Search Results - (( normal distribution methods algorithm ) OR ( using optimization based algorithm ))

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  1. 1

    Profit-based optimal generation scheduling of a microgrid by Muhamad Razali N.M., Hashim A.H.

    Published 2023
    “…The results demonstrate the efficiency of using genetic algorithm to solve the optimization problem. �2010 IEEE.…”
    Conference paper
  2. 2

    A new variant of black hole algorithm based on multi population and levy flight for clustering problem by Haneen Abdul Wahab, Abdul Raheem

    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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    Thesis
  3. 3

    Nomadic people optimizer (NPO) for large-scale optimization problems by Mohamd Salih, Sinan Qahtan

    Published 2019
    “…The basic component of the algorithm consists of several clans and each clan searches for the best place (or best solution) based on the position of their leader. …”
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    Thesis
  4. 4

    Adaptive Traffic Prioritization Algorithm Over Ad Hoc Network Using IEEE 802.11e by Anuar, Ammar

    Published 2016
    “…The IEEE 802.11e standard aims to provide enhancements that allow traffic with specific requirements to be treated differently from normal traffic. Enhanced Distributed Channel Access (EDCA) is a fundamental and mandatory contention-based channel access method of IEEE 802.11e which delivers traffic based on differentiated Access Category (ACs). …”
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    Thesis
  5. 5

    Determining penetration limit of central distributed generation topology in radial distribution networks by Suliman, Mohamed Saad Abdelgadir

    Published 2021
    “…The biogeography based optimization method has been proven to have better performance than artificial bee colony, genetic algorithm, particle swarm optimization, hybrid of particle swarm optimization and constriction factor approach, and hybrid of ant colony optimization and artificial bee colony methods in terms of active power loss reduction. …”
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    Thesis
  6. 6

    Heart sound diagnosis using nonlinear ARX model / Noraishah Shamsuddin by Shamsuddin, Noraishah

    Published 2011
    “…The Resilient Backpropagation (RPROP) algorithm is used to train the network. The optimized learning parameter used is 0.07 and the network has best performance when hidden neurons equal to 220. …”
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    Thesis
  7. 7

    Inter-cell and intra-cell facility layout models under different demand environments in cellular manufacturing systems by Ariafar, Shahram

    Published 2012
    “…In order to validate the models several cases are generated and demonstrated by two methods, Lingo 12.0 optimization software and an enumeration algorithm which is developed in C/C++. …”
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  8. 8

    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

    Published 2014
    “…The backpropagation algorithm is one of the most famous algorithms to train neural network based on the mean square error (MSE) of ordinary least squares (OLS). …”
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    Book Section
  9. 9

    Optimal performance of stand-alone hybrid microgrid systems based on integrated techno-economic-environmental energy management strategy using the grey wolf optimizer by Tukkee, Ahmed Sahib, Bin Abdul Wahab, Noor Izzri, Binti Mailah, Nashiren Farzilah, Hassan, Mohd Khair

    Published 2024
    “…The proposed strategy reduced the system’s total net present cost, power loss, and emissions by (1.06), (8.69), and (17.19), respectively compared to normal operation. Firefly Algorithm (FA) and Particle Swarm Optimization (PSO) techniques were used to verify the results. …”
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    Article
  10. 10

    Reservoir Inflow Forecasting Using Artificial Neural Network and Adaptive Neuro-Fuzzy Inference System Techniques by Googhari, Shahram Karimi

    Published 2007
    “…Daily reservoir inflow was computed using a water balance equation. The reservoir inflow and rainfall data sets were examined for normal distribution and the best data transformation was used. …”
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    Thesis
  11. 11

    Improved performance in distributed estimation by convex combination of DNSAF and DNLMS algorithms by Ahmad Pouradabi, Amir Rastegarnia, Azam Khalili, Ali Farzamnia

    Published 2022
    “…Diffusion normalized least mean square (DNLMS) algorithm has low misadjustment error, but it is slow in convergence. …”
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    Proceedings
  12. 12

    Algorithm enhancement for host-based intrusion detection system using discriminant analysis by Dahlan, Dahliyusmanto

    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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  13. 13

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

    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
  14. 14

    Confidence intervals (CI) for concentration parameter in von Mises distribution and analysis of missing values for circular data / Siti Fatimah binti Hassan by Hassan, Siti Fatimah

    Published 2015
    “…For example, the distribution analogues to the normal distribution in linear data is known as circular normal distribution. …”
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    Thesis
  15. 15

    Inversion of 2D and 3D DC resistivity imaging data for high contrast geophysical regions using artificial neural networks / Ahmad Neyamadpour by Neyamadpour, Ahmad

    Published 2010
    “…One common method to obtain the true resistivity distribution is by inverting the apparent resistivity values. …”
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    Thesis
  16. 16

    Statistical approach on grading: mixture modeling by Md. Desa, Zairul Nor Deana

    Published 2006
    “…Statistical approaches which use the Standard Deviation and conditional Bayesian methods are considered to assign the grades. 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. …”
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    Thesis
  17. 17
  18. 18

    Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares by Uraibi, Hassan Sami

    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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    Thesis
  19. 19

    Simulated Kalman Filter algorithms for solving optimization problems by Nor Hidayati, Abdul Aziz

    Published 2019
    “…The proposed population-based SKF algorithm and the single solution-based SKF algorithm use the scalar model of discrete Kalman filter algorithm as the search strategy to overcome these flaws. …”
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    Thesis
  20. 20

    Sizing optimization of large-scale grid connected photovoltaic system using dolphin echolocation algorithm / Muhammad Zakyizzuddin Rosselan by Rosselan, Muhammad Zakyizzuddin

    Published 2018
    “…Later, an Iterative-based Sizing Algorithm (ISA) was developed to determine the optimal sizing solution which was later used as benchmark for sizing algorithms using optimization methods. …”
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    Thesis