Search Results - (( model validation bat algorithm ) OR ( label classification mining algorithm ))
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Multi-label learning based on positive label correlations using predictive apriori
Published 2019“…Multi-label Learning (MLL) is a general task in data mining that consists of three main tasks: classification, label ranking, and multi-label ranking. …”
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Thesis -
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Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy
Published 2019“…In the second part of the study, a novel classification algorithm called Hessian semi-supervised ELM (HSS-ELM) is proposed to enhance the semi-supervised learning of ELM. …”
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3
Improvement anomaly intrusion detection using Fuzzy-ART based on K-means based on SNC Labeling
Published 2011“…This paper presents our work to improve the performance of anomaly intrusion detection using Fuzzy-ART based on the K-means algorithm. The K-means is a modified version of the standard K-means by initializing the value K from the value obtained after data mining using Fuzzy-ART and SNC labeling technique. …”
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Gravitational search – bat algorithm for solving single and bi-objective of non-linear functions
Published 2018“…Secondly, two meta-heuristics, namely, Bi-Objective Gravitational Search Algorithm (BOGSA) and Bi-Objective Bat Algorithm (BOBAT), were combined to form a (BOGS-BAT) algorithm. …”
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5
Taguchi?s T-method with Normalization-Based Binary Bat Algorithm
Published 2025“…Therefore, a variable selection technique using a swarm-based Binary Bat algorithm is proposed. Specifically, a normalization-based Binary Bat algorithm is used, where discretization of continuous solution into binary form is performed using a normalization equation. …”
Conference paper -
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Feature Selection with Harmony Search for Classification: A Review
Published 2021“…A good classification accuracy can be achieved when the model correctly predicted the class labels. …”
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Proceeding -
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Application of Optimization Methods for Solving Clustering and Classification Problems
Published 2011“…Cluster and classification analysis are very interesting data mining topics that can be applied in many fields. …”
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8
Fuzzy Systems and Bat Algorithm for Exergy Modeling in a Gas Turbine Generator
Published 2011“…The fuzzy models are trained applying locally linear model tree algorithm followed by a meta-heuristic nature inspired algorithm called bat algorithm. …”
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Conference or Workshop Item -
9
Evaluations of oil palm fresh fruit bunches maturity degree using multiband spectrometer
Published 2017“…Furthermore, the Lazy-IBK algorithm have been validated to produce the best classifier model, with the machine learning algorithm performance of 65.26%, recall of 65.3%, and 65.4% F-measured as compared to other evaluated machine learning classifier algorithms proposed within the WEKA data mining algorithm. …”
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A hybrid bat–swarm algorithm for optimizing dam and reservoir operation
Published 2019“…This study proposes a new hybrid optimization algorithm based on a bat algorithm (BA) and particle swarm optimization algorithm (PSOA) called the hybrid bat–swarm algorithm (HB-SA). …”
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Application of augmented bat algorithm with artificial neural network in forecasting river inflow in Malaysia
Published 2024“…Only a few simulation systems, where previous techniques failed to anticipate SF data quickly, let alone cost-effectively, and took a long time to execute. The bat algorithm (BA), a meta-heuristic approach, was used in this study to optimize the weights and biases of the artificial neural network (ANN) model. …”
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Predicting game-induced emotions using EEG, data mining and machine learning
Published 2024“…The 20 experiment cases’ results from subject-based experiments supported that the SVM classifer could accurately classify the 4 emotion states with a kappa value over 0.62, demonstrating the SVM-based algorithm’s capabilities in precisely determining the emotion label for each participant’s EEG features’ instance. …”
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New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems
Published 2024“…Thirdly, the thesis validates the algorithm's performance on standard constrained single objective and multi objective benchmark test functions. …”
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15
Classification of breast cancer disease using bagging fuzzy-id3 algorithm based on fuzzydbd
Published 2022“…Classification is a data mining technique used to classify varied data types according to a specific criterion. …”
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A coherent knowledge-driven deep learning model for idiomatic - aware sentiment analysis of unstructured text using Bert transformer
Published 2023“…Machine learning and deep neural networks have shown promise in accurately representing and classifying sentiment, but they require large amounts of labeled data to train the models. In this context, the proposed novel strategy aims to eliminate the need for human labeling of the idiomatic lexicon and fine-tuning the classifier to handle the sentiment classification of tweets containing idiomatic expressions. …”
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Final Year Project / Dissertation / Thesis -
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Cyber parental control framework for objectionable web content classification and filtering based on topic modelling using enhanced latent dirichlet allocation / Hamza H. M. Altart...
Published 2023“…Despite substantial advancements in automating web classification that combines web mining and content classification methods, the study identifies a gap in applying advanced machine learning algorithms for superior objectionable web content classification. …”
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Application of augmented bat algorithm with artificial neural network in forecasting river inflow of hydroelectric reservoir stations in Malaysia
Published 2023“…Uncertainty Analyses such as Taylor Diagram, Violin Plot, Relative Error, and Scatter Plot were applied to further validate the results. The Hybrid BA-ANN model proved to be versatile and robust when being applied to other study areas in Malaysia. …”
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Investigation on the potential to integrate different artificial intelligence models with metaheuristic algorithms for improving river suspended sediment predictions
Published 2023“…Although the adaptive neuro fuzzy system (ANFIS) and multilayer feed-forward neural network (MFNN) have been widely used to simulate hydrological variables, improving the accuracy of the above models is an important issue for hydrologists. In this article, the ANFIS and MFNN models were improved by the bat algorithm (BA) and weed algorithm (WA). …”
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