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Improved stochastic gradient descent algorithm with mean-gradient adaptive stepsize for solving large-scale optimization problems by Zulkifli, Munierah, Abd Rahmin, Nor Aliza, Wah, June Leong

“…The performance of the method is evaluated based on the ability to reduce function value after each iteration, ability to attain the lowest function value when applied to solve the well-known zebra-strip problem. …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Alzaeemi, Shehab Abdulhabib, Tay, Kim Gaik, Huong, Audrey, Sathasivam, Saratha, Majahar Ali, Majid Khan

“…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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Finding the root of nonlinear function using five bracketing method / Nur Afiqah Mohamed Azhar by Mohamed Azhar, Nur Afiqah

“…Therefore, numerical method in the form of bracketing method is often used to find only the approximate root of the function. …”
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The efficiency of conjugate gradient methods with global convergence / Siti Nur Hafiza Shamsudin by Shamsudin, Siti Nur Hafiza

“…The global convergence result is established using exact line searches. Numerical result shows that algorithm 2 which is one of the proposed CG methods is more efficiency when compared to other algorithms.…”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

“…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majid Khan bin Majahar Ali, Majid Khan bin Majahar Ali

“…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

“…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

“…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Alzaeemi, Shehab Abdulhabib, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

“…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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Self-adaptive conjugate method for a robust and efficient performance measure approach for reliability-based design optimization by Keshtegar, Behrooz, Baharom, Shahrizan, El-Shafie, Ahmed

“…These iterative methods can yield unstable solutions to highly nonlinear performance functions. …”
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An improvement of BFGS by applying n-th section method for solving unconstrained optimization / Nurul Atikah Mohamed Ramli by Mohamed Ramli, Nurul Atikah

“…The result is analysed based on number of iterations and CPU times. It is concluded that the n-th section method which is the sixth section method is the best method that can be used as the inexact line search in BFGS to lower the number of iterations and solve most of the problems.…”
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Hybrid path planning for indoor robot with Laplacian Behaviour-based control via four point-explicit group by Azali Saudi, Jumat Sulaiman

“…Consequently, the gradient of the potential functions would be used by the searching algorithm to generate path from starting to goal location. …”
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Solving nonlinear equation using Bisection method and its variants based on MATLAB GUI / Muhammad Athir Zamani by Zamani, Muhammad Athir

“…Based on the result obtained, it can be concluded that fzero is the best method for number of iterations while Modified Bisection Algorithm and Regula Falsi was the best method if compared based on computational time.…”
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Hybrid conjugate gradient methods using strong Wolfe line search for Whale Optimization Algorithm / Wan Nur Athirah Wan Mohd Zakirudin by Wan Mohd Zakirudin, Wan Nur Athirah

“…The nonlinear conjugate gradient (CG) method recently is the most used iterative methods for solving optimizing problems because it requires less storage and easy for implementation. …”
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Artificial Immune System Based Remainder Method for Multimodal Mathematical Function Optimization by Yap, David F. W., Koh, S. P., Tiong, S. K.

“…Artificial immune system (AIS) is one of the nature-inspired algorithm for solving optimization problems. In AIS, clonal selection algorithm (CSA) is able to improve global searching ability compare to other meta-heuristic methods. …”
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Optimising neural network training efficiency through spectral parameter-based multiple adaptive learning rates by Yeong, Lin Koay, Hong, Seng Sim, Yong, Kheng Goh, Sing, Yee Chua, Wah, June Leong

“…The proposed algorithm updates the learning rate in every iteration based on the approximated spectrum of the Hessian of the loss function. …”
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Iterative And Single-Step Solutions Of Two Dimensional Time-Domain Inverse Scattering Problem Featuring Ultra Wide Band Sensors by Binajjaj, Saeed Ali Saeed

“…The imaging algorithm was based on a non-linear optimization technique from which the single-step and iterative inversion schemes were realized. …”
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An Improved Artificial Immune System Based On Antibody Reminder Method For Mathematical Function Optimization by Yap, David F. W., Habibullah, Akbar, Koh, S. P., Tiong, S. K.

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Comparative study of secant, Fixed point and Sixth section methods for solving root in nonlinear equation / Nik Syahrul Naim Abdul Rahman by Abdul Rahman, Nik Syahrul Naim

“…In this research, these methods are selected because it can be understand and has simple algorithm to use. …”
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Breast cancer disease classification using fuzzy-ID3 algorithm based on association function by Nur Farahaina, Idris, Mohd Arfian, Ismail, Mohd Saberi, Mohamad, Shahreen, Kasim, Zalmiyah, Zakaria, Sutikno, Tole

“…The FID3-AF algorithm is a hybridisation of the fuzzy system, the iterative dichotomizer 3 (ID3) algorithm, and the association function. …”
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