MaxD K-Means: A clustering algorithm for auto-generation of centroids and distance of data points in clusters by Wan Maseri, Wan Mohd, Beg, Abul Hashem, Herawan, Tutut, Fazley Rabbi, Khandakar

“…The results from the new algorithm show that the number of iteration improves tremendously, and the number of iterations is reduced by confirming an improvement rate is up to 78%.…”
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Shadow Detection Using Double-Threshold Pulse Coupled Neural Networks by Sun, Wei, Ji, Jing, Jiang, Xudong

“…To solve this problem, two different dynamic thresholds that iteratively alter are designed. The upper and lower limits of detecting shadows are determined respectively by a higher threshold that decreases iteratively and a lower one that increases iteratively. …”
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Asynchronous control network optimization using fast minimum cycle time analysis by Law, Chong Fatt, Gwee, Bah Hwee, Chang, Joseph Sylvester

“…We also propose a fast algorithm for iterative minimum-cycle-time analysis. The novelty of the proposed algorithm is that it takes advantage of the fact that only small modifications are made to the control network during each optimization iteration. …”
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Successive over relaxation method in solving two-point fuzzy boundary value problems by A. A. Dahalan, M. S. Muthuvalu, Jumat Sulaiman

“…The approximation solver towards system of linear equations is described through the implementation of the Gauss-Seidel (GS) and Successive Over Relaxation (SOR) iterative methods. Then several numerical experiments were shown to illustrate the effectiveness of SOR iterative method compared with the GS method.…”
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Shape-simplifying image abstraction by Padmavathy

“…The framework demonstrates the constrained MCF technique, in an iterative and incremental manner, to simplify the image content. …”
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Secure algorithm based data aggregation for sensor networks by Chai, Jeremy Wen Zhang

“…Robust Iterative Filtering is than shown to not work because of a wrong assumption that the sum of bias will be zero. …”
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Diagonal quasi-newton's method for large-scale systems of nonlinear equations by Yusuf, Mohammed Waziri

“…This method is simple to implement and converges rapidly. Nevertheless, an iteration of this method turns out to be computational expensive,this is due to the fact that the method requires the computation and storage of the Jacobian matrix, the floating point operations is O(n)3 and as well as the solution of an n linear systems in each iteration. …”
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Simulation based optimisation on cloud by Liew, Jordan Yi An

“…Simulation-based optimisation (SBO) aims to obtain a set of optimal simulation parameters by combining the use of 2 steps into an iterative process – simulation modelling and optimisation. …”
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Beamforming for wireless communications by Qu, Lin

“…We classify the techniques into two categories: non-iterative beampattern synthesis algorithms and iterative beampattern synthesis algorithms. …”
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Response surface methodology with prediction uncertainty : a multi-objective optimisation approach by Chi, Guoyi, Hu, Shuangquan, Yang, Yanhui, Chen, Tao

“…Overall, the method iterates through initial experimental design, empirical modelling and model-based optimisation to allocate promising experiments for the next iteration. …”
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A symmetric rank-one method based on extra updating techniques for unconstrained optimization. by Modarres, Farzin, Abu Hassan, Malik, Leong, Wah June

“…In particular, we discuss how to consider a criterion for indicating at each iteration whether it is necessary to employ extra updates. …”
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A framework for design information management system for architects by Muhammad Alhassan, Aliyu

“…Architectural design is characterised by rework (iteration). Many of the available process models are not capable of representing these iterative processes. …”
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Eigen is all you need: efficient lidar-inertial continuous-time odometry with internal association by Nguyen, Thien-Minh, Xu, Xinhang, Jin, Tongxing, Yang, Yizhuo, Li, Jianping, Yuan, Shenghai, Xie, Lihua

“…Two, CT-LIO benefits more from the correct association than the number of iterations. Based on these ideas, we implement our method with a customized solver where the feature association process is performed immediately after each incremental step, and the solution can converge within a few iterations. …”
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Application and efficiency evaluation of 4-point newton explicit group to solve 2d porous medium equation by J. V. L. Chew, Jumat Sulaiman, A. Sunarto, J. Pradeepkandhasamy

“…A large and sparse nonlinear system is iteratively solved using the Newton method and the 4-point explicit group technique. …”
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A new Newtons method with diagonal Jacobian approximation for systems of nonlinear equations by Yusuf, Mohammed Waziri, Leong, Wah June, Abu Hassan, Malik, Monsi, Mansor

“…Problem statement: The major weaknesses of Newton method for nonlinear equations entail computation of Jacobian matrix and solving systems of n linear equations in each of the iterations. Approach: In some extent function derivatives are quit costly and Jacobian is computationally expensive which requires evaluation (storage) of n×n matrix in every iteration. …”
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A binary particle swarm optimization approach to optimize assembly sequence planning by Mukred, J.A.A., Ibrahim, Z., Ibrahim, I., Adam, A., Wan, K., Yusof, Z.M., Mokhtar, N.

“…Permutation encoding of sequences is used to represent particles, then those particles are strictly subjected to a precedence constraint matrix at which only the feasible sequences will be iterated in the process. An archive is used in storing the feasible sequences and a swap mechanism is used to identify the feasible sequences for iteration. …”

A new Quarter-Sweep Arithmetic Mean (QSAM) method to solve diffusion equations by Jumat Sulaiman, Mohamed Othman, Mohammad Khatim Hasan

“…The formulation of the QSAM method is developed by combining the concept of the quartersweep iteration and the Arithmetic Mean (AM) method known as one of two-step iterative methods. …”
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A new Quarter Sweep Arithmetic Mean (QSAM) method to solve diffusion equations by Jumat.Sulaiman, M. Othman, M.K. Hasan

“…The formulation of the QSAM method is developed by combining the concept of the quartersweep iteration and the Arithmetic Mean (AM) method known as one of two-step iterative methods. …”
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Solving delay differential equations using intervalwise partitioning by Runge–Kutta method by Ismail, Fudziah, Suleiman, Mohammed

“…Initially the whole system is considered as nonstiff and solved using simple iteration, in the event that stiffness is indicated, the whole system is considered as stiff and solved using Newton iteration. …”
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A new Quarter Sweep Arithmetic Mean (QSAM) method to solve diffusion equations by Sulaiman, J., Othman, Mohamed, Hasan, M.K.

“…The formulation of the QSAM method is developed by combining the concept of the quarter- sweep iteration and the Arithmetic Mean (AM) method known as one of two-step iterative methods. …”