Search Results - (( pattern using algorithmic ) OR ((( patterns ant algorithm ) OR ( patterns means algorithm ))))

Ant system-based feature set partitioning algorithm for classifier ensemble construction by Abdullah, , Ku-Mahamud, Ku Ruhana

“…All of these approaches attempt to generate diversity in the ensemble.However, classifier ensemble construction still remains a problem because there is no standard guideline in constructing a set of accurate and diverse classifiers. In this study, Ant system-based feature set partitioning algorithm for classifier ensemble construction is proposed.The Ant System Algorithm is used to form an optimal feature set partition of the original training set which represents the number of classifiers.Experiments were carried out to construct several homogeneous classifier ensembles using nearest mean classifier, naive Bayes classifier, k-nearest neighbor and linear discriminant analysis as base classifier and majority voting technique as combiner. …”
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Cryptanalysis using biological inspired computing approaches by Ahmad, Badrisham, Maarof, Mohd. Aizaini

“…Some examples of BIC approaches are genetic algorithm (GA), ant colony and artificial immune system (AIS). …”
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An improved multiple classifier combination scheme for pattern classification by Abdullah,

“…In this study, an improved multiple classifier combination scheme is proposed. The ant system (AS) algorithm is used to partition feature set in developing feature subsets which represent the number of classifiers. …”
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Incremental continuous ant colony optimization for tuning support vector machine’s parameters by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…Support Vector Machines are considered to be excellent patterns classification techniques. The process of classifying a pattern with high classification accuracy counts mainly on tuning Support Vector Machine parameters which are the generalization error parameter and the kernel function parameter.Tuning these parameters is a complex process and Ant Colony Optimization can be used to overcome the difficulty. …”
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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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Formulating new enhanced pattern classification algorithms based on ACO-SVM by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

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Big data clustering using grid computing and ant-based algorithm by Ku-Mahamud, Ku Ruhana

“…This paper presents a framework for big data clustering which utilizes grid technology and ant-based algorithm.…”
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Predicting stroke using ant colony optimization algorithm / Azfaruddin Azri and Rizauddin Saian by Azri, Azfaruddin, Saian, Rizauddin

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Ant colony algorithm for text classification in multicore-multithread environment / Ahmad Nazmi Fadzal by Fadzal, Ahmad Nazmi

“…Pheromone concept is the main criterion that distinguish ACO to other algorithms. Based on the concept, pheromone saturation is used to combine stackable solution pattern that is discovered while straying to different term node to build a path. …”
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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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MINING CUSTOMER DATA FOR DECISION MAKING USING NEW HYBRID CLASSIFICATION ALGORITHM by Aurangzeb, khan, Baharum, Baharudin, Khairullah, khan

“…The experimental result shows that the proposed hybrid k-mean plus MFP algorithm can generate more useful pattern from large stock data.…”
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Frequent patterns minning of stock data using hybrid clustering association algorithm by B., Baharudin, A., Khan, K., Khan

“…The experimental result shows that the proposed hybrid k-mean plus MFP algorithm can generate more useful pattern from large stock data. …”
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Traditional marble game using ant colony optimization / Muhammad Izzat Imran Che Isa by Che Isa, Muhammad Izzat Imran

“…The study of traditional marble game will be implemented in a game prototype using Ant Colony Optimization (ACO). ACO technique is used for searching method in order to find the nearest marble that can be selected to be shot. …”
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MINING CUSTOMER DATA FOR DECISION MAKING USING NEW HYBRID CLASSIFICATION ALGORITHM by Aurangzeb, khan, Baharum, Baharudin, Khairullah, Khan

“…The experimental result shows that the proposed hybrid k-mean plus MFP algorithm can generate more useful pattern from large stock data.…”
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Pattern discovery using k-means algorithm by Ahmed, Almahdi Mohammed, Wan Ishak, Wan Hussain, Md Norwawi, Norita, Alkilany, Ahmed

“…This paper will discuss the results of a pattern extraction process using a clustering algorithm that is k-means. …”
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Hybrid ant colony system algorithm for static and dynamic job scheduling in grid computing by Alobaedy, Mustafa Muwafak Theab

“…The proposed algorithms were evaluated against twelve metaheuristic algorithms in static (expected time to compute model) and dynamic (distribution pattern) grid computing environments. …”
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An improved ACS algorithm for data clustering by Mohammed Jabbar, Ayad, Ku-Mahamud, Ku Ruhana, Sagban, Rafid

“…To improve the ACOC, this study proposes a modified ACOC, called M-ACOC, which has a modification rate parameter that controls the convergence of the algorithm. Comparison of the performance of several common clustering algorithms using real-world datasets shows that the accuracy results of the proposed algorithm surpasses other algorithms.…”
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Frequent Lexicographic Algorithm for Mining Association Rules by Mustapha, Norwati

“…The primary concept of association rule algorithms consist of two phase procedure. In the first phase, all frequent patterns are found and the second phase uses these frequent patterns in order to generate all strong rules. …”
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Pattern Discovery Using K-Means Algorithm by Ahmed, AM, Norwawi, NM, Ishak, WHW, Alkilany, A

“…This paper will discuss the results of a pattern extraction process using a clustering algorithm that is k-means. …”

Sequential pattern mining using PrefixSpan with pseudoprojection and separator database by Saputra, D., Rambli, D.R.A., Foong, Oi Mean

“…Future research includes exploring the use of Separator Database in PrefixSpan with pseudoprojection to improve mining constrained sequential patterns. …”
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