Search Results - (( usage detection method algorithm ) OR ( java application mining algorithm ))
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Direct approach for mining association rules from structured XML data
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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
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Mining Sequential Patterns Using I-PrefixSpan
Published 2007“…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
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A web-based implementation of k-means algorithms
Published 2022“…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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Final Year Project / Dissertation / Thesis -
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Mining Sequential Patterns using I-PrefixSpan
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Citation Index Journal -
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An efficient anomaly intrusion detection method with evolutionary kernel neural network random weights
Published 2020“…Internet security requirements are increasing due to the growth of internet usage. One of the most efficient approaches used to secure the usage of the internet from internal and external intruders is Intrusion Detection System (IDS). …”
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Methods of intrusion detection in information security incident detection: a comparative study
Published 2018“…These algorithms and methods provide fast and high rate of detection. …”
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Conference or Workshop Item -
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Reactive power imbalance method for islanding detection in micro-grid operation
Published 2014“…This paper presents and investigates the Reactive Power imbalance Method for islanding detection. The passive algorithm implements in this paper due to the low cost operation, however it got the higher non-detection zone (NDZ) and slower response time compare some active methods. …”
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Automated feature selection using boruta algorithm to detect mobile malware
Published 2020“…This research proposed automated feature selection using Boruta algorithm to detect the malware. The proposed method adopts machine learning prediction and optimizes the selecting features in order to reduce the model of machine learning complexity. …”
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Feature selection in intrusion detection, state of the art: A review
Published 2016“…These input features give information to the learning algorithms which used in intrusion detection system in the form of the detection method. …”
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A COLLABORATIVE FRAMEWORK FOR ANDROID MALWARE IDENTIFICATION USING DYNAMIC ANALYSIS
Published 2019“…The scope of this project focuses on Android Malware detection by using dynamic analysis. The methods to implement this project is through data collection, feature extraction, feature selection, and classification process. …”
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Final Year Project Report / IMRAD -
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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Thesis -
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Panoramic image matching method for uav remote sensing based on surf algorithm
Published 2024text::Final Year Project -
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P300 detection of brain signals using a combination of wavelet transform techniques
Published 2012“…This research is proving the power of combination of discrete and continuous wavelet transform for achieving high accuracy in single trial detection and visualization of P300. Meanwhile the new approaches in channels selection methods help the algorithms for convenient online usage.…”
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Thesis -
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Application of machine learning and artificial intelligence in detecting SQL injection attacks
Published 2024“…The study uses a mixed-methods approach to evaluate how well different AI and ML algorithms identify SQL injection attacks by combining algorithmic evaluation with empirical investigation. …”
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Research on the construction of an efficient and lightweight online detection method for tiny surface defects through model compression and knowledge distillation
Published 2024“…In response to the current issues of poor real-time performance, high computational costs, and excessive memory usage of object detection algorithms based on deep convolutional neural networks in embedded devices, a method for improving deep convolutional neural networks based on model compression and knowledge distillation is proposed. …”
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