Search Results - (( variables location process algorithm ) OR ( java adaptation optimization algorithm ))

Refine Results
  1. 1
  2. 2

    Cloudlet deployment and task offloading in mobile edge computing using variable-length whale and differential evolution optimization and analytical hierarchical process for decisio... by Daba, Layth Muwafaq Abdulhussein

    Published 2023
    “…Unlike the existing optimization algorithm, VL-WIDE features the capability of searching different lengths of solutions to cover the variable number of cloudlets for deployment. …”
    Get full text
    Get full text
    Thesis
  3. 3

    Optimizing the placement of fire department in Kulim using greedy heuristic and simplex method / Muhammad Abu Syah Mohd Suzaly by Mohd Suzaly, Muhammad Abu Syah

    Published 2023
    “…The binary integer programming (BIP) issue is a rare form of integer programming problem in which the value of variable xi is only 0 or 1. In this case, condition xi is also known as a "Binary" or "0 - 1"variable. …”
    Get full text
    Get full text
    Thesis
  4. 4

    A proposed algorithm of random vector in measuring similarity for network topology of Bursa Malaysia by Lim, San Yee

    Published 2018
    “…Hence, to ease the calculation process and improve the computational efficiency of RV coefficient, an algorithm is proposed. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  5. 5

    Multiple Linear Regression Models For Estimating True Subsurface Resistivity From Apparent Resistivity Measurements by Bala, Muhammad Sabiu

    Published 2018
    “…The objective is to minimize the processing time required to carry out inversion with conventional algorithms. …”
    Get full text
    Get full text
    Thesis
  6. 6

    Iris segmentation and normalization approach by Shamsi, Mahboubeh, Saad, Puteh, Rasouli, Abdolreza

    Published 2008
    “…Iris is located by using a variable parameter binning approach. …”
    Get full text
    Get full text
    Article
  7. 7

    Linear regression convolutional neural network for fully automated coronary lumen segmentation in intravascular optical coherence tomography / Yong Yan Yin by Yong, Yan Ling

    Published 2018
    “…The average absolute error of luminal area estimation is 1.38 % and the processing rate is 40.6 ms per image. In addition, an inter-observer variability test was performed and has shown that the proposed algorithm has comparable variability against manual luminal area estimations by expert human observers. …”
    Get full text
    Get full text
    Get full text
    Thesis
  8. 8

    Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions by Saraswati, Galuh Wilujeng

    Published 2017
    “…The project has also implemented the optimization process onto the proposed ANFIS model through the hybrid of Genetic Algorithm on the fuzzy membership function of the ANFIS model. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Thesis
  9. 9

    Predicting sea levels using ML algorithms in selected locations along coastal Malaysia by Hazrin N.A, Chong K.L, Huang Y.F, Ahmed A.N, Ng J.L, Koo C.H, Tan K.W, Sherif M, El-shafie A

    Published 2025
    “…An assessment of the multiple statistics-driven regression algorithms resulted such that each tested location was associated with a particular preferred model. …”
    text::Article
  10. 10

    An Automated Method For Model-Plant Mismatch Detection And Correction In Process Plants Employing Model Predictive Control (MPC) by Ahmed Bahakim, Sami Saeed

    Published 2012
    “…Testing for various mismatch scenarios for both two major contributors to the process, the algorithm was able to bring the output back to the desired set-point in a very short time.…”
    Get full text
    Get full text
    Final Year Project
  11. 11

    Crossover and mutation operators of genetic algorithms by Lim, Siew Mooi, Md. Sultan, Abu Bakar, Sulaiman, Md. Nasir, Mustapha, Aida, Leong, Kuan Yew

    Published 2017
    “…Genetic algorithms (GA) are stimulated by population genetics and evolution at the population level where crossover and mutation comes from random variables. …”
    Get full text
    Get full text
    Get full text
    Article
  12. 12

    Crossover and mutation operators of genetic algorithms by Siew, Mooi Lim, Md. Sultan, Abu Bakar, Sulaiman, Md. Nasir, Mustapha, Aida, Leong, K. Y.

    Published 2017
    “…Genetic algorithms (GA) are stimulated by population genetics and evolution at the population level where crossover and mutation comes from random variables. …”
    Get full text
    Get full text
    Get full text
    Article
  13. 13
  14. 14

    Flood prediction in southern strip of Caspian Sea watershed. by S., Chavoshi, Sulaiman, Wan Nor Azmin, B., Saghafian, Sulaiman, Md Nasir, Abd Manaf, Latifah

    Published 2013
    “…Modeling of hydrological process has become increasingly complicated since we need to take into consideration an increasing number of descriptive variables. …”
    Get full text
    Get full text
    Article
  15. 15

    A comparative effectiveness of hierarchical and non-hierarchical regionalisation algorithms in regionalising the homogeneous rainfall regions by Chuan, Zun Liang, Wan Nur Syahidah, Wan Yusoff, Azlyna, Senawi, Mohd Akramin, Mohd Romlay, Fam, Soo-Fen, Wendy Ling, Shinyie, Tan Lit, Ken

    Published 2022
    “…However, previous studies employed regionalisation algorithms, namely agglomerative hierarchical and non-hierarchical regionalisation algorithms requiring post-processing techniques to validate and interpret the analysis results. …”
    Get full text
    Get full text
    Get full text
    Article
  16. 16

    A comparative effectiveness of hierarchical and nonhierarchical regionalisation algorithms in regionalising the homogeneous rainfall regions by Zun, Liang Chuan, Wan Yusof, Wan Nur Syahidah, Senawi, Azlyna, Mohd Akramin, Mohd Romlay, Soo, Fen Fam, Wendy, Ling Shinyie, Tan, Lit Ken

    Published 2022
    “…However, previous studies employed regionalisation algorithms, namely agglomerative hierarchical and non-hierarchical regionalisation algorithms requiring post-processing techniques to validate and interpret the analysis results. …”
    Get full text
    Get full text
    Get full text
    Article
  17. 17

    An investigation of structural breaks on spot and futures crude palm oil returns by Zainudin, Rozaimah, Shaharudin, Roselee Shah

    Published 2011
    “…The implications of omitting structural break in volatility clustering modelling process are largely discussed in various developed macroeconomic and finance variables. …”
    Get full text
    Get full text
    Article
  18. 18

    Clustering approach on layout redesign to optimize container handling process by Sugiyono, Andre

    Published 2020
    “…One of the ways to achieve these goals is to focus on layout planning and management that can potentially be beneficial to all factors involved such as space exploitation, process efficiency etc. The layout planning of a container terminal can significantly benefit from using Group Technology approach in which containers can be grouped into families of containers and transported between cells(block locations in the yard).With this type of layout, the company has many advantages like flexibility on production process to address high variability in the system. …”
    Get full text
    Get full text
    Get full text
    Article
  19. 19

    Improvement of land cover mapping using Sentinel 2 and Landsat 8 imageries via non-parametric classification by Myaser, Jwan

    Published 2020
    “…Thus, TC suggested being the main step in data pre-processing for mountainous terrain before the RBF-based SVM classification process. …”
    Get full text
    Get full text
    Thesis
  20. 20

    Predicting sea levels using ML algorithms in selected locations along coastal Malaysia by Hazrin N.A., Chong K.L., Huang Y.F., Ahmed A.N., Ng J.L., Koo C.H., Tan K.W., Sherif M., El-shafie A.

    Published 2024
    “…An assessment of the multiple statistics-driven regression algorithms resulted such that each tested location was associated with a particular preferred model. …”
    Article