Search Results - (( data optimization means algorithm ) OR ( based constructive method algorithm ))
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An evolutionary based features construction methods for data summarization approach
Published 2015“…In other words, this research will discuss the application of genetic algorithm to optimize the feature construction process from the Coral Reefs data to generate input data for the data summarization method called Dynamic Aggregation of Relational Attributes (DARA). …”
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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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Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach
Published 2022“…After that, it has been suggested to improve the efficiencies in the Deep Neural Network (DNN) model by combining the DNN with an unsupervised machine learning algorithm, the K-Means clustering algorithm. This study constructs the flow of DNN based method with the K-Means algorithm. …”
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A generalized laser simulator algorithm for optimal path planning in constraints environment
Published 2022“…The mean path cost generated by the LS algorithm, on the other hand, is 14% higher than that generated by the PRM. …”
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An Empirical Study on the Construction of A Non-Convex Risk Parity Portfolio using a Genetic Algorithm
Published 2025“…Risk-based portfolio optimization has become increasingly crucial due to the limitations and underperformance of traditional Mean-Variance (MV) portfolios. …”
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Enhanced Intelligent Water Drops Algorithm for University Examination Timetabling Problems
Published 2024“…(iii) It is a constructive-based meta-heuristic algorithm which means, the solution is incrementally constructed (step by step) until the complete solution is obtained (Noferesti and Shah-Hosseini, 2012). …”
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A robust firefly algorithm with backpropagation neural networks for solving hydrogeneration prediction
Published 2018“…The objective of this study, first, a firefly algorithm (FA) based on the k-fold cross-validation of BPNN has been suggested to predict data for keeping rapid learning and prevents the exponential increase in operating parts. …”
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3D prediction of tunneling-induced ground movements based on a hybrid ANN and empirical methods
Published 2019“…In this paper, a hybrid particle swarm optimization (PSO) algorithm-based ANN is developed to predict the maximum surface settlement and inflection points in transverse and longitudinal directions. …”
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3D prediction of tunneling-induced ground movements based on a hybrid ANN and empirical methods
Published 2020“…In this paper, a hybrid particle swarm optimization (PSO) algorithm-based ANN is developed to predict the maximum surface settlement and inflection points in transverse and longitudinal directions. …”
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Mean of correlation method for optimization of affective states detection in children
Published 2018“…This paper proposes an effective algorithm of texture analysis based on novel technique using Gray Level Co-occurrence Matrix approach to be applied so as to identify blood-flow region. …”
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Development of a hybrid PSO-ANN model for estimating glucose and xylose yields for microwave-assisted pretreatment and the enzymatic hydrolysis of lignocellulosic biomass
Published 2018“…ANN is a powerful tool capable of determining the relationship between the desired input and output data while PSO was used as a robust population-based search algorithm to optimize the performance of the ANN model. …”
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An optimized ensemble for predicting reservoir rock properties in petroleum industry
Published 2013“…In the present thesis, we proposed a new method named optimized ensembleto improve the prediction of these reservoirs parameters from well log data with the aid of available core data. …”
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Energy balancing mechanisms for decentralized routing protocols in wireless sensor networks
Published 2012“…Finally, we propose Self-Decision Route Selection scheme which is an improvement of the Hop-based Spanning Tree (HST) algorithm that is used in some routing protocols such as AODV and DSR. …”
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Design and modelling of an autonomous robotic airship with soft computing control
Published 2012“…The result shows a feasible means of UAV control. Along with the prototype airship, a path planner was also proposed for the UAV for the purpose of obstacle avoidance and path optimization using genetic algorithm to minimize on the distance travelled and to generate the shortest path to cover the specified waypoints. …”
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Time series modeling of water level at Sulaiman Station, Klang River, Malaysia
Published 2010“…The estimation of parameters of the model is accomplished using the hybrid learning algorithm consisting of standard neural network backpropagation algorithm and least squares method. …”
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Linear programming approach for scheduling sports league problems in Malaysia
Published 2017“…Sports league problems in Malaysia are usually made by manual method or so called ad-hoc method. This means that the construction of a particular schedule is based on the availability of the chosen venues (stadiums) and number of teams involved. …”
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Optimized clustering with modified K-means algorithm
Published 2021“…Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
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