Search Results - normal distribution ((factor algorithm) OR (((function algorithm) OR (selection algorithm))))
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1
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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2
ETERS: A comprehensive energy aware trust-based efficient routing scheme for adversarial WSNs
Published 2021“…A novel and efficient cluster head selection algorithm (ECHSA) is employed to improve the performance of the cluster head (CH) selection process in clustered WSN. …”
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3
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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4
Optimal placement and sizing of distributed generation in radial distribution networks using particle swarm optimization and forward backward sweep method
Published 2012“…The proposed PSO algorithm is used to determine optimal placement and size of DG in radial distribution networks, where Forward Backward Sweep Method (FBSM) of distribution load flow analysis was used, to determine the actual power loss in the system. …”
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5
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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A Study of Ikaz and Normalized Hilbert transform for solving faulty in pipeline distribution system using transmission line modelling
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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“…Previous researchers normally select the IMF visually, based on the user’s experience, and introduced a merit index that allows the automatic selection of the IMF. …”
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9
Performance Improvement of Multiobjective Optimal Power Flow-Based Renewable Energy Sources Using Intelligent Algorithm
Published 2022“…Weibull and lognormal probability distribution functions (PDFs) are respectively adopted to describe uncertainties in wind speed and solar irradiance. …”
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Nomadic people optimizer (NPO) for large-scale optimization problems
Published 2019“…The NPO successfully solved 52 out of 60 (86.6%) normal sized test functions while 16 out of 18 (88.8%) large-scale problems were equally solved. …”
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11
Reservoir Inflow Forecasting Using Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System Techniques
Published 2007“…The models were trained with normalized and non-normalized data. The selected ANFIS model was trained with normalized data with 6 Gaussian membership functions for each of 9 inputs and 6 rules. …”
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12
Research on the construction of an efficient and lightweight online detection method for tiny surface defects through model compression and knowledge distillation
Published 2024“…The K-means++ clustering algorithm generates candidate bounding boxes, adapting to defects of different sizes and selecting finer features earlier. …”
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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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14
Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares
Published 2009“…One of the important assumptions of the linear model is that the error terms are normally distributed. Unfortunately, many researchers are not aware that the performance of the OLS can be very poor when the data set that one often makes a normal assumption, has a heavy-tailed distribution which may arise as a result of the presence of outliers. …”
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15
Development of classification model between clean water and polluted water based on capacitance properties using Levenberg Marquardt (LM) algorithm of artificial neural network / M...
Published 2020“…For both cases, the statistical analysis data show that the p-value is more than 0.05, which indicates that the data are normally distributed. These measurement inputs were then going through the process of classification in ANN to generate the optimized models by using LM algorithm. …”
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Student Project -
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Algorithm enhancement for host-based intrusion detection system using discriminant analysis
Published 2004“…The focus of this analysis is on original observations that performed a detecting outlier and power transformation to transform not normally distributed data to near normality. The correlation of each system calls are examined using coefficient correlations of each selected system call variables. …”
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17
Termite mounds morphometry in predicting groundwater potentiality using geospatial technology
Published 2020“…Thereafter, twelve (12) groundwater conditioning factors (GCFs) (geology, drainage density, lineament density, lineament intersection density, land use/land cover, topographic wetness index (TWI), normalized difference vegetation index (NDVI), slope, elevation, plan curvature, static water level and groundwater level fluctuation) were passed through a feature selection filter (Correlation-based feature selection using the best first algorithm) to select the optimum groundwater control factors (GCFs) for groundwater prediction in the study area. …”
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Investigation of evolutionary multi-objective algorithms in solving view selection problem / Seyed Hamid Talebian
Published 2013“…In addition to the normal metrics, the computational time for executing each algorithm was also measured and compared. …”
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19
Robust Kernel Density Function Estimation
Published 2010“…To do this evaluation, the mixtures of bivariate normal distribution with different percentage of contribution are simulated. …”
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A study on advanced statistical analysis for network anomaly detection
Published 2005“…The focus of this analysis is on original observations that performed a detecting outlier and power transformation to transform not normally distributed data to near normality. The correlation of each system calls are examined using coefficient correlations of each selected system call variables. …”
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