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Identification of continuous-time hammerstein system using sine cosine algorithm by E. F., Junis, J. J., Jui, Mohd Helmi, Suid, Mohd Ashraf, Ahmad

“…This paper presents the development of identification of continuous-time Hammerstein systems based on Sine Cosine Algorithm (SCA). …”
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Thermoelectric cooler identification based on continuous-time hammerstein model using metaheuristics algorithm by Jui, Julakha Jahan, Mohd Ashraf, Ahmad, Mohamed Sultan, Mohamed Ali, Mohd Anwar, Zawawi, Mohd Falfazli, Mat Jusof

“…This paper presents the identification of the Thermoelectric Cooler (TEC) plant using a novel metaheuristic called hybrid Multi-Verse Optimizer with Sine Cosine Algorithm (hMVOSCA) based continuous-time Hammerstein model. …”
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Curve fitting by rational cubic Bézier with C1 and G1 continuity using metaheuristics methods by Najihah, Mohamed, Ahmad Lutfi, Amri Ramli, Ahmad, Abd Majid, Abd Rahni, Mt Piah

“…Rational cubic Bézier curves are used to approximate the data sets while minimizing the least-squares error function using different metaheuristics algorithms. …”
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Real time power quality event detection using continuous wavelet transform by Tan R.H.G., Ramachandaramurthy V.K.

“…A test bench setup with voltage sag generator is used to test the performance of the proposed algorithm. …”

Formulating new enhanced pattern classification algorithms based on ACO-SVM by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…ACO originally deals with discrete optimization problem.In applying ACO for solving SVM model selection problem which are continuous variables, there is a need to discretize the continuously value into discrete values.This discretization process would result in loss of some information and hence affects the classification accuracy and seeking time.In this algorithm we propose to solve SVM model selection problem using IACOR without the need to discretize continuous value for SVM.The second algorithm aims to simultaneously solve SVM model selection problem and selects a small number of features.SVM model selection and selection of suitable and small number of feature subsets must occur simultaneously because error produced from the feature subset selection phase will affect the values of SVM model selection and result in low classification accuracy.In this second algorithm we propose the use of IACOMV to simultaneously solve SVM model selection problem and features subset selection.Ten benchmark datasets were used to evaluate the proposed algorithms.Results showed that the proposed algorithms can enhance the classification accuracy with small size of features subset.…”
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A Continuous Overlay Path Probing Algorithm For Overlay Networks by Feily, Maryam

“…Several experiments were carried out using the OMNeT++ simulation framework. The designed algorithm was evaluated using experimental data. …”
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Identification of continuous-time hammerstein model using improved archimedes optimization algorithm by Islam, Muhammad Shafiqul, Mohd Ashraf, Ahmad, Cho, Bo Wen

“…This proposed algorithm also discerned linear and nonlinear subsystem variables within a continuous-time Hammerstein model utilizing input and output data. …”
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Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd by Nur Farahaina, Idris

“…There are various decision tree algorithms, but the most commonly used are Iterative Dichotomiser 3 (ID3), CART, and C4.5. …”
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Identification of continuous-time model of hammerstein system using modified multi-verse optimizer by Most. Julakha, Jahan Jui

“…his thesis implements a novel nature-inspired metaheuristic optimization algorithm, namely the modified Multi-Verse Optimizer (mMVO) algorithm, to identify the continuous-time model of Hammerstein system. …”
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Modification of particle swarm optimization algorithm for optimization of discrete values by Mohd Yassin, Ahmad Ihsan, Jusoh, Muhammad Huzaimy, Abdul Rahman, Farah Yasmin

“…We propose a novel modification to the PSO algorithm to perform rapid discrete optimization. The proposed Discrete-PSO method (DPSO) uses a rescaling equation to convert the continuous-valued positions into discrete-valued variables. …”
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Continuation power flow for voltage stability assessment / Mohd Zamri Laton by Laton, Mohd Zamri

“…The continuation power flow program is developed using MATLAB programming language base on algorithm of continuation power flow (CPF) technique, which can compute efficiently the parameter at saddle node bifurcation point. …”
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Hybrid ACO and SVM algorithm for pattern classification by Alwan, Hiba Basim

