Search Results - (( pattern machine algorithm ) OR ((( pattern bees algorithm ) OR ( pattern _ algorithm ))))
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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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Conference or Workshop Item -
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Optimization of economic lot scheduling problem with backordering and shelf-life considerations using calibrated metaheuristic algorithms
Published 2015“…Efficient search procedures are presented to obtain the optimum solutions by employing four well-known metaheuristic algorithms, namely genetic algorithm (GA), particle swarm optimization (PSO), simulated annealing (SA), and artificial bee colony (ABC). …”
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Optimization Of Pid Controller For Double-Link Flexible Robotic Manipulator Using Metaheuristic Algorithms
Published 2019“…This paper investigates the optimization approach of PID controller for double-link flexible robotic manipulator using metaheuristic algorithm. This research focus on population-based metaheuristic that is particle swarm optimization (PSO) and artificial bees algorithm (ABC) to tune the PID control parameters of the system. …”
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Proceeding -
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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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An algorithm for Elliott Waves pattern detection
Published 2018“…Under several different algorithm settings, several EW pattern sets are obtained. …”
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An algorithm for Elliott Waves pattern detection
Published 2018“…Under several different algorithm settings, several EW pattern sets are obtained. …”
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Financial time series predicting using machine learning algorithms
Published 2013“…Thereafter, Artificial Neural Network (ANN) and Support Vector Machine (SVM) algorithms are implemented separately to train with the trend patterns for predicting the movement direction of financial trends. …”
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Thesis -
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Market prices trend forecasting supported by Elliott Wave's theory
Published 2017“…The combination of ML algorithms and EW pattern detector achieved significantly higher performance compare to the ML algorithms only.…”
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A comparative study of clonal selection algorithm for effluent removal forecasting in septic sludge treatment plant
Published 2023“…Algorithms; Artificial intelligence; Biochemical oxygen demand; Bioinformatics; Developing countries; Effluent treatment; Effluents; Forecasting; Least squares approximations; Oxygen; Pattern recognition; Support vector machines; Water quality; Biological oxygen demand; Clonal selection algorithms; Least-square support vector machines; Sludge treatment plants; Total suspended solids; Chemical oxygen demand; oxygen; sewage; algorithm; clone; comparative study; effluent; least squares method; nonlinearity; pattern recognition; simulation; sludge; water treatment; activated sludge; algorithm; Article; biochemical oxygen demand; chemical oxygen demand; clonal selection algorithm; comparative study; computer simulation; effluent; forecasting; pattern recognition; prediction; regression analysis; septic sludge treatment plant; sludge treatment; statistical model; support vector machine; suspended particulate matter; waste water treatment plant; chemistry; procedures; sewage; theoretical model; Algorithms; Biological Oxygen Demand Analysis; Forecasting; Least-Squares Analysis; Models, Theoretical; Sewage; Support Vector Machines; Waste Disposal, Fluid…”
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Machine learning predictions of stock market pattern using Econophysics approach
Published 2025“…Hence, this research will be using Monte Carlo Simulation and identify which machine learning algorithm is suitable for predicting stock market patterns. …”
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Book Section -
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Advanced flood prediction at forest with rainfall data using various machine learning algorithms
Published 2024“…Prediction in flood patterns, K-Nearest Neighbour consisting rainfall pattern expressively used to produce improved accuracy than the Logistic Regression.…”
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Conference or Workshop Item -
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Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation
Published 2023Subjects: “…Knuth-Morris-Pratt (KMP) pattern matching algorithm…”
Conference paper -
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Frequent Lexicographic Algorithm for Mining Association Rules
Published 2005“…An algorithm called Flex (Frequent lexicographic patterns) has been proposed in obtaining a good performance of searching li-equent patterns. …”
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Thesis -
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Hybrid ACO and SVM algorithm for pattern classification
Published 2013“…A new direction for ACO is to optimize continuous and mixed (discrete and continuous) variables. Support Vector Machine (SVM) is a pattern classification approach originated from statistical approaches. …”
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Thesis -
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Design of a pattern classification system using extreme learning machine
Published 2024text::Final Year Project -
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IncSPADE: An Incremental Sequential Pattern Mining Algorithm Based on SPADE Property
Published 2016“…In this paper we propose Incremental Sequential PAttern Discovery using Equivalence classes (IncSPADE) algorithm to mine the dynamic database without the requirement of re-scanning the database again. …”
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Book Chapter -
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Clustering natural language morphemes from EEG signals using the Artificial Bee Colony algorithm
Published 2015“…This study aims at analyzing EEG signals for the purpose of clustering natural language morphemes using the Artificial Bee Colony (ABC) algorithm. Using as input the features extracted from EEG signals during morphological priming tasks, our experimental results indicate that applying the ABC algorithm on EEG datasets to cluster Malay morphemes produces promising results.…”
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Proceeding Paper
