Search Results - (( model validation based algorithm ) OR ( level classification search algorithm ))
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1
Automatic detection and indication of pallet-level tagging from rfid readings using machine learning algorithms
Published 2020“…In order to further validate the position of the tagging in the pallet box of the Random Forest model developed, a different predefined location was used to validate the model. …”
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2
Efficient gear fault feature selection based on moth‑flame optimisation in discrete wavelet packet analysis domain
Published 2019“…Second, the MFO algorithm was utilised to select the optimal discriminative features. …”
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3
Enhancement Of Static Code Analysis Malware Detection Framework For Android Category-Based Application
Published 2021“…The result shows that the detection of malware within application category achieves higher accuracy compared to application with non-category based. In increasing the reliability, the results obtained are then validated by using statistical analysis procedure which each machine learning classification algorithm are iterate 50 times. …”
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4
Optimized techniques for landslide detection and characteristics using LiDAR data
Published 2018“…In this task, two neural network algorithms, Recurrent Neural Networks (RNN) and Multi-Layer Perceptron Neural Networks (MLP-NN) were used and the hyper-parameters of the network architecture was optimized based on a systematic grid search. …”
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5
Digital economy tax compliance model in Malaysia using machine learning approach
Published 2021“…Based on the validation of training data with the presence of seven single classifier algorithms, three performance improvements have been established through ensemble classification, namely wrapper, boosting, and voting methods, and two techniques involving grid search and evolution parameters. …”
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6
Improvement on rooftop classification of worldview-3 imagery using object-based image analysis
Published 2019“…The result shows the area under the ROC curve (AUC) of 0.804 with p < 0.0001 at 95% confidence level. Furthermore, a systematic feature selection approach was proposed in which search algorithms (Ant-Search, Best First-Search and Particle Swamp Optimization (PSO) - Search) performance were evaluated to select the most significant features. …”
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7
Propositional satisfiability method in rough classification modeling for data mining
Published 2002“…SIPIDRIP generated shorter rules among other methods in most dataset. The proposed search strategy indicated that the best performance can be achieved at the lower level or shorter path of the tree search. …”
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8
Fingerprint classification : a BI-resolution approach to singular point extraction
Published 2004“…The algorithm will only search for singular points in the finer level in a particular region if and only if there is a hit. …”
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9
Social spider optimisation algorithm for dimension reduction of electroencephalogram signals in human emotion recognition
Published 2018“…Whereby, the max accuracy obtained is 66.66% and 70.83%, the mean accuracy obtained is 55.51±7.17 and 60.97±8.38 for 3-level of valence emotions and 3-level of arousal emotions classification respectively.…”
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10
Classification System for Wood Recognition using K-Nearest Neighbor with Optimized Features from Binary Gravitational Algorithm
Published 2014“…The project proposes a classification system using Gray Level Co-Occurrence Matrix (GLCM) as feature extractor, K-Nearest Neighbor (K-NN) as classifier and Binary Gravitational Search Algorithm (BGSA) as the optimizer for GLCM’s feature selection and parameters. …”
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11
Intelligent non-destructive classification of josapine pineapple maturity using artificial neural network
Published 2016“…Statistical based features namely minimum, maximum, arithmetic average and standard deviation were extracted from each image channels within detected ROI to represent pineapple skin color's tendency and dispersion. Next, classification index to determine the pineapple maturity level has been applied which are linear classification using thresholding value and artificial neural network adopting pattern recognition method. …”
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Efficient classifying and indexing for large iris database based on enhanced clustering method
Published 2018“…From the experimental results, the proposed method was indeed more effective for clustering and classification and outperformed the traditional k-mean algorithm. …”
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14
Multi-level of feature extraction and classification for X-Ray medical image
Published 2018“…Therefore, effective techniques for medical image retrieval and classification are required to provide accurate search through substantial amount of images in a timely manner. …”
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Power line faults classification by neural network train by Ant Colony Optimization
Published 2017“…The characteristic of ACO algorithms is their explicit use of elements of previous solutions. …”
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Modeling of cardiovascular diseases (CVDs) and development of predictive heart risk score
Published 2021“…Secondly, the ML models offer better and consistent risk prediction models as compared to LRA-based model. …”
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17
Improved Ozone Level Detection through Feature Selection with Modified Whale Optimization Algorithm
Published 2024“…This study presents a new approach for ozone level detection through feature selection by the modified Whale Optimization Algorithm (mWOA). …”
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Cluster Analysis of Data Points using Partitioning and Probabilistic Model-based Algorithms
Published 2014“…This study explores the performance accuracies of partitioning-based algorithms and probabilistic model-based algorithm. …”
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Dynamic modelling of a flexible beam structure using feedforward neural networks for active vibration control
Published 2019“…Correlation tests were used to validate the obtained model. Based on the proposed method, a small mean squared error value has been achieved in the validation phase. …”
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Optimization of assembly line balancing with energy efficiency by using tiki-taka algorithm
Published 2023“…Lastly, a study of the industrial case was performed as a validation of the developed model and algorithm. An automotive company is selected, and the collected actual data is used for validation purposes. …”
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