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JMASM39: Algorithm for combining robust and bootstrap in multiple linear model regression by Wan Ahmad, Wan Muhamad Amir, Ghazali, Puspa Liza, Mohd Ibrahim, Mohamad Shafiq, Aleng, Azlida, A. Rahim, Hanafi, Abdullah, Zailani

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JMASM algorithms and code algorithm for combining robust and bootstrap in multiple linear model regression (SAS) by Wan Muhamad Amir, Mohamad Shafiq, Hanafi A. Rahim, Puspa Liza Ghazali, Azlida Aleng, Abdullah, Z.

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JMASM 46: Algorithm for comparison of robust regression methods in multiple linear regression by weighting least Square Regression by Mohd Ibrahim, Mohamad Shafiq, Wan Ahmad, Wan Muhamad Amir, Zafakali, Nur Syabiha

“…An algorithm for weighting multiple linear regression by standard deviation and variance for combining different robust method is given in SAS along with an application.…”
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Comparison between fuzzy bootstrap weighted multiple linear regression and multiple linear regression: a case study for oral cancer modelling by Mohd Ibrahim, Mohamad Shafiq, Wan Ahmad, Wan Muhamad Amir, Hasan, Ruhaya, Harun, Masitah Hayati

“…Methodology: Methodology building is based on the SAS algorithm (SAS 9.4 software) which is a robust computational statistic that consists the combination of robust regression, bootstrap, weighted data, Bayesian, and fuzzy regression method. …”
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Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions by Abbas, Iraq Tareq

“…Firstly, a new strategy based on a combined method (i.e. single-objective Gravitational Search (GSA) with Bat Algorithm (BAT) (SOGS-BAT)) algorithm is proposed in which relies on the closed interval between 0 and 1 to avoid falling into local search. …”
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Combination of linear and gradient vector flow field digital mosaic rendering for automated tile placement by Akindokun, Tolulope John

“…So an improved hybrid algorithm which combines the linear, and non-linear GVF digital mosaic rendering via image segmentation is proposed, to improve the overall tile coverage area and maintain a good similarity to the source image. …”
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JMASM41: An alternative method for multiple linear model regression modeling, a technical combining of robust, bootstrap and fuzzy approach (SAS) by Wan Ahmad, Wan Muhamad Amir, Aleng, Nor Azlida, Awang Nawi, Mohamad Arif, Mohd Ibrahim, Mohamad Shafiq

“…An algorithm for combining method is given by SAS language. …”
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Disturbance-Kalman state for linear offset free MPC by Tuan, T.T., Zabiri, H., Mutalib, M.I.A., VO, D.-V.N.

“…However, the observer gain in those methods is difficult to define. Based on the drawbacks observed in those methods, a novel algorithm is proposed to guarantee offset-free MPC under model-plant mismatches and disturbances by combining the two proposed methods which are the proposed Recursive Kalman estimated state method and the proposed Disturbance-Kalman state method. …”
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Model structure selection for a discrete-time non-linear system using a genetic algorithm by Ahmad, R., Jamaluddin, H., Hussain, M. A.

“…They offer many advantages such as global search characteristics, and this has led to the idea of using this programming method in modelling dynamic non-linear systems. In this paper, a methodology for model structure selection based on a genetic algorithm was developed and applied to non-linear discrete-time dynamic systems. …”
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Model structure selection for a discrete-time non-linear system using a genetic algorithm by Ahmad, R., Jamaluddin, H., Hussain, M. A.

