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Comparative analysis of line search methods in the Steepest Descent algorithm for unconstrained optimization problems / Ahmad Zikri Shukeri, Puteri Qurratu Ain Megat Sulzamzamendi...
Published 2024“…The result from this study is choosing FMRI algorithm using exact line search to get faster convergence rate which means that the algorithm achieves a high level of accuracy in fewer iterations compared to using other algorithms and inexact line search.…”
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Automated-tuned hyper-parameter deep neural network by using arithmetic optimization algorithm for Lorenz chaotic system
Published 2023“…This study proposes an automated-tuned hyper-parameter for DNN using a metaheuristic optimization algorithm, arithmetic optimization algorithm (AOA). …”
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Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…The algorithms are evaluated using 30 benchmark functions of the CEC2014 benchmark suite, and then applied to solve PCB drill path optimization case study. …”
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4
Automated-tuned hyper-parameter deep neural network by using arithmetic optimization algorithm for Lorenz chaotic system
Published 2023“…This study proposes an automated-tuned hyper�parameter for DNN using a metaheuristic optimization algorithm, arithmetic optimization algorithm (AOA). …”
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Using genetic algorithms to optimise land use suitability
Published 2012“…Second task is to determine the fitness function for the genetic algorithms. The third objective is to optimize the land use map using economic benefits. …”
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Recommendation System Model For Decision Making in the E-Commerce Application
Published 2024thesis::doctoral thesis -
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Modeling of flood water level prediction using NNARX / Fazlina Ahmat Ruslan
Published 2015“…Further, after a careful investigation into the OLS algorithm, it was shown that the ERR technique which is an essential part of the algorithm to reach model parsimony, has led the resultant model to select an incorrect model terms albeit some improvement in model selection criteria and validation method adopted in this study. …”
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Model input and structure selection in multivariable dynamic modeling of batch distillation column pilot plant / Ilham Rustam
Published 2015“…Further, after a careful investigation into the OLS algorithm, it was shown that the ERR technique which is an essential part of the algorithm to reach model parsimony, has led the resultant model to select an incorrect model terms albeit some improvement in model selection criteria and validation method adopted in this study. …”
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9
State-of-charge estimation for lithium-ion batteries with optimized self-supervised transformer deep learning model
Published 2023“…The SSL framework trains the Transformer in two stages. In the first stage, the model is pre-trained using unlabeled data with unsupervised learning. …”
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Evaluation of machine learning classifiers in faulty die prediction to maximize cost scrapping avoidance and assembly test capacity savings in semiconductor integrated circuit (IC)...
Published 2019“…This new framework will be able to provide range of possible recall rate from minimum to maximum, to identify which classifier algorithm performs the best for given dataset. …”
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Manufacturing process planning optimisation in reconfigurable multiple parts flow lines
Published 2008“…Two modified genetic algorithms are devised and employed to provide the best approximate process planning solution. …”
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Comparative Performance Analysis of Bat Algorithm and Bacterial Foraging Optimization Algorithm using Standard Benchmark Functions
Published 2014“…In order to help engineers make a sound decision on the selection amongst the best meta-heuristic algorithms for the problem at hand, there is a need to assess the performance of each algorithm against common case studies. …”
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Security alert framework using dynamic tweet-based features for phishing detection on twitter
Published 2019“…As a conclusion, this security alert framework has achieved its objective, is the only framework that provides phishing tweet detection security alert to prompt Twitter users to the best of our knowledge.…”
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14
Estimation-based Metaheuristics: A New Branch of Computational Intelligence
Published 2016“…Heuristic Kalman Algorithm (HKA) also is inspired by the Kalman Filter framework. …”
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Finding the root of nonlinear function using five bracketing method / Nur Afiqah Mohamed Azhar
Published 2019“…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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Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions
Published 2018“…The second technique is to solve bi-objective functions by using the BOBAT algorithm. The third technique is an integration of BOGSA with BOBAT to produce a BOGSBAT algorithm. …”
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Determining the preprocessing clustering algorithm in radial basis function neural network
Published 2008“…Three types of method used in this study to find the centres include random selections, K-means clustering algorithm and also K-median clustering algorithm. …”
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Sentiment analysis on airline reviews using Naive Bayes / Nurul Sarah Aliessa Che Harun
Published 2025“…In the design and implementation phases, TF-IDF was considered in cleaning and preparing the reviews for application, while the construction of a sentiment analysis model was implemented through the use of the Multinomial Naive Bayes algorithm. …”
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Accelerating DNA sequence alignment based on smith waterman algorithm using recursive variable expansion / Muhamad Faiz Ismail
Published 2014“…Finally, we validate the proposed DP framework using the Smith-Waterman (SW) algorithm, which is a widely used, computation and data intensive application in bioinformatics. …”
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Electric vehicle battery state of charge estimation using metaheuristic-optimized CatBoost algorithms
Published 2025“…Experimental results demonstrate that the BMOCatBoost approach achieved superior performance with best-case metrics of RMSE = 6.1031, MAE = 4.1303, and R² = 0.8211, outperforming both PSOCatBoost, GA-CatBoost, and WOA-CatBoost implementations. …”
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