Search Results - (( model validation bat algorithm ) OR ( label classification means algorithm ))
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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…The advantage of the cluster labelling algorithm compared to co-spectral plot and maximum-likelihood classifier was the algorithm provided a rapid production of high accuracy classification map.…”
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Integration Of Unsupervised Clustering Algorithm And Supervised Classifier For Pattern Recognition
Published 2017“…Whereas for supervised learning method, it requires teacher or prior data (i.e. large, prohibitive and labelled training data) during classification process which in real life, the cost of obtaining sufficient labelled training data is high. …”
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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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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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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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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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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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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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VEHICLE CLASSIFICATION USING NEURAL NETWORKS AND IMAGE PROCESSING
Published 2022“…The aim of this study is to propose a vehicle classification scheme where YOLO v5 algorithm and Faster R-CNN algorithm are being implemented separately into vehicle classification, followed by comparison of result between these two algorithms. …”
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Minimizing Classification Errors in Imbalanced Dataset Using Means of Sampling
Published 2023Conference Paper -
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Fuzzy C-Means with Improved Chebyshev Distance for Multi-Labelled Data
Published 2018“…Fuzzy C-Means (FCM) is one of the most well-known clustering algorithms, nevertheless its performance has been limited by the utilization of Euclidean as its distance metric.Even though there exist studies that applied FCM with other distance metrics such as Manhattan, Minkowski and Chebyshev, its performance can still be argued particularly on multi-label data.Various applications rely on data points that can be grouped into more than one class and this includes protein function classification and image annotation.This study proposes the employment of FCM that is implement using an improved Chebyshev distance metric.The proposed work eliminates correlation in data points and improve performance of clustering.The results show that the proposed FCM improves the performance of clustering as it produces minimum objective function value and with less iteration count. …”
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A coherent knowledge-driven deep learning model for idiomatic - aware sentiment analysis of unstructured text using Bert transformer
Published 2023“…We hypothesized that revealing the implicit meaning of an idiom and using it as a feature may improve the sentiment classification results. …”
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Final Year Project / Dissertation / Thesis -
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Anomaly-based intrusion detection through K-means clustering and naives Bayes classification
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Anomaly-based intrusion detection through K-Means clustering and Naives Bayes classification
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AUTONOMOUS POWER LINE INSPECTION USING COMPUTER VISION
Published 2022“…DenseNet-201 model is proposed as the base network to perform insulator fault detection autonomously. An algorithm with DenseNet-201 backbone consisting of two branches which are class label classification and bounding box regression is developed. …”
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A modified weighted support vector machine (WSVM) to reduce noise data in classification problem
Published 2021“…Classification refers to a predictive modeling problem where a class label is predicted for a given example of input data. …”
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