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1
Bee colony optimisation of the travelling salesman problem in light rail systems
Published 2019“…The study reported in this paper aimed to identify the most efficient algorithm and develop a mathematical model based on artificial bee colony optimisation to solve this problem in light rail transit systems. …”
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2
Data mining based damage identification using imperialist competitive algorithm and artificial neural network
Published 2018“…In this study, to predict the damage severity of sin-gle-point damage scenarios of I-beam structures a data mining based damage identification framework and a hybrid algorithm combining Artificial Neural Network (ANN) and Imperial Competitive Algorithm (ICA), called ICA-ANN method, is proposed. …”
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3
LSSVM parameters tuning with enhanced artificial bee colony
Published 2014“…The proposed model was employed in predicting financial time series data and comparison is made against the standard Artificial Bee Colony (ABC) and Cross Validation (CV) technique.The simulation results assured the accuracy of parameter selection, thus proved the validity in improving the prediction accuracy with acceptable computational time.…”
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4
Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics
Published 2018“…Optimization is a crucial process to select the best parameters in single and multi-objective problems for manufacturing process.However,it is difficult to find an optimization algorithm that obtain the global optimum for every optimization problem.Artificial Bees Colony (ABC) is a well-known swarm intelligence algorithm in solving optimization problems.It has noticeably shown better performance compared to the state-of-art algorithms.This study proposes a novel hybrid ABC algorithm with β-Hill Climbing (βHC) technique (ABC-βHC) in order to enhance the exploitation and exploration process of the ABC in optimizing carbon nanotubes (CNTs) characteristics.CNTs are widely used in electronic and mechanical products due to its fascinating material with extraordinary mechanical,thermal,physical and electrical properties. …”
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5
An efficient fuzzy clustering algorithm for mining user session clusters on web log data
Published 2021“…This paper proposes an efficient Fuzzy Clustering algorithm for mining client session clusters from web access log information to find the groups of client profiles. …”
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6
Arabic Speaker Identification System for Forensic Authentication Using K-NN Algorithm
Published 2023“…Classification (of information); Data mining; Digital forensics; Forestry; Learning algorithms; Loudspeakers; Motion compensation; Nearest neighbor search; Speech recognition; Trees (mathematics); K-near neighbor; Logistic model tree; Logistics model; Mel frequency cepstral co-efficient; Mel frequency cepstral coefficient; Mel-frequency cepstral coefficients; Mining classification; Model trees; Nearest-neighbour; Speaker identification systems; Authentication…”
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A prototype for context identification of scientific papers via agent-based text mining
Published 2023Conference Paper -
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A regulative norms mining algorithm for complex adaptive system
Published 2023“…Adaptive systems; Soft computing; Complex adaptive systems; Exceptional events; Mining algorithms; Normative system; Norms identifications; Regulative norms; Social norm; Data mining…”
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Context identification of scientific papers via agent-based model for text mining (ABM-TM)
Published 2023“…In this paper, we propose an agent-based text mining algorithm to extract potential context of papers published in the WWW. …”
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Discovering association rules for mining images datasets: a proposal
Published 2005“…The algorithm has four major steps: feature extraction, object identification, auxiliary image creation and object mining. …”
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Privacy Preserving Features Selection for Data Mining using Machine Learning Algorithms
Published 2023Conference Paper -
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A Text Mining Algorithm Optimising the Determination of Relevant Studies
Published 2023Conference Paper -
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The application of neural network data mining algorithm into mixed pixel classification in geographic information system environment
Published 2007“…This , paper discusses the development of data mining and pattern recognition algorithm to handle the complexity of hyperspectral remote sensing images in Geographical Information Systems environment. …”
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14
Transfer learning in near infrared spectroscopy for stingless bee honey quality prediction across different months
Published 2024“…Thus, this study aims to evaluate the feasibility of homogenous transfer learning approaches to overcome data constraints in developing NIRS predictive models of stingless bee honey qualities across different months. …”
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Outlier Detection Technique in Data Mining: A Research Perspective
Published 2005“…Finding ,removing and detecting outliers is very important in data mining, for example error in large databases can be extremely common, so an important property of a data mining algorithm is robustness with respect to outliers in the database. …”
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Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan
Published 2020“…In the modeling phase, amongst all DM algorithms, the applicability of machine learning, artificial intelligence and statistical data mining techniques were examined using Support Vector Machine (SVM), Artificial Neural Network (ANN) and Classification and Regression Tree (CART) to detect the hidden patterns in vibration data. …”
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17
Comparison of algorithm Support Vector Machine and C4.5 for identification of pests and diseases in chili plants
Published 2019“…Information about chili pests is collected so that it becomes a database that can be used to identify disease pests using the data mining method. The use of data mining algorithms is expected to help in the identification of pests and diseases in chili plants. …”
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Data mining in mobile ECG based biometric identification
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Potential norms detection in social agent societies
Published 2023“…In this paper, we propose a norms mining algorithm that detects a domain's potential norms, which we called the Potential Norms Mining Algorithm (PNMA). …”
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Big Data Mining Using K-Means and DBSCAN Clustering Techniques
Published 2022“…Therefore, this paper aims to analyze and cluster the log file data to get useful information that helps understand the users' behavior. A variety of data mining techniques were used to address the problem; three steps of data pre-processing were applied, namely the cleaning of data, the identification of users, and the identification of sessions. …”
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