Search Results - (( wave optimization methods algorithm ) OR ( quality classification using algorithm ))
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Inversion Of Surface Wave Phase Velocity Using New Genetic Algorithm Technique For Geotechnical Site Investigation
Published 2011“…Therefore the use of genetic algorithm (GA) optimization technique which is one of nonlinear optimization methods is an appropriate choice to solve surface wave inversion problem having high nonlinearity and multimodality. …”
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Optimizing the efficiency of Oscillating Water Column (OWC) wave energy converter using genetic algorithm
Published 2015“…This paper, describes a method to maximize the pneumatic system efficiency using optimization technique based on Genetic algorithm. …”
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Low computational complexity for optimizing energy efficiency in mm-wave hybrid precoding system for 5G
Published 2021“…We propose effective alternating minimization algorithms based on the zero gradient method to establish fully-connected structures (FCSs) and partially-connected structures (PCSs). …”
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Low computational complexity for optimizing energy efficiency in mm-wave hybrid precoding system for 5G
Published 2021“…We propose effective alternating minimization algorithms based on the zero gradient method to establish fully-connected structures (FCSs) and partially-connected structures (PCSs). …”
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Heuristic optimization-based wave kernel descriptor for deformable 3D shape matching and retrieval
Published 2018“…This paper presents an optimized wave kernel signature (OWKS) using a modified particle swarm optimization (MPSO) algorithm. …”
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Heuristic optimization-based wave kernel descriptor for deformable 3D shape matching and retrieval
Published 2018“…This paper presents an optimized wave kernel signature (OWKS) using a modified particle swarm optimization (MPSO) algorithm. …”
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Classification model for water quality using machine learning techniques
Published 2015“…There is a need to resolve this problem for us to get good water that can be used for domestic purposes. This article proposes a suitable classification model for classifying water quality based on the machine learning algorithms. …”
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Comparison of Logistic Regression, Random Forest, SVM, KNN Algorithm for Water Quality Classification Based on Contaminant Parameters
Published 2024“…This finding emphasizes that Stacking with Gradient Boosting provides much better performance in water quality classification compared to other models. This research provides new insights into the application of machine learning algorithms for water quality management as well as guidance for optimal algorithm selection.…”
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A generalized laser simulator algorithm for optimal path planning in constraints environment
Published 2022“…The results demonstrated that the proposed method could generate an optimal collision-free path. …”
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Interferometric array planning using division algorithm for radio astronomy applications
Published 2017“…In the second scheme, a genetic algorithm is developed, in order to optimize a correlator array of antennas by using Genetic Algorithm (GA). …”
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Edge detection and contour segmentation for fruit classification in natural environment / Khairul Adilah Ahmad
Published 2018“…Experimental results show that the developed methods and model are able to classify the Harumanis quality with accuracy of 79% using fuzzy classification based on shape and size.…”
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Real-time power quality disturbance classification using convolutional neural networks
Published 2020“…Experimental results showed that the proposed algorithm produced a good result with the classification accuracy of 97.52% trained using 100 epochs. …”
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A novelty classification model for varied agarwood oil quality using the K-Nearest Neighbor algorithm / Aqib Fawwaz Mohd Amidon … [et al.]
Published 2022“…Their services are used to sniff and evaluate each agarwood to determine if it is of high quality or not. …”
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Gooseneck barnacle optimization algorithm: A novel nature inspired optimization theory and application
Published 2024“…In contrast to the previously published Barnacle Mating Optimizer (BMO) algorithm, GBO more accurately captures the unique static and dynamic mating behaviours specific to gooseneck barnacles. …”
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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…The comparison showed that, the accuracy of the unsupervised classification map with value of 88.4% that was generated by using the cluster labelling algorithm was slightly more than the maximum-likelihood supervised classification map with value of 87.5%. …”
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An adaptive ant colony optimization algorithm for rule-based classification
Published 2020“…Ant-Miner is a variant of ant colony optimisation and a prominent intelligent algorithm widely use in rules-based classification. …”
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Agarwood oil quality classification using one versus all strategies in multiclass on SVM model / Aqib Fawwaz Mohd Amidon … [et al.]
Published 2021“…So, the output was the classification of quality between low, medium low, medium high or high quality while the input was the abundances (%) of compounds. …”
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An Ultrasound-Assisted System For The Optimization Of Biodiesel Production From Chicken Fat Oil Using A Genetic Algorithm And Response Surface Methodology
Published 2015“…The time reduction for the ultrasonic method compared to the conventional method makes the ultrasonic method superior.…”
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Hybrib NSGA-II optimization for improving the three-term BP network for multiclass classification problems
Published 2015“…This paper presents a hybrid of the multiobjective evolutionary algorithm to gain a better accuracy of the fi nal solutions.The aim of using the hybrid algorithm is to improve the multiobjective evolutionary algorithm performance in terms of the enhancement of all the individuals in the population and increase the quality of the Pareto optimal solutions.The multiobjective evolutionary algorithm used in this study is a nondominated sorting genetic algorithm-II (NSGA-II) together with its hybrid, the backpropagation algorithm (BP), which is used as a local search algorithm to optimize the accuracy and complexity of the three-term backpropagation (TBP) network. …”
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