Search Results - (( java application optimisation algorithm ) OR ( using practical model algorithm ))

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  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. …”
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    Article
  2. 2

    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.…”
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    Thesis
  3. 3

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

    Published 2011
    “…The output is measured from the model and used to adapt the adjustable parameters. …”
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    Thesis
  4. 4

    Hybrid DE-PEM algorithm for identification of UAV helicopter by Tijani, Ismaila, Akmeliawati, Rini, Legowo, Ari, Budiyono, Agus, Abdul Muthalif, Asan Gani

    Published 2014
    “…Design/methodology/approach – In this study, flight data were collected and analyzed; MATLAB-based system identification algorithm was developed using DE and PEM; parameterized state-space model parameters were estimated using the developed algorithm and model dynamic analysis. …”
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    Article
  5. 5

    Real time nonlinear filtered-x lms algorithm for active noise control by Sahib, Mouayad Abdulredha

    Published 2012
    “…Consequently, the practical applicability of the NLFXLMS algorithm is limited by this drawback. …”
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    Thesis
  6. 6

    Algorithmic Loan Risk Prediction Method Based on PSO-EBGWO-Catboost by Chen, Suihai, Bong, Chih How, Chiu, Po Chan

    Published 2024
    “…Under the background of big data, it is of practical significance to prevent loan risk by the machine learning algorithm. …”
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    Article
  7. 7

    Rock brittleness prediction through two optimization algorithms namely particle swarm optimization and imperialism competitive algorithm by Hussain, Azham, Surendar, A., Clementking, A., Kanagarajan, Sujith, Ilyashenko, Lubov K.

    Published 2018
    “…The results showed that the PSO power model has superior fitting specification for the prediction of the BI compared to the other prediction models and is quite practical for use. …”
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    Article
  8. 8

    Multistep forecasting for highly volatile data using new algorithm of Box-Jenkins and GARCH by Siti Roslindar, Yaziz, Roslinazairimah, Zakaria

    Published 2018
    “…The study of the multistep ahead forecast is significant for practical application purposes using the proposed statistical model. …”
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    Conference or Workshop Item
  9. 9

    Modelling and Optimization of Asymmetric Vehicle Routing Problem Using Particle Swarm Optimization Algorithm by Muhamad Rozikin, Kamaluddin, M. F. F., Ab Rashid

    Published 2021
    “…Specific optimization model and algorithm were developed to solve the problem. …”
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    Conference or Workshop Item
  10. 10

    Sampling weight adjustments in partial least squares structural equation modeling: guidelines and illustrations by Cheah, Jun Hwa, Roldan, Jose L., Ciavolino, Enrico, Ting, Hiram, Ramayah, T.

    Published 2020
    “…The results of the WPLS algorithm and the traditional PLS algorithm are then compared using a marketing research model. …”
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    Article
  11. 11

    Mathematical models and optimization algorithms for low-carbon Location-Inventory-Routing Problem with uncertainty by Liu, Lihua

    Published 2024
    “…This thesis also aims to solve the low-carbon LIRP model with uncertainty factors such as carbon trading, customer demand, shortages, and soft time windows using advanced algorithms. …”
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    Thesis
  12. 12

    Laptop price prediction using decision tree algorithm / Nurnazifah Abd Mokti by Abd Mokti, Nurnazifah

    Published 2024
    “…This research project focuses on developing a laptop price prediction model using the decision tree algorithm based on laptop specifications. …”
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    Thesis
  13. 13

    Nlfxlms and thf-nlfxlms algorithms for wiener-hammerstein nonlinear active noise control by Srazhidinov, Radik

    Published 2016
    “…However, this assumption may lead to inaccurate secondary path model. In this work, the modelling of acoustic path using FIR filters is incorporated for both algorithms for Wiener-Hammerstein structure. …”
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    Thesis
  14. 14

    Structural Equation Modeling Algorithm and Its Application in Business Analytics by Sorooshian, Shahryar

    Published 2017
    “…Structural Equation Modeling (SEM) is a statistical-based multivariate modeling methods, Application of SEM is similar but more powerful than regression analysis; and number of scientists using SEM in their research is rupidly inereasing. …”
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    Book Chapter
  15. 15

    Two level Differential Evolution algorithms for ARMA parameters estimatio by Salami, Momoh Jimoh Emiyoka, Tijani, Ismaila, Aibinu, Abiodun Musa

    Published 2013
    “…The performance of the algorithm is evaluated using both simulated ARMA models and practical rotary motion system. …”
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    Proceeding Paper
  16. 16

    Nonlinear adaptive algorithm for active noise control with loudspeaker nonlinearity by Dehkordi, Sepehr Ghasemi

    Published 2014
    “…The proposed THF-NLFXLMS algorithm models the Wiener secondary path and applies the estimated degree of nonlinearity of the nonlinear secondary path in the control algorithm design. …”
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    Thesis
  17. 17

    Automated time series forecasting by Ismail, Suzilah, Zakaria, Rohaiza, Tuan Muda, Tuan Zalizam

    Published 2011
    “…Good planning and controlling procedure would lead to successful business.There are two categories of forecasting techniques; namely qualitative and quantitative.Qualitative technique is more towards judgmental forecasting and usually used when data is limited. While quantitative technique is based on statistical concepts and requires large amount of data in order to formulate the mathematical models.This technique can be classified into projective and causal technique.The projective technique (or univariate modelling) just involve one variable while the causal technique (or econometric modelling) suitable for multi-variables.Since forecasting involves uncertainty, several methods need to be executed on one set of time series data in order to produce accurate forecast.Hence, usually in practice forecaster need to use several softwares to obtain the forecast values.If this practice can be transformed into algorithm (well-defined rules for solving a problem) and then the algorithm can be transformed into a computer program, less time will be needed to compute the forecast values where in business world time is money.In this study, we focused on algorithm development for univariate forecasting techniques only and will expand towards econometric modelling in the future.Two set of simulated data (yearly and non-yearly) and several univariate forecasting techniques (i.e. …”
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    Monograph
  18. 18

    Continuous-time Hammerstein model identification utilizing hybridization of augmented sine cosine algorithm and game-theoretic approach by Mohd Helmi, Suid, Mohd Ashraf, Ahmad, Ahmad Nor Kasruddin, Nasir, Mohd Riduwan, Ghazali, Jui, Julakha Jahan

    Published 2024
    “…To address the limitations of uncovering an optimized continuous-time Hammerstein model, researchers have explored the practical application of the Augmented Sine Cosine Algorithm-Game Theoretic (ASCA-GT). …”
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    Article
  19. 19

    Automated model selection for corporation credit risk assessment using machine learning / Zulkifli Halim by Halim, Zulkifli

    Published 2023
    “…This study also investigates the significance of data dimension in CCRA: single or multi-dimensional, and the correlation of the features. For the best practice machine learning pipelines, various machine learning models are used to discover the best model for CCRA study. …”
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    Thesis
  20. 20

    Earthquake prediction model based on geomagnetic field data using automated machine learning by Yusof, Khairul Adib, Mashohor, Syamsiah, Abdullah, Mardina, Amiruddin, Mohd, Rahman, Abd, Abdul Hamid, Nurul Shazana, Qaedi, Kasyful, Matori, Khamirul Amin, Hayakawa, Masashi

    Published 2024
    “…Several features were extracted from them through wavelet scattering transform (WST). The features were used as the input to model optimization, of which the strategy for automatic algorithm selection and hyperparameter tuning was performed based on the asynchronous successive halving algorithm (ASHA). …”
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    Article