Search Results - (( data distributed normal algorithm ) OR ( data distribution function algorithm ))
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1
Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets
Published 2019“…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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2
Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah
Published 2015“…Anderson-Darling (AD) and Goodness of Fit test is used to identify the best fitted distribution model to the real data. Four traffic distribution which are normal, lognormal, Weibull and exponential distribution are fitted and derived. …”
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3
Time based internet traffic policing and shaping with Weibull traffic model / Mohd Azrul Abdullah
Published 2015“…Anderson-Darling (AD) and Goodness of Fit test is used to identify the best fitted distribution model to the real data. Four traffic distribution which are normal, lognormal, Weibull and exponential distribution are fitted and derived. …”
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4
Optimal network reconfiguration and intelligent service restoration prediction technique based on Cuckoo search spring algorithm / Mohamad Izwan Zainal
Published 2022“…In addition, objective function using the same CSSA algorithm were applied i.e., Vmin and Ploss as the objective function, and multi-objective involves Vmin and Ploss as the objective function. …”
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5
Robust Kernel Density Function Estimation
Published 2010“…Additionally, they are able to assign anomaly scores to normal and outlying observations. Finally this thesis also addresses the estimation of Mutual Information (MI) for mixture distribution which prone to create two distant groups in the data. …”
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6
A new variant of black hole algorithm based on multi population and levy flight for clustering problem
Published 2020“…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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7
Modeling The Modified Internal Rate Of Return (Mirr) For Long-Term Investment Strategy By The Assumption Of Gamma Distribution
Published 2023“…It offers greater flexibility compared to the commonly used normal distribution.…”
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8
Peak pressure analysis of foot plantar distribution based on image processing algorithm
Published 2018“…The other main goal of this work is to create an algorithm which has the ability to formulate accurately and reliably the distribution of pressure over the foot plantar. …”
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9
PSO modelling and PID controlled of automatic fish feeder system
Published 2020“…The main objective of this study is to improve the performance of fish feeding system by using PID controller through ARX modelling. In this study, raw data at distribution part with speed of 130 rpm, 160 rpm, 190 rpm, 220 rpm and 250 rpm were extracted and used to determine ARX equation parameters as transfer function by using PSO algorithm to optimize ARX model parameter. …”
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10
ETERS: A comprehensive energy aware trust-based efficient routing scheme for adversarial WSNs
Published 2021“…ETERS utilizes the Beta distribution-based trust function because recovery of trust values under attacks is faster in Beta distribution than Gaussian and Dirichlet distribution. …”
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Reservoir Inflow Forecasting Using Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System Techniques
Published 2007“…The reservoir inflow and rainfall data sets were examined for normal distribution and the best data transformation was used. …”
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12
Automatic database of robust neural network forecasting / Saadi Ahmad Kamaruddin, Nor Azura Md. Ghani and Norazan Mohamed Ramli
Published 2014“…The direct idea of making the conventional neural network learning algorithm more powerful towards outlying data is by replacing the mean square error (MSE) with a different symmetric and continuous cost function. …”
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Transient analysis for leak signature identification based on Hilbert Huang transform and integrated kurtosis algorithm for z-notch filter technique
Published 2018“…The HHT is a way to decompose a signal into intrinsic mode functions (IMF). However, this method has the difficulty in selecting the suitable IMF for the next data post-processing method, which is Hilbert Transform (HT). …”
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14
Fault identification in pipeline system using normalized hilbert huang transform and automatic selection of intrinsic mode function
Published 2018“…This paper proposed to apply Integrated Kurtosis-based Algorithm for z-filter Technique (Ikaz) for that allows automatic selection of intrinsic mode function (IMF) that’s should be used. …”
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Enhancing clustering algorithm with initial centroids in tool wear region recognition
Published 2020“…Autonomous manufacturing allows the system to distinguish between a mild, normal and total failure in tool condition. K-means clustering has become the most applied algorithm in discovering classes in an unsupervised scenario. …”
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Clustering autism spectrum disorder student’s system based on intelligence, skills and behavior using agglomerative clustering algortihm / Daarin Nadia Nordin
Published 2020“…Data cleaning and data transformation is first carried out, followed by normalization through the Z-score method before being processed in the clustering model. …”
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17
Efficiency of 4253HT smoothers in extracting signal from noise and their applications in forecasting
Published 2019“…Compound smoother is a non-linear smoothing technique that has the ability to reduce heavy noise from signal and at the same time, is resistant to sudden changes and impulse in a data series. The compound smoother of 4253HT has been studied and modified in the algorithm, specifically to estimate the middle point of running median for even span size by applying the following types of means; geometric, harmonic, quadratic and contraharmonic. …”
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18
Cognitive load assessment through EEG: a dataset from arithmetic and stroop tasks
Published 2025“…The recordings are categorized into four classes representing varying levels of induced mental stress: normal, low, mid, and high. Each task was performed for a duration of 10–20 s, and three trials were conducted for comprehen- sive data collection. …”
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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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20
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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