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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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LCSS-Based Algorithm for Computing Multivariate Data Set Similarity: A Case Study of Real-Time WSN Data by Khan, Rahim, Ali, Ihsan, Altowaijri, Saleh, Zakarya, Muhammad, Rahman, Atiq Ur, Ahmedy, Ismail, Khan, Anwar, Gani, Abdullah

“…The proposed algorithm performs exceptionally well on numerous multivariate data sets compared with the classical dynamic programming-based algorithms. …”
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APPROXIMATION ALGORITHM-BASED INITIAL POPULATION GENERATION FOR THE GENETIC ALGORITHM SOLUTION OF THE SET COVERING PROBLEM by MOHAMAD RAZIP, HAJAR

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Clustering chemical data set using particle swarm optimization based algorithm by Triyono, Triyono

“…In this study, Particle Swarm Optimization (PSO) based clustering algorithm is exploited to optimize the results of other clustering algorithm such as K-means. …”
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Efficient genetic partitioning-around-medoid algorithm for clustering by Garib, Sarmad Makki Mohammed

“…Precisely, the second set revealed that the proposed genetic medoid based algorithms with both DB and VRC fitness functions produced more accurate results compared with the genetic means based algorithms in terms of the Fscore. …”
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Comparative study on 4G/LTE cryptographic algorithms based on different factors by Ghanim, Alyaa, Alshaikhli, Imad Fakhri Taha

“…Apparently, there are three sets of cryptographic algorithms that work on LTE technology and each set based on core algorithm. …”
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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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A Genetic Algorithm Based Approach for Solving the Minimum Dominating Set of Queens Problem by Alharbi, Saad, Venkat, Ibrahim

“…However, literature shows that limited research has been carried out to solve theMDSQP using bioinspired algorithms. To fill this gap, this paper proposes a simple and effective solution based on genetic algorithms to solve this classical problem. …”
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A Genetic Algorithm Based Approach for Solving the Minimum Dominating Set of Queens Problem by Alharbi, Saad, Venkat, Ibrahim

“…However, literature shows that limited research has been carried out to solve theMDSQP using bioinspired algorithms. To fill this gap, this paper proposes a simple and effective solution based on genetic algorithms to solve this classical problem. …”
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An Interval-Valued Fuzzy Soft Set Based Decision Making Approach Considering Weight by Hongwu, Qin, Ma, Xiuqin

“…The algorithm to solve fuzzy decision making problems based on interval-valued fuzzy soft sets has been proposed. …”
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A novel normal parameter reduction algorithm of soft sets by Ma, Xiuqin, Norrozila, Sulaiman, Qin, Hongwu, Herawan, Tutut

“…The comparison result on a Boolean-valued dataset shows that, the proposed algorithm involves relatively less computation and is easier to implement and understand as compared with the soft set-based algorithm of normal parameter reduction.…”
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Optimized clustering with modified K-means algorithm by Alibuhtto, Mohamed Cassim

“…Empirical evidences based on simulated data sets indicated that the proposed modified k-means algorithm is able to recognise the optimum number of clusters for uncorrelated data sets. …”
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An alternative approach to normal parameter reduction algorithms for decision making using a soft set theory / Sani Danjuma by Sani , Danjuma

“…Secondly, an alternative algorithm for parameter reduction and decision making based on soft set theory was proposed. …”
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A new ant based rule extraction algorithm for web classification by Ku-Mahamud, Ku Ruhana, Saian, Rizauddin

“…Using Classifier-based attribute subset selection will reduce more attributes, but sacrifice the performance of the classifier.A hybrid ant colony optimization with simulated annealing algorithm to discover rules from data is proposed.The simulated annealing technique will minimize the problem of low quality discovered rule by an ant in a colony.The best rule for a colony will then be chosen and later the best rule among the colonies will be included in the rule set.The best rule for a colony will then be chosen and later the best rule among the colonies will be included in the rule set.The rule set is arranged in decreasing order of generation.Thirteen data sets which consist of discrete and continuous data were used to evaluate the performance of the proposed algorithm in terms of accuracy, number of rules and number of terms in the rules.Experimental results obtained from the proposed algorithm are comparable to the results of the Ant-Miner algorithm in terms of rule accuracy but are better in terms of rule simplicity.…”
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Discovering decision algorithm of distance protective relay based on rough set theory and rule quality measure by Othman, Mohamad Lutfi

“…The discovered decision algorithm and association rule from the Rough-Set based data mining had been compared with and successfully validated by those discovered using the benchmarking Decision-Tree based data mining strategy. …”
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A hybrid local search algorithm for minimum dominating set problems by Abed, S.A., Rais, H.M., Watada, J., Sabar, N.R.

“…For the second stage, we propose a gain-based deterministic local search algorithm as an exploitation procedure. …”
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A hybrid local search algorithm for minimum dominating set problems by Abed, S.A., Rais, H.M., Watada, J., Sabar, N.R.

“…For the second stage, we propose a gain-based deterministic local search algorithm as an exploitation procedure. …”
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Max degree around (MDA) algorithm: a smart and efficient approximate algorithm for Vertex cover and independent set problems by Fayaz, Muhammad, Arshad, S, Shah, A.S, Shah, Asadullah

“…Mostly the state of art approximation algorithms for the MVC problem are based on greedy approaches, or inspired from MIS approaches. …”
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Nearest neighbour group-based classification by Samsudin, Noor A., Bradley, Andrew P.

“…The results show that, while no one algorithm clearly outperforms all others on all data sets, the proposed group-based classification techniques have the potential to outperform the individual-based techniques, especially as the (group) size of the test set increases. …”
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Hybrid bat algorithm for minimum dominating set problem by Abed, S.A., Rais, H.M.

“…However, population-based algorithms are not good in exploiting the search space in comparison to single-solution based methods, therefore we included simulated annealing (SA) algorithm to balance between exploitation and exploration in order to reach a best possible solution. …”
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