Search Results - normal distribution ((mining algorithm) OR (learning algorithms))

Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets by Saeed, Sana

“…For this purpose, the normal distributions are applied to each class. The parameters of this distribution are optimized by applying the proposed MOHA. …”
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Small Dataset Learning In Prediction Model Using Box-Whisker Data Transformation by Lateh, Masitah bdul

“…Subsequently, the Small Johnson Data Transformation is employed to transformed raw samples to a Normal Distribution. Next, samples are generated from Normal Distribution. …”
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Algorithm enhancement for host-based intrusion detection system using discriminant analysis by Dahlan, Dahliyusmanto

“…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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A study on advanced statistical analysis for network anomaly detection by Ngadi, Md. Asri, Idris, Mohd. Yazid, Abdullah, Abd. Hanan

“…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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An Integrated Principal Component Analysis And Weighted Apriori-T Algorithm For Imbalanced Data Root Cause Analysis by Ong, Phaik Ling

“…However, frequent pattern mining (FPM) using Apriori-like algorithms and support-confidence framework suffers from the myth of rare item problem in nature. …”
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Adaptive Neural Subtractive Clustering Fuzzy Inference System for the Detection of High Impedance Fault on Distribution Power System by Tawafan, Adnan, Sulaiman , Marizan, Ibrahim, Zulkifilie

“…HIF and other operation event data were obtained by simulation of a 13.8 kV distribution feeder using PSCAD. The results show that the proposed algorithm can distinguish successfully HIFs from other events in distribution power system…”
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A Comparative Study of Z-Score and Min-Max Normalization for Rainfall Classification in Pekanbaru by Rahmad Ramadhan, Laska, Anne Mudya, Yolanda

“…Data preprocessing plays a crucial role in enhancing the performance of machine learning algorithms for classification tasks. Among the essential preprocessing stages is data normalization, which aims to standardize data into a comparable range of values. …”
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Mitigating Unbalanced And Overlapped Problems Of Large Network Intrusion Data Using Multiplelevel Detection Techniques by Ho, Yan Bing

“…These problems have caused a low detection rate for intrusions that are the minority in data sets because learning algorithms favour the majority class (normal traffic). …”
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A new variant of black hole algorithm based on multi population and levy flight for clustering problem by Haneen Abdul Wahab, Abdul Raheem

“…The obtained results were compared with the BH and previous optimization algorithms for both test functions as well as data clustering in terms of normal and high dimensional datasets. …”
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Privacy optimization and intrusion detection in modbus/tcp network-based scada in water distribution systems by Franco, Daniel Jose Da Graca Peceguina

“…Another problematic aspect is related to the intrusion detection solutions that are based on machine learning cluster algorithms to learn systems’ specifications and extract general state-based rules for attacks identification. …”
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Detection of arcing fault in underground distribution cable using artificial neural network by Chan, Wei Kian

“…A Multi-layer Perceptron (MLP) with Backpropagation (BP) learning is used to discriminate arcing faults from normal load condition. …”
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Heart sound diagnosis using nonlinear ARX model / Noraishah Shamsuddin by Shamsuddin, Noraishah

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LSTM-based electroencephalogram classification on autism spectrum disorder by Ahmad Radzi, Syafeeza, Ali, Nur Alisa, Ja'afar, Abd Shukur, Shamsuddin, Syamimi, Kamal Nor, Norazlin

“…The accuracy of 99.6% obtained for 90:10 train:test data distribution, while the accuracy of 97.3% was achieved for 70:30 distribution. …”
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Incremental learning for large-scale stream data and its application to cybersecurity by Ali, Siti Hajar Aminah

“…To process large-scale data sequences, it is important to choose a suitable learning algorithm that is capable to learn in real time. …”
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Automatic database of robust neural network forecasting / Saadi Ahmad Kamaruddin, Nor Azura Md. Ghani and Norazan Mohamed Ramli by Ahmad Kamaruddin, Saadi, Md. Ghani, Nor Azura, Mohamed Ramli, Norazan

“…Most of the previous studies seek to improve the learning algorithm of backpropagation neural networks by adapting the M-estimators predominantly. …”
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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 by Chen, Qipeng, Xiong, Qiaoqiao, Huang, Haisong, Tang, Saihong, Liu, Zhenghong

“…It can be applied in distributed service architectures for edge computing, providing new technological references for deploying deep learning models in the industrial sector.…”
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REGION-BASED ADAPTIVE DISTRIBUTED VIDEO CODING CODEC by ABDELRAHMAN ELAMIN, ABDELRAHMAN ELAMIN

“…The resulting regions map is compressed by employing quadtree algorithm and communicated to the encoder via the feedback channel. …”
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Nomadic people optimizer (NPO) for large-scale optimization problems by Mohamd Salih, Sinan Qahtan

“…A Wilcoxon Signed-Rank Test was performed to measure the pair-wise statistical performances of the algorithms and from the results, NPO recorded a better statistical performance compared to the other benchmarking algorithms. …”
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Unsupervised chest X-ray opacity classification using minimal deep features by Che Azemin, Mohd Zulfaezal, Mohd Tamrin, Mohd Izzuddin, Md. Ali, Mohd. Adli, Jamaludin, Iqbal

“…With only ten features required to build the unsupervised model, this would pave the way for future federated learning research where actual CXRs can remain distributed over multiple centers without sacrificing the anonymity of the patients.…”
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Validation assessments on resampling method in imbalanced binary classification for linear discriminant analysis by Jamaluddin, Ahmad Hakiim, Mahat, Nor Idayu

“…The curse of class imbalance affects the performance of many conventional classification algorithms including linear discriminant analysis (LDA). …”
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