Search Results - (( (variable OR variables) simulation model algorithm ) OR ( java application learning algorithm ))

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  1. 1
    A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models

    A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models by ul Islam, B., Baharudin, Z.

    Published 2017
    “…Genetic algorithm and simulated annealing techniques are used to optimize the control parameters of the neural network. …”
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  2. 2
    Forecasting hydrological parameters for reservoir system utilizing artificial intelligent models and exploring their influence on operation performance

    Forecasting hydrological parameters for reservoir system utilizing artificial intelligent models and exploring their influence on operation performance by Allawi, Mohammed Falah, Jaafar, Othman, Mohamad Hamzah, Firdaus, Koting, Suhana, Mohd, Nuruol Syuhadaa, El-Shafie, Ahmed

    Published 2019
    “…During the simulation procedure, although reservoir inflow and evaporation are stochastic variables that are required to be forecasted during simulation, they are considered deterministic variables. …”
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  3. 3
    SURE-Autometrics algorithm for model selection in multiple equations

    SURE-Autometrics algorithm for model selection in multiple equations by Norhayati, Yusof

    Published 2016
    “…This automatic model selection algorithm is better than non-algorithm procedure which requires knowledge and extra time. …”
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    Thesis
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  4. 4
    Design optimization of valve timing at various engine speeds using Multi-Objective Genetic Algorithm (MOGA)

    Design optimization of valve timing at various engine speeds using Multi-Objective Genetic Algorithm (MOGA) by Mohiuddin, A. K. M., Ashour, Ahmed Aly Ibrahim Shaaban, Yap, Haw Shin

    Published 2008
    “…This paper involves engine modeling in 1D software simulation environment, GT-Power. …”
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    Proceeding Paper
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  5. 5
    Neural network based model predictive control for a steel pickling process

    Neural network based model predictive control for a steel pickling process by Kittisupakorn, P., Thitiyasook, P., Hussain, Mohd Azlan, Daosud, W.

    Published 2009
    “…The Levenberg-Marquardt algorithm is used to train the process models. In the control (MPC) algorithm, the feedforward neural network models are used to predict the state variables over a prediction horizon within the model predictive control algorithm for searching the optimal control actions via sequential quadratic programming. …”
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  6. 6
    Assessing the simulation performances of multiple model selection algorithm

    Assessing the simulation performances of multiple model selection algorithm by Yusof, Norhayati, Ismail, Suzilah, Tuan Muda, Tuan Zalizam

    Published 2015
    “…The capability of the algorithm in finding the true specification of multiple models is measured by the percentage of simulation outcomes.Overall results show that the algorithm has performed well for a model with two equations.The findings also indicated that the number of variables in the true models affect the algorithm performances. …”
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  7. 7
    Classification for large number of variables with two imbalanced groups

    Classification for large number of variables with two imbalanced groups by Ahmad Hakiim, Jamaluddin

    Published 2020
    “…This study proposed two algorithms of classification namely Algorithm 1 and Algorithm 2 which combine resampling, variable extraction, and classification procedure. …”
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  8. 8
    Development of a building energy analysis package (BEAP) and its application to the analysis of cool thermal energy storage systems

    Development of a building energy analysis package (BEAP) and its application to the analysis of cool thermal energy storage systems by Senawi, M. Y.

    Published 2001
    “…A library building is used as a simulation model to demonstrate the application of the new package for simulating CTES systems. …”
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  9. 9
    Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data

    Robust diagnostics and variable selection procedure based on modified reweighted fast consistent and high breakdown estimator for high dimensional data by Baba, Ishaq Abdullahi

    Published 2022
    “…The performance of the proposed method is illustrated using simulation study and on glass vessel data with 1920 variables, cardiomyopathy microarray data with 6319 variables, and octane data with 226 dimensions. …”
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  10. 10
    Feature selection and model selection algorithm using incremental mixed variable ant colony optimization for support vector machine classifier

