Search Results - (( java optimization method algorithm ) OR ( parameters deviations means algorithm ))

Refine Results
  1. 1

    Efficient Time-Varying q-Parameter Design for q-Incremental Least Mean Square Algorithm with Noisy Links by Arif, M., Khan, S.S., Qadri, S.S.U., Naseem, I., Moinuddin, M.

    Published 2022
    “…Moreover, for the proposed NL-qILMS, we also devised various time-varying techniques for the selection of the optimal q-parameter to improve the performance. Furthermore, the closed-form solutions for the steady-state mean square deviation, excess mean square deviation and mean square error are derived. …”
    Get full text
    Get full text
    Article
  2. 2

    Route Optimization System by Zulkifli, Abdul Hayy

    Published 2005
    “…After much research into the many algorithms available, and considering some, including Genetic Algorithm (GA), the author selected Dijkstra's Algorithm (DA). …”
    Get full text
    Get full text
    Final Year Project
  3. 3

    Impact of evolutionary algorithm on optimization of nonconventional machining process parameters by B V, Raghavendra, R Annigiri, Anandkumar, Srikatamurthy, JS

    Published 2025
    “…The PSO algorithm achieved two optimal mean surface roughness values of 0.9333 µm and 0.9838 µm, with an overall average of 0.9399 µm and a standard deviation of 0.0171 µm across 250 runs. …”
    Get full text
    Get full text
    Get full text
    Article
  4. 4

    A Stochastic Total Least Squares Solution of Adaptive Filtering Problem by Javed, Shazia, Ahmad, Noor Atinah

    Published 2014
    “…The TLMS algorithm is computationally simpler than the other TLS algorithms and demonstrates a better performance as compared with the least mean square (LMS) and normalized least mean square (NLMS) algorithms. …”
    Get full text
    Get full text
    Get full text
    Article
  5. 5
  6. 6

    Fuzzy modeling using Bat Algorithm optimization for classification by Noor Amidah, Ahmad Sultan

    Published 2018
    “…In order to solve it, Bat Algorithm method is implement in to optimization method in fuzzy modeling for classification. …”
    Get full text
    Get full text
    Get full text
    Undergraduates Project Papers
  7. 7

    On the problem formulation for parameter extraction of the photovoltaic model: novel integration of hybrid evolutionary algorithm and Levenberg Marquardt based on adaptive damping... by Mohammed Ridha, Hussein, Hizam, Hashim, Mirjalili, Seyedali, Othman, Mohammad Lutfi, Ya'acob, Mohammad Effendy, Ahmadipour, Masoud, Ismaeel, Nooruldeen Q.

    Published 2022
    “…This paper presents an approach to determine the nine parameters of the three diode (TD) PV model based on the integration of the guaranteed convergence arithmetic optimization algorithm and Levenberg-Marquardt with adaptive damping nonlinear parameter method named as GCAOAAdLM. …”
    Get full text
    Get full text
    Article
  8. 8

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

    Published 2006
    “…The problem lies in estimating the posterior density of the parameters which is analytically intractable. A solution to this problem is using the Markov Chain Monte Carlo method namely Gibbs sampler algorithm. …”
    Get full text
    Get full text
    Thesis
  9. 9

    A proposed variable parameter control chart for monitoring the multivariate coefficient of variation by Chew, X. Y., Khoo, B. C., Khaw, K. W., Yeong, W. C. *, Chong, Z. L.

    Published 2019
    “…In certain processes where the process mean and variance are not independent of one another, the coefficient of variation (CV), which measures the ratio of the standard deviation to the mean, should be monitored. …”
    Get full text
    Get full text
    Article
  10. 10

    A novel quantum calculus-based complex least mean square algorithm (q-CLMS) by Sadiq, A., Naseem, I., Khan, S., Moinuddin, M., Togneri, R., Bennamoun, M.

    Published 2022
    “…Transient and steady-state analyses of the proposed q-CLMS algorithm are performed and exact analytical expressions for mean analysis, mean square error (MSE), excess mean square error (EMSE), mean square deviation (MSD) and misadjustment are presented. …”
    Get full text
    Get full text
    Article
  11. 11

    A novel quantum calculus-based complex least mean square algorithm (q-CLMS) by Sadiq, A., Naseem, I., Khan, S., Moinuddin, M., Togneri, R., Bennamoun, M.

    Published 2022
    “…Transient and steady-state analyses of the proposed q-CLMS algorithm are performed and exact analytical expressions for mean analysis, mean square error (MSE), excess mean square error (EMSE), mean square deviation (MSD) and misadjustment are presented. …”
    Get full text
    Get full text
    Article
  12. 12

    A novel quantum calculus-based complex least mean square algorithm (q-CLMS) by Sadiq, A., Naseem, I., Khan, S., Moinuddin, M., Togneri, R., Bennamoun, M.

    Published 2023
    “…Transient and steady-state analyses of the proposed q-CLMS algorithm are performed and exact analytical expressions for mean analysis, mean square error (MSE), excess mean square error (EMSE), mean square deviation (MSD) and misadjustment are presented. …”
    Get full text
    Get full text
    Article
  13. 13

    Optimization of process parameters for rapid adsorption of Pb(II), Ni(II), and Cu(II) by magnetic/talc nanocomposite using wavelet neural network by Darajeh, Negisa, Masoumi, Hamid Reza Fard, Kalantari, Katayoon, Ahmad @ Ayob, Mansor, Shameli, Kamyar, Basri, Mahiran, Khandanlou, Roshanak

    Published 2016
    “…This comparison indicated that the IBP algorithm had the minimum root-mean-square error and absolute average deviation, and maximum coefficient of determination, for the test dataset. …”
    Get full text
    Get full text
    Get full text
    Article
  14. 14

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

    Published 2009
    “…It is now evident that the classical mean and classical standard deviation are easily affected by the presence of outliers. …”
    Get full text
    Get full text
    Thesis
  15. 15

    Parameter identification of thermoelectric modules using enhanced slime mould algorithm (ESMA) by Ponnalagu, Dharswini, Mohd Ashraf, Ahmad, Jui, Julakha Jahan

    Published 2024
    “…Competency of the proposed algorithm in generating the optimal parameters for TEMs was appraised based on 21 benchmarked design parameters, following the objective of root mean square error (RMSE) minimization between the temperature of both actual and estimated models. …”
    Get full text
    Get full text
    Get full text
    Article
  16. 16

    Optimal route checking using genetic algorithm for UiTM's bus services / Tengku Salman Fathi Tengku Jaafar by Tengku Jaafar, Tengku Salman Fathi

    Published 2006
    “…This research study with the development of the Optimal Route Checking Using Genetic Algorithm system should solve this scenario. …”
    Get full text
    Get full text
    Thesis
  17. 17

    Optimize class time tabling by using genetic algorithm technique in UTHM by Ahmad, Izah Rafidah

    Published 2019
    “…This research used genetic algorithm (GA) that was applied to java programming languages with a goal of reducing conflict and optimizing the fitness. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  18. 18

    Agents for Fuzzy Indices of Reliability Power System with Uncertainty Using Monte Carlo Algorithm by Shalash, Nadheer A., Abu Zaharin, Ahmad

    Published 2014
    “…Two agents are developed based on fuzzy parameters of Monte Carlo i.e. current with its means and variances; the other agent is the probability of outage capacity for each state. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  19. 19
  20. 20

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…Features selection process can be considered a problem of global combinatorial optimization in machine learning. Genetic algorithm GA had been adopted to perform features selection method; however, this method could not deliver an acceptable detection rate, lower accuracy, and higher false alarm rates. …”
    Get full text
    Get full text
    Thesis