“…They offer many advantages such as global search characteristics, and this has led to the idea of using this programming method in modelling dynamic non-linear systems. In this paper, a methodology for model structure selection based on a genetic algorithm was developed and applied to non-linear discrete-time dynamic systems. …”
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Model structure selection for a discrete-time non-linear system using genetic algorithm by Ahmad, Robiah, Jamaluddin , Hishamuddin, Hussain, Mohd. Azlan

“…They offer many advantages such as global search characteristics, and this has led to the idea of using this programming method in modelling dynamic non-linear systems. In this paper, a methodology for model structure selection based on a genetic algorithm was developed and applied to non-linear discrete-time dynamic systems. …”
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Modified Sumudu Transform Analytical Approximate Methods For Solving Boundary Value Problems by Al-Nemrat, Asem Mustafa Moh’ad

“…In addition, for the STVIM method, a new algorithm has been proposed to solve various kinds of linear and nonlinear second-order two-point BVPs. …”
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Modified Sumudu Transform Analytical Approximate Methods For Solving Boundary Value Problems by Al-Nemrat, Asem Mustafa Moh’ad

“…In addition, for the STVIM method, a new algorithm has been proposed to solve various kinds of linear and nonlinear second-order two-point BVPs. …”
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Committee neural networks with fuzzy genetic algorithm. by Jafari , S.A., Mashohor , Syamsiah, Varnamkhasti, M. Jalali

“…Finally, we use fuzzy genetic algorithm methods for combining the output of experts to predict a reservoir parameter in petroleum industry. …”
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Path planning algorithm for a car like robot based on MILP method by Mohd Sadri, Mohd Pawzi

“…This has been combined with collision avoidance constraints to form a mixed integer linear program, which can be solved by a commercial software package.…”
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Model structure selection for a discrete-time non-linear system using a genetic algorithm by Ahmad, R., Jamaluddin, H., Hussain, Mohd Azlan

“…They offer many advantages such as global search characteristics, and this has led to the idea of using this programming method in modelling dynamic non-linear systems. In this paper, a methodology for model structure selection based on a genetic algorithm was developed and applied to non-linear discrete-time dynamic systems. …”
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Depth linear discrimination-oriented feature selection method based on adaptive sine cosine algorithm for software defect prediction by Nasser, Abdullah, H.M. Ghanem, Waheed Ali, H.Y. Saad, Abdul-Malik, Hamed Abdul-Qawy, Antar Shaddad, A. Ghaleb, Sanaa A, Mohammed Alduais, Nayef Abdulwahab, Din, Fakhrud, Ghetas, Mohamed

“…To address these challenges, this research introduces a novel Depth Linear Discrimination-Oriented Feature Selection Method based on Adaptive Sine Cosine Algorithm, named Depth Adaptive Sine Cosine Feature Selection (DASC-FS). …”
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Linear and Rotary Infrared Scan System for Measuring Circumference by Miskon, Muhammad Fahmi, Md Sani, Zamani, Jamaluddin, Mohd Herman

“…This paper presents the design and development of new circumference measurement methods. Three methods namely the Digital Linear Scan (DLS), Analog Linear Scan (ALS) and Analog Rotary Scan (ARS) were designed and develop using the combinations of hardware of infrared sensors and stepper motors with different novel algorithms to control the motion of the system. …”
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Projecting image on non-planar surface with zero-th order geometric continuity using simple dual-linear function and manipulation of strict integer implementation in programming la... by Yusoff, Fakhrul Hazman, Azhar, Muhammad Amirul

“…Usage of a projection system to display large screen images is still relevant in the midst of LED-based display increasing popularity.This is due to that the system itself is a mature technology, reliable and cheaper than the LED counterpart.While various methods had addressed the projection problems on curve surface, projecting image on jagged like surface (zero order geometric continuity) has yet to be studied in depth.This paper proposes a method for projecting image on non-planar surface with zero-order geometric continuity property using parametric modeling.The method manipulate linear function by combining two functions into one by taking advantage of computer programs strict implementation of integer variables.The method was applied to grid-based texturing algorithm in order to create the desired zero-continuity effect on the surface.The method was compared with texturing that implement existing curve algorithm to project image on the screen.Visual evaluation results showed that the proposed method fared better compared to existing curve-based projection algorithm.…”
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Non-invasive pathological voice classifications using linear and non-linear classifiers by Hariharan, Muthusamy

“…Three feature extraction methods are proposed based on the time-domain energy variations, Mel frequency cepstral coefficients combined with singular value decomposition and wavelet packet and entropy features. …”
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