Search Results - (( a constructive method algorithm ) OR ( data normalization based algorithm ))
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1
Web-based clustering tool using fuzzy k-mean algorithm / Ahmad Zuladzlan Zulkifly
Published 2019“…Even a normal people using clustering to grouping their data. …”
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Thesis -
2
Smart energy meter with adaptive communication data transfer algorithm for electrical energy monitoring
Published 2021“…Thus, in this thesis, a new Smart Energy Meter (SEM) with adaptive data transfer algorithm is designed to accommodate the problem. …”
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3
Confidence intervals (CI) for concentration parameter in von Mises distribution and analysis of missing values for circular data / Siti Fatimah binti Hassan
Published 2015“…By ignoring the existence of missing values, leads to the biasness and lack of efficiency of a statistics. In this study, three imputation methods are considered namely expectation-maximization (EM) algorithm and data augmentation (DA) algorithm. …”
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4
PSO and Linear LS for parameter estimation of NARMAX/NARMA/NARX models for non-linear data / Siti Muniroh Abdullah
Published 2017“…PSO is a swarm-based search algorithm perform a stochastic search to explore the search space. …”
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5
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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6
Fault Detection and Identification in Quadrotor System (Quadrotor Robot)
Published 2016“…The aim of the research is to construct and design a Fault Detection and Isolation algorithm. …”
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7
Reliability assessment of power system generation adequacy with wind power using population-based intelligent search methods
Published 2017“…The reliability assessment of the adequacy of the generating system is normally calculated by using either analytical or simulation methods. …”
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8
An integrated anomaly intrusion detection scheme using statistical, hybridized classifiers and signature approach
Published 2015“…Detection methods based on statistical and data mining techniques are widely deployed as anomaly-based detection system (ADS). …”
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9
Scheduling dynamic cellular manufacturing systems in the presence of cost uncertainty using heuristic method
Published 2016“…Since the proposed models (like similar models in the literature) are likely to fall into local optimum points, a Branch and Bound based heuristic, a hybrid Simulated Annealing and Genetic algorithm, a hybrid Tabu search and Simulated Annealing, a hybrid Genetic algorithm and Simulated Annealing, a hybrid Ant Colony Optimization and Simulated Annealing and a hybrid Multi-layer Perceptron and Simulated Annealing algorithms are developed. …”
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10
Machine Learning based Predictive Modelling of Cybersecurity Threats Utilising Behavioural Data
Published 2023“…A system is developed to predict the risk of users based on their behaviour when they are online using real-life behavioural data obtained from a private university’s 207 undergraduates. …”
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Reservoir Inflow Forecasting Using Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System Techniques
Published 2007“…The ANN model has been constructed for a strong non-linear input/output data. …”
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12
Machine condition monitoring and fault diagnosis using spectral analysis techniques
Published 2001“…Both normal and fault signals are analyzed using the singular value decomposition (SVD) algorithm so as to compute the parameters of the auto regressive moving average (ARMA) models. …”
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Proceeding Paper -
13
Mean of correlation method for optimization of affective states detection in children
Published 2018“…This paper proposes an effective algorithm of texture analysis based on novel technique using Gray Level Co-occurrence Matrix approach to be applied so as to identify blood-flow region. …”
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14
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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15
Incremental learning for large-scale stream data and its application to cybersecurity
Published 2015“…In Chapter 2, we propose a new algorithm based on incremental Radial Basis Function Network (RBFN) to accelerate the learning in stream data. …”
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Classification of Cardiac Disorders Based on Electrocardiogram Data with Fuzzy Cognitive Map (FCM) Algorithm Approach
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18
The effect of dose calculation algorithms on the normal tissue complication probability values of thoracic cancer
Published 2015“…Purpose: To identify the effect of dose calculation algorithms on the Normal Tissue Complication Probability values of thoracic cancer. …”
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Monograph -
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A study on advanced statistical analysis for network anomaly detection
Published 2005“…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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Monograph -
20
Data normalization techniques in swarm-based forecasting models for energy commodity spot price
Published 2014“…Data mining is a fundamental technique in identifying patterns from large data sets.The extracted facts and patterns contribute in various domains such as marketing, forecasting, and medical.Prior to that, data are consolidated so that the resulting mining process may be more efficient.This study investigates the effect of different data normalization techniques.which are Min-max, Z-score and decimal scaling, on Swarm-based forecasting models.Recent swarm intelligence algorithms employed includes the Grey Wolf Optimizer (GWO) and Artificial Bee Colony (ABC).Forecasting models are later developed to predict the daily spot price of crude oil and gasoline.Results showed that GWO works better with Z-score normalization technique while ABC produces better accuracy with the Min-Max.Nevertheless, the GWO is more superior than ABC as its model generates the highest accuracy for both crude oil and gasoline price.Such a result indicates that GWO is a promising competitor in the family of swarm intelligence algorithms.…”
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