Search Results - (( normal distribution means algorithm ) OR ( parameters evaluation from algorithm ))
Search alternatives:
- parameters evaluation »
- distribution means »
- means algorithm »
- evaluation from »
- from algorithm »
-
1
Confidence intervals (CI) for concentration parameter in von Mises distribution and analysis of missing values for circular data / Siti Fatimah binti Hassan
Published 2015“…Directional statistics is a branch of statistics which deal with the data in angle form in which the method of analysis is different from linear data. For example, the distribution analogues to the normal distribution in linear data is known as circular normal distribution. …”
Get full text
Get full text
Thesis -
2
Land use evaluation for Kuala Selangor, Malaysia using remote sensing and GIS technologies
Published 2007“…The study integrates remote sensing and GIS technologies for landuse/cover evaluation. In evaluating landuse for sustainable use of natural resources several maps were taken as parameters and obtained from digital classification of SPOT 2005 data by means of supervised modes with maximum likelihood algorithm using necessary ground truth data. …”
Get full text
Get full text
Article -
3
Improved performance in distributed estimation by convex combination of DNSAF and DNLMS algorithms
Published 2022“…Diffusion normalized least mean square (DNLMS) algorithm has low misadjustment error, but it is slow in convergence. …”
Get full text
Get full text
Get full text
Get full text
Proceedings -
4
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. …”
Get full text
Get full text
Thesis -
5
Statistical approach on grading: mixture modeling
Published 2006“…In the conditional Bayesian model, we assume the data to follow the Normal Mixture distribution where the grades are distinctively separated by the parameters: means and proportions of the Normal Mixture distribution. …”
Get full text
Get full text
Thesis -
6
Entropy in portfolio optimization / Yasaman Izadparast Shirazi
Published 2017“…More specifically, we use multi-objective models that are the mean-entropy-entropy (MEE). The purpose of this new model is to overcome the limitations as observed in a traditional model; that is, having performance close to Markowitz’s mean-variance (MV) model when data comes from a normal distribution, but exhibit better performance when data comes from a non-normal distribution. …”
Get full text
Get full text
Get full text
Thesis -
7
TRMM Satellite Algorithm Estimates to Represent the Spatial Distribution of Rainstorms
Published 2016“…These findings suggest that satellite algorithm estimations from TRMM are suitable to represent the spatial distribution of extreme rainfall.…”
Get full text
Get full text
Get full text
Article -
8
Evaluation of lightning current parameters using measured lightning induced voltage on distribution power lines
Published 2019“…In this paper, an algorithm had been proposed to evaluate the lightning current parameters using measured voltage from overhead distribution lines based on lightning location obtained from lightning location system. …”
Get full text
Get full text
Conference or Workshop Item -
9
Statistical approach on grading the student achievement via normal mixture modeling
Published 2006“…In the conditional Bayesian model, we assume the data to follow the Normal Mixture distribution where the grades are distinctively separated by the parameters: means and proportions of the Normal Mixture distribution. …”
Get full text
Get full text
Get full text
Article -
10
Fire severity and post-fire generation using : Landsat [NDVI], [NBR] and [SAVI] / Nur Izzaty Dali
Published 2018“…Pre-fire and post-fire of Landsat 7 ETM+ images were obtained to identify the fire severity using Normalized Burn Ratio algorithms. The objectives of this study are (1) to produce Normalized Difference Vegetation Index (NDVI), Normalized Burn Ratio (NBR), and Soil Adjusted Vegetation Index (SAVI) and (2) to determine the changes of forest distribution based on NDVI, NBR and SAVI changes. …”
Get full text
Get full text
Thesis -
11
A speech enhancement framework using discrete Krawtchouk-Tchebichef Transform
Published 2018“…The analytical solution is derived from the assumption that speech and noise components can be modeled based on a combination between Gamma and Laplacian distributions. …”
Get full text
Get full text
Get full text
Thesis -
12
A Comparative Study of Z-Score and Min-Max Normalization for Rainfall Classification in Pekanbaru
Published 2024“…However, Z-Score Normalization, sometimes referred to as Standardization, standardizes the data by dividing by the standard deviation and subtracting the mean, maintaining the shape of the distribution and making it resistant to outliers. …”
Get full text
Get full text
Get full text
Article -
13
Statistical approach on grading the student achievement via mixture modelling
Published 2006“…In the conditional Bayesian model, we assume the Normal Mixture distribution where the grades are distinctively separated means and proportions of the Normal Mixture distribution. …”
Get full text
Get full text
Article -
14
Autonomous anomaly detection using density-based features in streaming data / Muhammmad Yunus Iqbal Basheer
Published 2023“…These algorithms are data-driven and do not require thresholds or predefined assumptions. …”
Get full text
Get full text
Thesis -
15
Evaluation of lightning current parameters using measured lightning induced voltage on distribution power lines
Published 2023Conference Paper -
16
Streamflow prediction with large climate indices using several hybrid multilayer perceptrons and copula Bayesian model averaging
Published 2023“…Climate models; Flood control; Floods; Forecasting; Information management; Inverse problems; Mean square error; Multilayer neural networks; Multilayers; Normal distribution; Particle swarm optimization (PSO); Reservoir management; Reservoirs (water); Risk management; Rivers; Stream flow; Uncertainty analysis; Bat algorithms; Bayesian model averaging; Bayesian modelling; Copula bayesian model; Gamma test; Inclusive multiple model; Multilayers perceptrons; Multiple-modeling; Natural hazard; Optimization algorithms; Bayesian networks; flood; flood control; North Atlantic Oscillation; perception; reservoir; streamflow; uncertainty analysis; Kelantan; Malaysia; West Malaysia…”
Article -
17
A study on the parameter selection of bat algorithm in in optimizing parameters in camera auto calibration problem
Published 2022“…By studying the echolocation behavior of the microbats, the bats will try to improve the fitness with each iteration. The Bat Algorithm's performance is evaluated using a case study from a database from Le2i Universite de Bourgoune. …”
Get full text
Get full text
Get full text
Article -
18
-
19
Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study
Published 2023“…The proposed mWOA and mGWO were given a new inversed control parameter expected to enable more search areas for the search agents in the early phase of the algorithms, resulting in a faster convergence speed. …”
Get full text
Get full text
Article -
20
Inversed Control Parameter in Whale Optimization Algorithm and Grey Wolf Optimizer for Wrapper-Based Feature Selection: A Comparative Study
Published 2023“…The proposed mWOA and mGWO were given a new inversed control parameter expected to enable more search areas for the search agents in the early phase of the algorithms, resulting in a faster convergence speed. …”
Get full text
Get full text
Article