Search Results - (((( pattern bees algorithm ) OR ( pattern bat algorithm ))) OR ( pattern mining algorithm ))*
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…Even the smart people are unable to report an email as a spam when the spammer tries to defraud them. The aim of data mining is to search and find undetermined patterns in huge databases. …”
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Data normalization techniques in swarm-based forecasting models for energy commodity spot price
Published 2014“…Data mining is a fundamental technique in identifying patterns from large data sets.The extracted facts and patterns contribute in various domains such as marketing, forecasting, and medical.Prior to that, data are consolidated so that the resulting mining process may be more efficient.This study investigates the effect of different data normalization techniques.which are Min-max, Z-score and decimal scaling, on Swarm-based forecasting models.Recent swarm intelligence algorithms employed includes the Grey Wolf Optimizer (GWO) and Artificial Bee Colony (ABC).Forecasting models are later developed to predict the daily spot price of crude oil and gasoline.Results showed that GWO works better with Z-score normalization technique while ABC produces better accuracy with the Min-Max.Nevertheless, the GWO is more superior than ABC as its model generates the highest accuracy for both crude oil and gasoline price.Such a result indicates that GWO is a promising competitor in the family of swarm intelligence algorithms.…”
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Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm
Published 2018“…Seven performance indexes were examined to evaluate the performance of the proposed Muskingum model integrated with IBA, with other models that were also based on the Muskingum Model with three-parameters but utilized different optimization algorithms. The results for the Wilson flood showed that the proposed model could reduce the Sum of Squared Deviations (SSD) value by 89%, 51%, 93%, 69%, and 88%, compared to the Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithm, Pattern Search (PS) algorithm, Harmony Search (HS) algorithm, and Honey Bee Mating Optimization (HBMO), respectively. …”
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Bat Algorithm for Complex Event Pattern Detection in Sentiment Analysis
Published 2021“…Thus, this study proposed a Bat Algorithm (BA) to address the complex learning structure of DBN in detecting sentiment patterns. …”
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Modifying iEclat algorithm for infrequent patterns mining
Published 2018“…This paper proposes an enhancement algorithm based on iEclat algorithms for mining infrequent pattern.…”
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Modifying iEclat algo ithm for infrequent patterns mining
Published 2018“…This paper proposes an enhancement algorithm based on iEclat algorithms for mining infrequent pattern.…”
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Performance of IF-Postdiffset and R-Eclat Variants in Large Dataset
Published 2018“…The multiple variants in the R-Eclat algorithm generate varied performances in infrequent mining patterns. …”
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Efficient prime-based method for interactive mining of frequent patterns.
Published 2011“…Since rerunning mining algorithms from scratch is very costly and time-consuming, researchers have introduced interactive mining of frequent patterns. …”
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Prime-based method for interactive mining of frequent patterns
Published 2010“…Since rerunning the mining algorithms from scratch can be very time consuming, researchers have introduced interactive mining to find proper patterns by using the current mining model with various minsup. …”
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DFP-growth: An efficient algorithm for mining frequent patterns in dynamic database
Published 2012“…Nowadays, FP-Growth is one of the famous and benchmarked algorithms to mine the frequent patterns from FP-Tree data structure. …”
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Algorithms for frequent itemset mining: a literature review
Published 2018“…This paper reviews and presents a comparison of different algorithms for Frequent Pattern Mining (FPM) so that a more efficient FPM algorithm can be developed. …”
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Frequent Lexicographic Algorithm for Mining Association Rules
Published 2005“…The mined frequent patterns are then used in generating association rules. …”
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A numerical method for frequent pattern mining
Published 2009“…Frequent pattern mining is one of the active research themes in data mining. …”
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Neural Network Training Using Hybrid Particle-move Artificial Bee Colony Algorithm for Pattern Classification
Published 2017“…Artificial Bees Colony (ABC) optimization algorithm is one of the competitive algorithms in the SI algorithms group. …”
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Neural network training using hybrid particle-move artificial bee colony algorithm for pattern classification
Published 2017“…In this work, we aimed to highlight the performance of the Hybrid Particle-move Artificial Bee Colony (HPABC) algorithm by applying it on the ANNT application.The performance of the HPABC algorithm was investigated on four benchmark pattern-classification data sets and the results were compared with other algorithms.The results obtained illustrate that HPABC algorithm can efficiently be used for ANNT.HPABC outperformed the original ABC and PSO as well as other state-of-art and hybrid algorithms in terms of time, function evaluation number and recognition accuracy.…”
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A frequent pattern mining algorithm based on FP-growth without generating tree
Published 2010“…An interesting method to frequent pattern mining without generating candidate pattern is called frequent-pattern growth, or simply FP-growth, which adopts a divide-and-conquer strategy as follows. …”
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A frequent pattern mining algorithm based on FP-growth without generating tree
Published 2010“…An interesting method to frequent pattern mining without generating candidate pattern is called frequent-pattern growth, or simply FP-growth, which adopts a divide-and-conquer strategy as follows.First, it compresses the database representing frequent items into a frequent-pattern tree, or FP-tree, which retains the itemset association information. …”
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Application of the bees algorithm to the selection features for manufacturing data
Published 2007“…The Bees Algorithm is employed to select an optimal set of features for a particular pattern classification task. …”
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