“…Ant Colony Optimization (ACO) is a metaheuristic algorithm that can be used to solve a variety of combinatorial optimization problems. …”
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Optimizing support vector machine parameters using continuous ant colony optimization by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…Hence, in applying Ant Colony Optimization for optimizing Support Vector Machine parameters, which are continuous parameters, there is a need to discretize the continuous value into a discrete value.This discretization process results in loss of some information and, hence, affects the classification accuracy and seek time.This study proposes an algorithm to optimize Support Vector Machine parameters using continuous Ant Colony Optimization without the need to discretize continuous values for Support Vector Machine parameters.Seven datasets from UCI were used to evaluate the performance of the proposed hybrid algorithm.The proposed algorithm demonstrates the credibility in terms of classification accuracy when compared to grid search techniques.Experimental results of the proposed algorithm also show promising performance in terms of computational speed.…”
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On the sequences ri, si, ti ∈ ℤ related to extended Euclidean algorithm and continued fractions by Muhammad, Khairun Nisak, Kamarulhaili, Hailiza

“…The concepts of Euclidean algorithm, extended Euclidean algorithm and continued fractions are intertwined and the properties related to these concepts are proved. …”
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Optimization and discretization of dragonfly algorithm for solving continuous and discrete optimization problems by Bibi Amirah Shafaa, Emambocus

“…Furthermore, the original DA is only suitable for solving continuous optimization problems. Although there is a binary version of the algorithm, it cannot be directly used for solving discrete optimization problems like the Traveling Salesman Problem (TSP). …”
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Incremental continuous ant colony optimization for tuning support vector machine’s parameters by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…Hence, in applying Ant Colony Optimization for optimizing Support Vector Machine parameters, which are continuous in nature, the values wil have to be discretized.The discretization process will result in loss of some information and, hence, affects the classification accuracy and seeks time.This paper presents an algorithm to optimize Support Vector Machine parameters using Incremental continuous Ant Colony Optimization without the need to discretize continuous values.Eight datasets from UCI were used to evaluate the performance of the proposed algorithm.The proposed algorithm demonstrates the credibility in terms of classification accuracy when compared to grid search techniques, GA with feature chromosome-SVM, PSO-SVM, and GA-SVM.Experimental results of the proposed algorithm also show promising performance in terms of classification accuracy and size of features subset.…”
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Application of Krylov Subspace methods for solving Continuous Power Flow problem in voltage stability analysis of power system by Jasni, Jasronita

“…Furthermore, the real data with 293 buses and 595 lines is used as a practical system for verification of the new algorithms The results show that these new algorithms are able to eliminate the convergence problem faced by the existing CPF algorithm. …”
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A hybrid metaheuristic algorithm for identification of continuous-time Hammerstein systems by Jui, Julakha Jahan, Mohd Ashraf, Ahmad

“…This paper presents a new hybrid identification algorithm called the Average Multi-Verse Optimizer and Sine Cosine Algorithm for identifying the continuous-time Hammerstein system. …”
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An improve unsupervised discretization using optimization algorithms for classification problems by Mohamed, Rozlini, Samsudin, Noor Azah

“…The paper emphasizes the significance of discretization in data preprocessing, offering a comprehensive approach that combines discretization techniques with optimization algorithms. An investigative study was undertaken to assess the efficiency of EB and EW by evaluating their classification performance using Naive Bayes and K-nearest neighbor algorithms on four continuous datasets sourced from the UCI datasets. …”
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An improve unsupervised discretization using optimization algorithms for classification problems by Mohamed, Rozlini, Samsudin, Noor Azah

“…The paper emphasizes the significance of discretization in data preprocessing, offering a comprehensive approach that combines discretization techniques with optimization algorithms. An investigative study was undertaken to assess the efficiency of EB and EW by evaluating their classification performance using Naive Bayes and K-nearest neighbor algorithms on four continuous datasets sourced from the UCI datasets. …”
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