Search Results - (( using practical problem algorithm ) OR ( using optimization means 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
    “…Instead of solving the original optimal control problem, the model-based optimal control problem is solved. …”
    Get full text
    Get full text
    Thesis
  2. 2

    Finding minimum path by using Genetic Algorithm (GA)/ Siti Zuraifah Hashim by Hashim, Siti Zuraifah

    Published 2007
    “…It makes use of three basic operations in order to optimize this problem. …”
    Get full text
    Get full text
    Thesis
  3. 3

    Simulation of shortest path using a-star algorithm / Nurul Hani Nortaja by Nurul Hani , Nortaja

    Published 2004
    “…The steps to calculate a shortest path using A • algorithm is shown by using appropriate examples and related figures. …”
    Get full text
    Get full text
    Thesis
  4. 4
  5. 5
  6. 6

    GF-CLUST: A nature-inspired algorithm for automatic text clustering by Mohammed, Athraa Jasim, Yusof, Yuhanis, Husni, Husniza

    Published 2016
    “…Text clustering is a task of grouping similar documents into a cluster while assigning the dissimilar ones in other clusters.A well-known clustering method which is the K-means algorithm is extensively employed in many disciplines.However, there is a big challenge to determine the number of clusters using K-means. …”
    Get full text
    Get full text
    Get full text
    Article
  7. 7

    Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems by Nor Sakinah, Abdul Shukor

    Published 2019
    “…In the industry, the proportional-integral-derivative (PID) controller is the control method that has been widely implemented because of its simplicity, the fact that it is more understandable and more reliable to be used for industrial purposes. So far, the tuning methods used for data-driven PID for the underactuated systems are mostly based on the multi-agent-based optimization, which means that the design requires substantial computation time and make it not practical for on-line tuning applications. …”
    Get full text
    Get full text
    Thesis
  8. 8

    Safe experimentation dynamics algorithm for data-driven PID controller of a class of underactuated systems by Nor Sakinah, Abdul Shukor

    Published 2019
    “…In the industry, the proportional-integral-derivative (PID) controller is the control method that has been widely implemented because of its simplicity, the fact that it is more understandable and more reliable to be used for industrial purposes. So far, the tuning methods used for data-driven PID for the underactuated systems are mostly based on the multi-agent-based optimization, which means that the design requires substantial computation time and make it not practical for on-line tuning applications. …”
    Get full text
    Get full text
    Thesis
  9. 9

    Optimization of Workload Allocation Problem in a Network of Heterogeneous Computer Systems by Rahela, Abdul Rahim

    Published 2005
    “…Other service distributional models such as exponential, Erlang-k and Gamma have also been used to expand the work applicability. A new algorithm of workload allocation scheme using First Come First Serve discipline in conjunction with optimization of GE queueing systems is proposed for minimizing mean queue length and mean response time in a network of computer systems. …”
    Get full text
    Get full text
    Get full text
    Thesis
  10. 10

    Plant identification using combination of fuzzy c-means spatial pyramid matching, gist, multi-texton histogram and multiview dictionary learning by Safa, Soodabeh

    Published 2016
    “…Moreover, instead of concatenating feature vectors together and send to classifier, sparse coding and dictionary learning methods are used and instead of considering all features as one view (visual feature), K-SVD algorithm that is one of the famous algorithms for sparse representation is optimized and developed to multi-view model.The experimental results prove that the proposed methods has improved accuracy by 53.77% compared to concatenating features and classic K-SVD dictionary learning model as well.…”
    Get full text
    Get full text
    Thesis
  11. 11

    Combining Recursive Least Square and Principal Component Analysis for Assisted History Matching by Md. Anuar, Nurul Syaza

    Published 2014
    “…The algorithm formulated also can easily be practiced, provided with ample knowledge of numerical computational tool to implement it. …”
    Get full text
    Get full text
    Final Year Project
  12. 12

    Analysis and decentralised optimal flow control of heterogeneous computer communication network models by Ku-Mahamud, Ku Ruhana

    Published 1993
    “…The decentralised optimal local flow control of the multiclass computer communication networks with single and multiple transmission links is shown to be a state dependent window type mechanism that has been traditionally used in practice. …”
    Get full text
    Get full text
    Get full text
    Thesis
  13. 13

    Techno-economic evaluation of off-grid hybrid renewable energy system for rural resort electrification in Malaysia / Monowar Hossain by Monowar, Hossain

    Published 2017
    “…For these purposes, the standalone ANFIS, ANFIS-PSO (particle swarm optimization),ANFIS-GA (genetic algorithm) and ANFIS-DE (differential evolution) prediction algorithms have been developed in MATLAB platform. …”
    Get full text
    Get full text
    Thesis
  14. 14

    Hybrid dynamic scheduling model for flexible manufacturing system with machine availability and new job arrivals by Paslar, Shahla

    Published 2015
    “…The idea of hybridizing the newly developed biogeography based optimization algorithm (BBO) with variable neighborhood structure (VNS) is proposed in order to produce a high performance initial schedule in terms of minimum completion time, tardiness and flow time within reasonable amount of time. …”
    Get full text
    Get full text
    Thesis
  15. 15

    Optimized clustering with modified K-means algorithm by Alibuhtto, Mohamed Cassim

    Published 2021
    “…Clustering technique is able to find hidden patterns and to extract useful information from huge data. Among the techniques, the k-means algorithm is the most commonly used technique for determining optimal number of clusters (k). …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  16. 16

    A near-optimal centroids initialization in K-means algorithm using bees algorithm by Mahmuddin, Massudi, Yusof, Yuhanis

    Published 2009
    “…The K-mean algorithm is one of the popular clustering techniques.The algorithm requires user to state and initialize centroid values of each group in advance. …”
    Get full text
    Get full text
    Get full text
    Conference or Workshop Item
  17. 17

    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. …”
    Get full text
    Get full text
    Thesis
  18. 18
  19. 19

    Finite Element and Differential Quadrature Methods for Heat Distribution in Rectangular Fins by Fakir, Md. Moslemuddin

    Published 2009
    “…DQM is used efficiently to solve various one-dimensional heat transfer problems. …”
    Get full text
    Get full text
    Thesis
  20. 20

    An improvement of stochastic gradient descent approach for mean-variance portfolio optimization problem by S. W. Su, Stephanie, Kek, Sie Long

    Published 2021
    “…Furthermore, the applicability of SGD, Adam, AdaMax, Nadam, AMSGrad, and AdamSE algorithms in solving the mean-variance portfolio optimization problem is validated.…”
    Get full text
    Get full text
    Get full text
    Article