Search Results - ((((mining algorithm) OR (_ algorithm))) OR (((means algorithm) OR (bat algorithm))))
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Hybrid bat algorithm-artificial neural network for modeling operating photovoltaic module temperature: article / Noor Rasyidah Hussin
Published 2014“…In other words, the implemented bat algorithm in neural network structure is to get global optimization in order to minimize mean absolute percentage error, MAPE. …”
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Hybrid bat algorithm hybrid-artificial neural network for modeling operating photovoltaic module temperature / Noor Rasyidah Hussin
Published 2014“…In other words, the implemented bat algorithm in neural network structure is to get global optimization in order to minimize mean absolute percentage error, MAPE. …”
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Thesis -
3
A Hybrid Least Squares Support Vector Machine with Bat and Cuckoo Search Algorithms for Time Series Forecasting
Published 2020“…Hence, to enhance the search ability of Cuckoo Search, it is integrated with Bat algorithm that offers a balanced search between global and local. …”
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The performance of Taguchi�s T-method with binary bat algorithm based on great value priority binarization for prediction
Published 2023“…This paper proposes an optimization algorithm based on the Binary Bat algorithm methodology for replacing the conventional orthogonal array approach. …”
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Non-invasive gliomas grading using swarm intelligence algorithm / Muhammad Harith Ramli
Published 2017“…Bat algorithm is chosen for the development of the prototype for segmentation and classification purpose. …”
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A modified π rough k-means algorithm for web page recommendation system
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FEATURES EXTRACTION OF FINGERPRINTS BASED ON HYBRID PARTICLE SWARM OPTIMIZATION AND BAT ALGORITHMS
Published 2023“…Both PSO and BA algorithms are swarmbased algorithms that mimics the swarm behaviour of particles and bats in nature. …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In order to address the challenges that mentioned above in this study, in the first phase, a novel architecture based on ensemble feature selection techniques include Modified Binary Bat Algorithm (NBBA), Binary Quantum Particle Swarm Optimization (QBPSO) Algorithm and Binary Quantum Gravita tional Search Algorithm (QBGSA) is hybridized with the Multi-layer Perceptron (MLP) classifier in order to select relevant feature subsets and improve classification accuracy. …”
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A web-based implementation of k-means algorithms
Published 2022“…The K-means algorithm has been around for over a century. …”
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An efficient fuzzy C-least median clustering algorithm
Published 2021“…In this paper we are discussing our new procedure for clustering called Fuzzy C-least median of squares algorithm which is an improvement to Fuzzy C-means (FCM) algorithm. …”
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MINING CUSTOMER DATA FOR DECISION MAKING USING NEW HYBRID CLASSIFICATION ALGORITHM
Published 2011“…In this paper we proposed an algorithm for mining patterns of huge stock data to predict factors affecting the sale of products. …”
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Citation Index Journal -
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MINING CUSTOMER DATA FOR DECISION MAKING USING NEW HYBRID CLASSIFICATION ALGORITHM
Published 2011“…In this paper we proposed an algorithm for mining patterns of huge stock data to predict factors affecting the sale of products. …”
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Frequent Lexicographic Algorithm for Mining Association Rules
Published 2005“…Four datasets from UCI machine learning repositories and domain theories except the pumsb dataset were experimented. The Flex algorithm and the other two existing algorithms Apriori and DIC under the same specification are tested toward these datasets and their extraction times for mining frequent patterns were recorded and compared. …”
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14
Analysis of K-Mean and X-Mean Clustering Algorithms Using Ontology-Based Dataset Filtering
Published 2021“…In this paper, we have compared the performance of K-Mean and XMean clustering algorithms using two datasets of student enrollment in higher education institutions. …”
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A Text Mining Algorithm Optimising the Determination of Relevant Studies
Published 2023Conference Paper -
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Comparison of expectation maximization and K-means clustering algorithms with ensemble classifier model
Published 2018“…EM and K-means clustering algorithms are used to cluster the multi-class classification attribute according to its relevance criteria and afterward, the clustered attributes are classified using an ensemble random forest classifier model. …”
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An Efficient Data Structure for General Tree-Like Framework in Mining Sequential Patterns Using MEMISP
Published 2007“…It has been shown that MEMISP algorithm has outperformed all other algorithms in terms of efficiency and scalability. …”
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Sequential pattern mining using PrefixSpan with pseudoprojection and separator database
Published 2008“…Sequential pattern mining is a new branch of data mining science that solves inter-transaction pattern mining problems. …”
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Development of a Novel Hybrid Optimization Algorithm for Minimizing Irrigation Deficiencies
Published 2019“…In the current study, the optimal utilization of the Aydoghmoush Dam Reservoir is examined based on a hybrid of the bat algorithm (BA) and particle swarm optimization algorithm (PSOA) by increasing the convergence rate of the new hybrid algorithm (HA) without being trapped in the local optima. …”
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Clustering of rainfall data using k-means algorithm
Published 2019“…Clustering algorithms in data mining is the method for extracting useful information for a given data. …”
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