Search Results - (( developing loading tree algorithm ) OR ( java application optimisation algorithm ))

  • Showing 1 - 19 results of 19
Refine Results
  1. 1

    Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

    Published 2019
    “…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
    Get full text
    Get full text
    Get full text
    Article
  2. 2

    Developing an app for streamlined inventory tracking with barcode scanning and load planning optimization by Teng, Yan Xin

    Published 2025
    “…Keywords: Inventory Management, Barcode Scanning, Load Planning, Binary Tree Bin Packing Algorithm, Mobile Application Development. …”
    Get full text
    Get full text
    Final Year Project / Dissertation / Thesis
  3. 3
  4. 4

    Constructing routing tree for centralized scheduling using multi-channel single transceiver system in 802.16 mesh mode by Al-Hemyari, Ali, Ng, Chee Kyun, Noordin, Nor Kamariah, Ismail, Alyani, Khatun, Sabira

    Published 2008
    “…This paper proposes a centralized scheduling algorithm that can reduce interferences by constructing routing tree with multi-channel single transceiver system in WiMAX mesh networks. …”
    Get full text
    Get full text
    Conference or Workshop Item
  5. 5

    Fuzzy Systems and Bat Algorithm for Exergy Modeling in a Gas Turbine Generator by Alemu Lemma, Tamiru, Mohd Hashim, Fakhruldin

    Published 2011
    “…The models cover part load as well as full load operating conditions. The fuzzy models are trained applying locally linear model tree algorithm followed by a meta-heuristic nature inspired algorithm called bat algorithm. …”
    Get full text
    Conference or Workshop Item
  6. 6

    Optimal load management strategy for enhanced time of use (ETOU) electricity tariff in Peninsular Malaysia / Mohamad Fani Sulaima by Sulaima, Mohamad Fani

    Published 2020
    “…A novel method was developed by integrating a modified energy audit procedure with decision tree technique to determine the percentage of controlled loads available for LM, and the optimal LM weightage. …”
    Get full text
    Get full text
    Thesis
  7. 7

    A Comparative Analysis of Peak Load Shaving Strategies for Isolated Microgrid Using Actual Data by Rana, M.M., Rahman, A., Uddin, M., Sarkar, M.R., Shezan, S.A., Ishraque, M.F., Rafin, S.M.S.H., Atef, M.

    Published 2022
    “…The model consists of four major components such as, PV, BESS, variable load, and gas turbine generator (GTG) dispatch models for the proposed algorithm, where the BESS and PV models are not applicable for the capacity addition technique. …”
    Get full text
    Get full text
    Article
  8. 8
  9. 9

    Web-based expert system for material selection of natural fiber- reinforced polymer composites by Ahmed Ali, Basheer Ahmed

    Published 2015
    “…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
    Get full text
    Get full text
    Thesis
  10. 10

    Development of an intelligent information system for financial analysis depend on supervised machine learning algorithms by Lei, X., Mohamad, U.H., Sarlan, A., Shutaywi, M., Daradkeh, Y.I., Mohammed, H.O.

    Published 2022
    “…The development of Management Information Systems (MIS) is impossible without the use of machine learning (ML). …”
    Get full text
    Get full text
    Article
  11. 11

    A Performance Comparison of Various Artificial Intelligence Approaches for Estimation of Sediment of River Systems by Hayder G., Solihin M.I., Kushiar K.F.B.

    Published 2023
    “…It was found that there is strong correlation between sediment and suspended solid with correlation coefficient of R = 0.9. The developed ML model successfully estimated the sediment load with competitive results from ANN, Decision Tree, AdaBoost and SVM. …”
    Article
  12. 12

    A short predictive Model Predictive Control (MPC) approach for hybrid characteristics analysis in DC-DC converter by Erliza, Serri

    Published 2017
    “…The MPC algorithm is developed based on the hybrid characteristic signals from the DC-DC converter. …”
    Get full text
    Get full text
    Thesis
  13. 13

    Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan by Meisam , Gordan

    Published 2020
    “…In the modeling phase, amongst all DM algorithms, the applicability of machine learning, artificial intelligence and statistical data mining techniques were examined using Support Vector Machine (SVM), Artificial Neural Network (ANN) and Classification and Regression Tree (CART) to detect the hidden patterns in vibration data. …”
    Get full text
    Get full text
    Get full text
    Thesis
  14. 14

    Energy balancing mechanisms for decentralized routing protocols in wireless sensor networks by Saleh, Ahmed Mohammed Shamsan

    Published 2012
    “…Finally, we propose Self-Decision Route Selection scheme which is an improvement of the Hop-based Spanning Tree (HST) algorithm that is used in some routing protocols such as AODV and DSR. …”
    Get full text
    Get full text
    Thesis
  15. 15

    Efficient flow-based channel assignment schemes for congestion avoidance in wireless mesh networks by Abdulla Mogaibel, Hassen Abd-Almotaleb

    Published 2016
    “…In addition, a hybrid interface assignment strategy is developed based on the spanning tree structure of the gateway traffic. …”
    Get full text
    Get full text
    Thesis
  16. 16

    Gateway placement optimisation problem for mobile multicast design in wireless mesh networks by Sanni, Mistura L., Hassan Abdalla Hashim, Aisha, Anwar, Farhat, Naji, Ahmed Wathik

    Published 2012
    “…Furthermore, the paper develops the sketch of modeling and formulation of IGW placement problem with the objective of optimising IGW placement while cost of multicast tree and mobility are optimised. …”
    Get full text
    Get full text
    Get full text
    Proceeding Paper
  17. 17

    A contactless computer vision system for underwater walking and jogging gait analysis using YOLO-pose and Multi-CNN BiLSTM architecture by Cheng, Tong Bao, Khairuddin, Uswah

    Published 2025
    “…A comparison of hyperparameter optimization algorithms was conducted, with the combination of multivariate tree-structured Parzen estimators (MultiTPE) and Hyperband identified as the optimal approach. …”
    Get full text
    Get full text
    Get full text
    Get full text
    Article
  18. 18

    Modeling purchase intention towards edible bird's nest products among Malaysians by Mohamad Shukri, Nurul Nabilah Huda, Mohd Nawi, Nolila, Abdullah, Amin Mahir, Man, Norsida

    Published 2018
    “…The three popular classification algorithms from predictive models which are decision tree, logistic regression, and artificial neural network will be used to analyze the dataset and determined the best model building. …”
    Get full text
    Get full text
    Get full text
    Article
  19. 19

    Ganoderma boninense classification based on near-infrared spectral data using machine learning techniques by Mas Ira Syafila, Mohd Hilmi Tan, Mohd Faizal, Jamlos, Ahmad Fairuz, Omar, Kamarulzaman, Kamarudin, Mohd Aminudin, Jamlos

    Published 2022
    “…A PLS regression is used on NIR spectra to implement the prediction of ergosterol concentration which shows good corelation of R = 0.861 between the ergosterol concentration and oil palm NIR spectra. Four different ML algorithms are tested for prediction of G. boninense infection: K-Nearest Neighbour (kNN), Naïve Bayes (NB), Support Vector Machine (SVM) and Decision Tree (DT) are tested which depicted DT algorithm achieves a satisfactory overall performance with high accuracy up to 93.1% and F1-score of 92.6% compared to other algorithms. …”
    Get full text
    Get full text
    Get full text
    Article