Search Results - (( using detection method algorithm ) OR ( knowledge solution mining algorithm ))
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Dynamic and adaptive execution models for data stream mining applications in mobile edge cloud computing systems / Muhammad Habib Ur Rehman
Published 2016“…The critical factors of complexity at application level include data size and data rate of continuously streaming data, the selection of data fusion and data preprocessing methods, the choice of learning models, learning rates and learning modes, and the adoption of data mining algorithms. …”
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Data Classification and Its Application in Credit Card Approval
Published 2004“…Many intensive researches have been conducted to enhance the capability of data mining solution in providing the intelligence so that different types of businesses can make informed decisions. …”
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Final Year Project -
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Medical diagnosis using data mining techniques / Shaiful Nizam Zamri
Published 2003“…Secondly, this report will review the literature part which started with basic knowledge of data mining and knowing what the basic information about data mining. …”
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Machine-learning approach using thermal and synthetic aperture radar data for classification of oil palm trees with basal stem rot disease
Published 2021“…In an imbalanced dataset, one of the two classes contains fewer total samples than the other class. The sampling-based method, also known as the data level method, is used to deal with this problem. …”
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An artificial immune system model as talent performance predictor / Siti ‘Aisyah Sa’dan, Hamidah Jantan and Mohd Hanapi Abdul Latif
Published 2016“…Immune based algorithm is part of bio-inspired algorithms elicits theories which can act as an inspiration for computer-based solutions. …”
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Research Reports -
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Synergizing intelligence and knowledge discovery: Hybrid black hole algorithm for optimizing discrete Hopfield neural network with negative based systematic satisfiability
Published 2024“…Additionally, a Hybrid Black Hole Algorithm was proposed in the retrieval phase to optimize the final neuron states. …”
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Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy
Published 2019“…By using the proposed algorithm, the sparse coefficients are learned by exploiting the relationships among different multi-view features and leveraging the knowledge from multiple related tasks. …”
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Towards a better feature subset selection approach
Published 2010“…The selection of the optimal features subset and the classification has become an important issue in the data mining field.We propose a feature selection scheme based on slicing technique which was originally proposed for programming languages.The proposed approach called Case Slicing Technique (CST).Slicing means that we are interested in automatically obtaining that portion 'features' of the case responsible for specific parts of the solution of the case at hand.We show that our goal should be to eliminate the number of features by removing irrelevant once.Choosing a subset of the features may increase accuracy and reduce complexity of the acquired knowledge.Our experimental results indicate that the performance of CST as a method of feature subset selection is better than the performance of the other approaches which are RELIEF with Base Learning Algorithm (C4.5), RELIEF with K-Nearest Neighbour (K-NN), RELIEF with Induction of Decision Tree Algorithm (ID3) and RELIEF with Naïve Bayes (NB), which are mostly used in the feature selection task.…”
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Conference or Workshop Item -
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Edge Detection Algorithm For Image Processing Of Search And Rescue Robot
Published 2016“…This paper highlights the various edge detection algorithms working method and comparison is made based on the advantages and disadvantages of the algorithms for the identification of an optimum edge detection algorithm. …”
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Final Year Project -
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Multi road marking detection system for autonomous car using hybrid- based method
Published 2018“…One of the embedded systems that received great attention is road detection system, that operates using road markings detection algorithm. …”
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Algorithm enhancement for host-based intrusion detection system using discriminant analysis
Published 2004“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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Improving intrusion detection using genetic algorithm
Published 2013“…The validity of this approach is verified using Knowledge Discovery and Data Mining Cup 1999 (KDD Cup ’99) dataset. …”
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Amplitude independent muscle activity detection algorithm of soft robotic glove system for hemiparesis stroke patients using single sEMG channel
Published 2020“…The algorithm employs the First Lag Autocorrelation and the Modified Sample Entropy methods to detect and classify weak hand closing and opening muscle activities by using signal obtained from the Flexor Carpi Ulnaris forearm muscle. …”
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Outlier detection in circular regression model using minimum spanning tree method
Published 2019“…Therefore, this study aims to develop new algorithms that can detect outliers by using the minimum spanning tree method. …”
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Obfuscated Malware Detection: Impacts on Detection Methods
Published 2024“…This paper focuses on the impacts of obfuscated malware detection techniques using a variety of detection methods. …”
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Multi-Phase Information Theory-Based Algorithm for Edge Detection of Aerial Images
Published 2022“…Such findings make the proposed algorithm desirable to be used as a key image detection method with other image-related applications.…”
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Detection of head position using chain code algorithm
Published 2007“…Features from the image are train using the Chain Code Algorithm (CCA) to do recognition of the crux human head then do detecting process. …”
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Detection of head position using chain code algorithm
Published 2007“…Features from the image are train using the Chain Code Algorithm (CCA) to do recognition of the crux human head then do detecting process. …”
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