technologi MARA (UiTM) Terengganu Kuala Terengganu Campus Malaysia

The most well-known technique or method in unconstrained optimization is the conjugate gradient method. It is used to get the greatest solution for the unconstrained optimization problems. This method is used in many fields especially, computer science, and engineering due to its convergence speed, simplicity, and the low memory requirements. A new modified conjugate gradient method is presented in this paper. This method is proved with the strong Wolfe-Powell (SWP) line search that it possesses sufficient descent property, and is globally convergent. Numerical results for a set of 141 test problems show the outperformance of the new proposed formula comparing with other methods using the same line search. The performance of this method is more efficient and better than the others.

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