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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

“…The simulation is implemented with iFogSim and java programming language. …”
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Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing by Husna, Jamal Abdul Nasir

“…Global pheromone update is performed after the completion of processing the jobs in order to reduce the pheromone value of resources. A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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Ant colony optimization algorithm for load balancing in grid computing by Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

“…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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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

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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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Incremental continuous ant colony optimization for tuning support vector machine’s parameters by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…Ant Colony Optimization originally deals with discrete optimization problems. 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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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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Markov-modulated Bernoulli-based performance analysis for BLUE algorithm under bursty and correlated traffics by Saaidah A.M., Jali M.Z., Marhusin M.F., Abdel-Jaber H.

Rough set discretization: equal frequency binning, entropy/MDL and semi naives algorithms of intrusion detection system by Noor Suhana, Sulaiman, Rohani, Abu Bakar

“…Empirical results have shown that the quality of classification methods depends on the discretization algorithm in preprocessing step. Universally, discretization is a process of searching for partition of attribute domains into intervals and unifying the values over each interval. …”
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Rough set discretization: Equal frequency binning, entropy/MDL and semi naives algorithms of intrusion detection system by Noor Suhana, Sulaiman, Rohani, Abu Bakar

“…Empirical results have shown that the quality of classification methods depends on the discretization algorithm in preprocessing step. Universally, discretization is a process of searching for partition of attribute domains into intervals and unifying the values over each interval. …”
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OPTIMIZED MIN-MIN TASK SCHEDULING ALGORITHM FOR SCIENTIFIC WORKFLOWS IN A CLOUD ENVIRONMENT by Murad S.S., Badeel R., Alsandi N.S.A., Alshaaya R.F., Ahmed R.A., Muhammed A., Derahman M.

“…To achieve this, we propose a new noble mechanism called Optimized Min-Min (OMin-Min) algorithm, inspired by the Min-Min algorithm. …”

Rough Set Discretization: Equal Frequency Binning, Entropy/MDL and Semi Naives Algorithms of Intrusion Detection System by Noor Suhana, Sulaiman, Rohani, Abu Bakar

“…Empirical results have shown that the quality of classification methods depends on the discretization algorithm in preprocessing step. Universally, discretization is a process of searching for partition of attribute domains into intervals and unifying the values over each interval. …”
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Design of dictionary based on Discrete Tchebichef Transform by Qayyum A., Malik A.S., Nuafal M., Iqbal M., Abdullah T.A.R.B.T.

Markov-modulated Bernoulli-based Performance Analysis for BLUE Algorithm under Bursty and Correlated Traffics by Saaidah, AM, Jali, MZ, Marhusin, MF, Abdel-Jaber, H

“…In this study, the discrete-time performance of BLUE algorithms under bursty and correlated traffics is analyzed using two-state Markov-modulated Bernoulli arrival process (BLUE-MMBP-2). …”

Enhancement of most significant bit (MSB) algorithm using discrete cosine transform (DCT) in non-blind watermarking / Halimah Tun Abdullah by Abdullah, Halimah Tun

“…This is because many attackers attempt to retrieve the secret data from an image than audio and video. The algorithm and techniques that implemented in this project is Most Significant Bit (MSB) algorithm and Discrete Cosine Transform (OCT) as a technique for embedding process. …”
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Solving Support Vector Machine Model Selection Problem Using Continuous Ant Colony Optimization by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…Ant Colony Optimization has been used to solve Support Vector Machine model selection problem.Ant Colony Optimization originally deals with discrete optimization problem.In applying Ant Colony Optimization for optimizing Support Vector Machine parameters which are continuous variables, there is a need to discretize the continuously value into discrete value.This discretize process would result in loss of some information and hence affect the classification accuracy and seeking time.This study proposes an algorithm that can optimize Support Vector Machine parameters using Continuous Ant Colony Optimization without the need to discretize continuous value for Support Vector Machine parameters.Eight datasets from UCI were used to evaluate the credibility of the proposed hybrid algorithm in terms of classification accuracy and size of features subset.Promising results were obtained when compared to grid search technique, GA with feature chromosome-SVM, PSO-SVM, and GA-SVM.…”
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization by Mohammad Ata, Karimeh Ibrahim

“…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
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Chebyshev approximation of discrete polynomials and splines by Che Seman, Fauziahanim

“…These algorithms use either cubic splines or Lagrange polynomials to construct the approximation function. …”
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Chebyshev approximation of discrete polynomials and splines by Che Seman, Fauziahanim

“…These algorithms use either cubic splines or Lagrange polynomials to construct the approximation function. …”
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Global Algorithms for Nonlinear Discrete Optimization and Discrete-Valued Optimal Control Problems by Woon, Siew Fang

“…These problems are known as discrete-valued optimal control problems. Most practical discrete-valued optimal control problems have multiple local minima and thus require global optimization methods to generate practically useful solutions. …”
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