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1
DESIGN AND IMPLEMENTATION OF RIPEMD-160 HASH FUNCTION USING VERILOG HDL
Published 2022“…Besides that, iterative methods also used to improve the frequency, power and are requirements performance of RIPEMD-160 hash function. …”
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Final Year Project Report / IMRAD -
2
DESIGN AND IMPLEMENTATION OF RIPEMD-160 ALGORITHM ON RECONFIGURABLE HARDWARE
Published 2019“…The RIPEMD-160 can improve the security in storing information. This project used iterative method to investigate the security algorithm and implemented the algorithm. …”
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3
Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…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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4
Comparative study of modified BFGS and new scale modified BFGS for solving unconstrained optimization / Shahirah Atikah Mohamad Husnin
Published 2018“…These methods were tested with several selected functions by using code Maple 18 software. …”
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5
Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…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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6
Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…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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7
Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…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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8
Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…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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9
Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms
Published 2023“…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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10
Comparative study of secant, Fixed point and Sixth section methods for solving root in nonlinear equation / Nik Syahrul Naim Abdul Rahman
Published 2017“…In this research, these methods are selected because it can be understand and has simple algorithm to use. …”
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11
Modifications of parameter regula falsi method p-RF for inclusion of zero of a function with one real variable
Published 2012“…The calculation of the gradient of the function in the p-RFM1 method is approximated using the secant method. …”
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12
Breast cancer disease classification using fuzzy-ID3 algorithm based on association function
Published 2022“…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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A modified n-th section line search in conjugate gradient methods for solving unconstrained optimization / Muhammad Imza Fakhri Jinudin
Published 2018“…All algorithms are written and executed using Maple 16 software. …”
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14
Variable Neighborhood Descent and Whale Optimization Algorithm for Examination Timetabling Problems at Universiti Malaysia Sarawak
Published 2025“…A constructive algorithm was developed to generate an initial feasible solution, which was subsequently refined using two primary approaches to evaluate their efficiency: Iterative Threshold Pipe Variable Neighborhood Descent (IT-PVND), and a modified Whale Optimization Algorithm (WOA). …”
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15
A Comparison of Particle Swarm optimization and Global African Buffalo Optimization
Published 2020“…The experimental results illustrated the differences in the performances of both algorithms toward the optimum solution. At the end of the experiments, the PSO algorithm quickly convergence towards the optimum solution using a few particles and iterations rather than GABO. …”
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16
A fictitious reference iterative tuning method for buck converter-powered DC motor control system
Published 2019“…This paper presents a model-free optimization algorithm for a PID controller based on Fictitious Reference Iterative Tuning and Simulated Kalman Filter. …”
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17
Support directional shifting vector: A direction based machine learning classifier
Published 2021“…The positional error of the linear function has been modelled as a loss function which is iteratively optimized using the gradient descent algorithm. …”
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18
A Mobile Application For Stock Price Prediction
Published 2021“…These prediction algorithms were evaluated using 6 sectors of Bursa Malaysia stocks which are in total 216 stocks. …”
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Final Year Project / Dissertation / Thesis -
19
A modified technique in RFID networking planning and optimization
Published 2015“…In this research, PSO algorithm was used in the optimization process as it was considered as a very useful, efficient and well known algorithm. …”
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20
Developing an app for streamlined inventory tracking with barcode scanning and load planning optimization
Published 2025“…The system was tested for functionality, usability, and performance, demonstrating improved stock accuracy, reduced manual workload, and improved space utilization compared to traditional manual methods. …”
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Final Year Project / Dissertation / Thesis
