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Using graph algorithm and classification technique for finding an optimal bus route in time-dependent travel times
Published 2016“…However, they are suffering from the long hours in traffic jam especially in rush hour.They also cannot avoid this such jam as bus routes are fixed by Bangkok Mass Transit Authority (BMTA).This paper aims to propose a technique for finding an Optimal Bus Route in Time-Dependent Travel Times by using graph algorithm and data mining technique. The proposed technique is able to find a least spent travel time path between two nodes in a bus network with time-dependence.Graph algorithm is used to generate all possible paths to reveal the distances.Classification technique is then used to analysis traffic situation in different period of the time.By analysis traffic situation, date, time, week, month, location are used as a main factor for training process in classification technique.From the experimental studies, the proposed technique is able to show the best route from any given node to the final destination depending on the different period of the time.The proposed technique provides significant benefit for traveler to select the best bus route, which is short distance and fast, among generated routes…”
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An improved directed random walk framework for cancer classification using gene expression data
Published 2020“…In this study, six gene expression datasets are applied to study the effectiveness of the sub-algorithm, directed graph and classifier in SDW in terms of cancer prediction and cancer classification. …”
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Random sampling method of large-scale graph data classification
Published 2024“…Finally, we classified the graphs of data blocks using the SVM algorithm. In experimental evaluation, our proposed method outperformed state-of-the-art graph kernels on graph classification datasets in terms of accuracy.…”
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Aco-based feature selection algorithm for classification
Published 2022“…An enhanced graph clustering ant colony optimisation (EGCACO) algorithm is proposed to solve the three (3) MGCACO algorithm problems. …”
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5
Determining the optimal number of GAT and GCN layers for node classification in graph neural networks
Published 2023“…Some graph neural networks such as Graph Convolutional Networks (GCN) and Graph Attention Networks (GAT) have emerged as effective approaches for achieving high-performance classification in such tasks. …”
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An improved pixel-based and region-based approach for urban growth classification algorithms / Nur Laila Ab Ghani
Published 2015“…The improved algorithm is constructed by adding new parameter and classification rule to existing algorithm. …”
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Ant colony optimization based subset feature selection in speech processing: Constructing graphs with degree sequences
Published 2024journal::journal article -
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Image Classification for Age-related Macular Degeneration Screening Using Hierarchical Image Decompositions and Graph Mining
Published 2011“…The resulting decomposition is then stored in a tree structure to which a weighted frequent sub-tree mining algorithm is applied. The identified sub-graphs are then incorporated into a feature vector representation (one vector per image) to which classification techniques can be applied. …”
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Development of cardioid based graph ECG heart abnormalities classification technique
Published 2015“…In this study, the development of Cardioid based graph electrocardiogram heart abnormalities classification technique is presented. …”
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A comparative analysis of QRS and cardioid graph based ECG biometric recognition in different physiological conditions
Published 2014“…Subjects were recognized with Multilayer Perceptron classification algorithm. Results were obtained through two approaches. …”
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Feature extraction and selection algorithm based on self adaptive ant colony system for sky image classification
Published 2023“…FESSIC outperforms other algorithms for average classification accuracy for the KSVM, MLP, RF and DT classifiers. …”
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Measuring height of high-voltage transmission poles using unmanned aerial vehicle (UAV) imagery
Published 2023“…Aerial photography; Classification (of information); Cost effectiveness; Electric power transmission; Graphic methods; Object detection; Poles; Remote sensing; Stereo image processing; Vehicle transmissions; Depth Map; Disparity map; Global information systems; Graph cut; High voltage transmissions; Ortho-rectification; Remote sensing applications; Stereo matching algorithm; Unmanned aerial vehicles (UAV)…”
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A Distributed Event Detection Scheme for Wireless Sensor Networks
Published 2009“…We propose a low-computation, distributed, and lightweight event detection scheme in wireless sensor networks, which is adopted from the pattern recognition scheme known as Distributed Hierarchical Graph Neuron. The experimental results show that the proposed scheme guarantees satisfactory classification accuracy, in comparison to Support VectorMachine and Self-Organizing Map algorithms.…”
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Application of Fuzzy C-Means with YCbCr and DenseNet-201 for Automated Corn Leaf Disease Detection
Published 2021“…The results show that the proposed method performed better than the previous methods with 96.81% for segmentation as well as 95.11% for classification and it is discovered to be a good fusion of algorithms to detect plant leaf diseases.…”
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15
Cardioid graph based ECG biometric in varying physiological conditions using compressed QRS
Published 2020“…Next, a Cardioid graph is generated. In order to verify the matching process, the classification is performed by using the Multilayer Perceptron (MLP) technique. …”
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Proceeding Paper -
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Sleep apnea detection using cardioid based grap
Published 2016“…In this study, the development of Cardioid based graph electrocardiogram heart abnormalities classification technique is presented. …”
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CAGDEEP : Mobile malware analysis using force atlas 2 with strong gravity call graph and deep learning
Published 2023“…Afterwards, this study adopts Convolutional Neural Network (CNN) for malware detection and classification algorithm. We compare CAGDeep with a state-of-the-art Android malware detection approach. …”
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Improving Classification Accuracy of Scikit-learn Classifiers with Discrete Fuzzy Interval Values
Published 2020“…Thus, the objective of this study is to observe the effect of fuzzy elements inside the discretization phase on the classification accuracy of Scikit-learn classifiers. In this study, fuzzy logic has been proposed to assist the existing discretization technique through fuzzy membership graph, linguistic variables and discrete interval values. …”
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Adaptive method to improve web recommendation system for anonymous users
Published 2011“…The first is iPACT, an improved recommendation system based on PACT methodology to demonstrate the prediction accuracy of the proposed enhanced classification algorithm in this research. The prediction accuracy was evaluated against two previous recommendation systems PACT and HyperGraph. …”
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