Search Results - (( java implication based algorithm ) OR ( net selection process algorithm ))
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Algorithmic approaches in model selection of the air passengers flows data
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Conference or Workshop Item -
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Solving computational algorithm using CLONALNet technique based on artificial clonal selection
Published 2023“…CLONALNet enforces an algorithm that is much more robust in evaluating the fitness for each antibody cells since it initiates boundaries so that the initialization process doesn't run off as of previous CLONALG algorithm but still maintains the immune network interaction as in aiNet. …”
Conference paper -
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Mixed variable ant colony optimization technique for feature subset selection and model selection
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Immune network algorithm in monthly streamflow prediction at Johor river
Published 2014“…The model of Immune Network Algorithm used in this study is aiNet. The training process in aiNet is partly inspired by clonal selection principle and the other part uses antibody interactions for removing redundancy and finding data patterns. …”
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Proceeding Paper -
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Enhanced gravitational search algorithm for nano-process parameter optimization problem / Norlina Mohd Sabri
Published 2020“…The analysis on the processing times has also shown that eGSA has been able to reduce its processing time compared to GSA and most of other algorithms. …”
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Lexicon-based and immune system based learning methods in Twitter sentiment analysis
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Immune network algorithm in monthly streamflow prediction at Johor river
Published 2023“…The model of Immune Network Algorithm used in this study is aiNet. The training process in aiNet is partly inspired by clonal selection principle and the other part uses antibody interactions for removing redundancy and finding data patterns. …”
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Immune network algorithm in monthly streamflow prediction at Johor river
Published 2015“…The model of Immune Network Algorithm used in this study is aiNet. The training process in aiNet is partly inspired by clonal selection principle and the other part uses antibody interactions for removing redundancy and finding data patterns. …”
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Immune-based technique for undergraduate programmes recommendation / Muhammad Azrill Mohd Zamri
Published 2017“…The proposed technique is obtained by combining artificial immune network (aiNET) and clonal selection algorithm (CLONALG). Myers-Briggs Type Indicator is also used as a psychological assessment mechanism in the selection process to enhance the accuracy of the proposed technique. …”
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Academic leadership bio-inspired classification model using negative selection algorithm
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The classification of wink-based eeg signals by means of transfer learning models
Published 2021“…It was demonstrated from the simulation investigation that the CWT model could yield a better signal transformation amongst the preprocessing algorithms. In addition, amongst the eighteen TL models evaluated based on the CWT transformation, fourteen was f ound to be able to extract the features reasonable, i.e., VGG16, VGG19, ResNet101, ResNet101 V2, ResNet152, ResNet152 V2, Inception V3, Inception ResNet V2, Xception, MobileNetV2, DenseNet 121, DenseNet 169, NasNetMobile and NasNetLarge. …”
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Using SURF to Improve ResNet-50 Model for Poultry Disease Recognition Algorithm
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Effectiveness of simple terminological ontology to support document retrieval in a specialized domain / Seyed Abolfazle Moosavifar
Published 2014“…In addition, the reliability of using WordNet to provide lexical support was tested during the process of the annotation and retrieval. …”
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Development of a Neural-Fuzzy Model for Machinability Data Selection in Turning Process
Published 2008“…A neural-fuzzy model has been developed to represent machinability data selection in turning process. Turning process is a branch of machining process, which is used to produce cylindrical parts. …”
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The Contribution of Feature Selection and Morphological Operation For On-Line Business System’s Image Classification
Published 2015“…It also target to study the effect of morphological operation and feature selection to the accuracy. For the classification experiment, it was tested using four types of classifiers: BayesNet, NaiveBayesUpdateable, RandomTree and IBk.…”
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