Search Results - (( parameter estimation case algorithm ) OR ( parameter optimization based algorithm ))

Refine Results
  1. 1

    Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems by Kek, Sie Long

    Published 2011
    “…The main idea is the integration of optimal control and parameter estimation. In this work, a simplified model-based optimal control model with adjustable parameters is constructed. …”
    Get full text
    Get full text
    Thesis
  2. 2
  3. 3
  4. 4
  5. 5

    LASSO-type estimations for threshold autoregressive and heteroscedastic time series models. by Muhammad Jaffri Mohd Nasir

    Published 2020
    “…We develop an active-set based block coordinate descent algorithm (BCD) to optimize exactly the group LASSO. …”
    Get full text
    Get full text
    UMK Etheses
  6. 6
  7. 7
  8. 8
  9. 9

    Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm by Farzin, Saeed, Singh, Vijay, Karami, Hojat, Farahani, Nazanin, Ehteram, Mohammad, Kisi, Ozgur, Allawi, Mohammed Falah, Mohd, Nuruol Syuhadaa, El-Shafie, Ahmed

    Published 2018
    “…The present study attempted to develop a three-parameter Muskingum model considering lateral flow for flood routing, coupling with a new optimization algorithm namely, Improved Bat Algorithm (IBA). …”
    Get full text
    Get full text
    Article
  10. 10

    Genetic Algorithm Based Lightning Estimation Model by Musse Mohamud, Ahmed, Mohammad Kamrul, Bin Hasan, Jong, F. Chen, Denis, Lee

    Published 2020
    “…Using the GA optimized parameter the estimations areprecise. To achieve estimation that is more accurate many trials are required to be carried out in order to determine the best fitness value. …”
    Get full text
    Get full text
    Get full text
    Article
  11. 11

    Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets by Saeed, Sana

    Published 2019
    “…A new self-adaptive hybrid algorithm (CSCMAES) is introduced for optimization. …”
    Get full text
    Get full text
    Thesis
  12. 12

    Estimation of transformers health index based on condition parameter factor and hidden Markov model by Mohd Selva, Amran, Yahaya, Muhammad Sharil, Azis, Norhafiz, Ab Kadir, Mohd Zainal Abidin, Jasni, Jasronita, Yang Ghazali, Young Zaidey

    Published 2018
    “…First, the mean for HI in each year was computed and the transition probabilities for the condition data were obtained based on non-linear optimization technique. Next, the emission probabilities for each of the condition parameter factors were derived based on frequency of occurrence method. …”
    Get full text
    Get full text
    Conference or Workshop Item
  13. 13
  14. 14

    A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

    Published 2024
    “…Consequently, the study involved exploiting optimization techniques to enhance the training artificial intelligence algorithm for streamflow forecasting from a gradient-based to a stochastic population-based approach in several aspects, including solution quality, computational effort, and parameter sensitivity on streanflow in Johor, Malaysia. …”
    Get full text
    Get full text
    Get full text
    Thesis
  15. 15

    Base drag estimation in suddenly expanded supersonic flows using backpropagation genetic and recurrent neural networks by Jaimon, Dennis Quadros, Prashanth, T., Khan, Sher Afghan

    Published 2022
    “…On the other hand, an effort is made to decide the optimal set of flow and geometric parameters for achieving the desired base pressure by reverse mapping (RM). …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  16. 16

    The impact of executive function and aerobic exercise recognition in obese children under deep learning by JING, XIN, ABDULLAH, BORHANNUDIN, ABU SAAD, HAZIZI, YANG, XIANGKUN

    Published 2025
    “…Initially, a motion recognition model based on STN and Lucas–Kanade optical flow algorithm optimization was constructed. …”
    Get full text
    Get full text
    Article
  17. 17

    Improving the modeling capacity of Volterra model using evolutionary computing methods based on Kalman Smoother adaptive filter by ., Edwar Yazid, Mohd Shahir Liew, Setyamartana Parman, Velluruzhati

    Published 2015
    “…This paper proposes three steps of improvements for identification of the nonlinear dynamic system, which exploits the concept of a state-space based time domain Volterra model. The first step is combining the forward and backward estimator in the original Volterra model; the second step is reformulating the Volterra model into a state-space model so that the Kalman Smoother (KS) adaptive filter can be used to estimate the kernel coefficients; the third step is optimization of KS parameters using evolutionary computing algorithms such as particle swarm optimization (PSO), genetic algorithm (GA) and artificial bee colony (ABC). …”
    Get full text
    Get full text
    Article
  18. 18

    A memory-guided Jaya algorithm to solve multi-objective optimal power flow integrating renewable energy sources by Ahmadipour M., Ali Z., Ramachandaramurthy V.K., Ridha H.M.

    Published 2025
    “…To ensure fair comparisons, parameter configurations for all algorithms are automated using the parameter tuning tool iterated racing (irace). …”
    Review
  19. 19

    Improved genetic algorithm for direct current motor high speed controller implemented on field programmable gate array by Alkhafaji, Falih Salih

    Published 2019
    “…There are many researches have been done to optimize PI controller based evolutionary algorithm, such as Genetic Algorithm (GA). …”
    Get full text
    Get full text
    Thesis
  20. 20

    River flow prediction based on improved machine learning method: Cuckoo Search-Artificial Neural Network by Zanial W.N.C.W., Malek M.B.A., Reba M.N.M., Zaini N., Ahmed A.N., Sherif M., Elshafie A.

    Published 2024
    “…Finding the best value for the hyper-parameters is one of the problems with machine learning algorithms, which have lately been adopted by many academics. …”
    Article