    Feature selection and model selection algorithm using incremental mixed variable ant colony optimization for support vector machine classifier by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

    Published 2013
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  11. 11
    ENGINEERING DESIGN WITH PSO ALGORITHM

    ENGINEERING DESIGN WITH PSO ALGORITHM by MHD BASIR, SITI NUR HAJAR

    Published 2019
    “…Currently, engineering design faces multiple complexity as it is very dependent on computer to ensure adequate modelling and simulation optimisation. This creates such problems and one of the root causes is the amount variables used by design engineers. …”
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    Final Year Project
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  12. 12
    Sensitivity-based fuzzy multi-objective portfolio model with Value-at-Risk

    Sensitivity-based fuzzy multi-objective portfolio model with Value-at-Risk by Zhang, H., Watada, J., Wang, B.

    Published 2019
    “…Meanwhile, based on the fuzzy simulation technique, the model adapted to a series of different distributed fuzzy variable, an improved particle swarm optimization algorithm (IPSO) is used for numerical simulations. …”
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  13. 13
    Maximizing power generation in variable speed micro-hydro with power point tracking

    Maximizing power generation in variable speed micro-hydro with power point tracking by Min Keng Tan, Norafe Maximo Javinez, Kit Guan Lim, Ahmad Razani Haron, Pungut Ibrahim, Kenneth Tze Kin Teo

    Published 2022
    “…This research first introduces a mathematical model for an experimental variable speed micro-hydro platform and then simulates the microhydro in MATLAB. …”
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  14. 14
    Penalized Quantile Regression Methods And Empirical Mode Decomposition For Improving The Accuracy Of The Model Selection

    Penalized Quantile Regression Methods And Empirical Mode Decomposition For Improving The Accuracy Of The Model Selection by Ambark, Ali Saleh Al-Massri

    Published 2024
    “…Moreover, selecting the relevant variables when fitting the regression model is critical. …”
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  15. 15
    Ensemble Dual Recursive Learning Algorithms for Identifying Custom Tanks Flow with Leakage

    Ensemble Dual Recursive Learning Algorithms for Identifying Custom Tanks Flow with Leakage by Akib, Afifi, Saad , Nordin, Asirvadam , Vijanth Sagayan

    Published 2010
    “…Relative mass release of the leakage is introduced as the input for the simulation model and the data from the simulation model is taken at real time (on-line) to feed into the recursive algorithms. …”
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  16. 16
    Automatic control of flotation process using computer vision

    Automatic control of flotation process using computer vision by Saravani, Ali Jahed

    Published 2015
    “…A froth model correlating the image variables to process variables and a prediction system estimating the metallurgical parameters based on image variables were then developed by using a neural network structure. …”
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  17. 17
    Independent And Dependent Job Scheduling Algorithms Based On Weighting Model For Grid Environment

    Independent And Dependent Job Scheduling Algorithms Based On Weighting Model For Grid Environment by M. Al-Najjar, Hazem

    Published 2018
    “…The resulting model is then applied onto the independent and dependent job scheduling algorithms to verify the capability of proposed job scheduling model in a real environment. …”
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  18. 18
    General Algorithm of n-Multiple Coil Shape for Variable Links Hyper-Redundant Robotic Manipulator

    General Algorithm of n-Multiple Coil Shape for Variable Links Hyper-Redundant Robotic Manipulator by Jamali, Annisa, Khan, Md. Raisuddin, Rahman , Md Mozasser

    Published 2011
    “…Further, the method allows planar manipulator to reach the same desired position by different paths. Numerical simulations for planar models are presented in order to illustrate the competency of the model.…”
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    Proceeding Paper
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  19. 19
    Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification

    Deterministic Mutation-Based Algorithm for Model Structure Selection in Discrete-Time System Identification by Abd Samad, Md Fahmi

    Published 2011
    “…A deterministic mutation-based algorithm is introduced to overcome this problem. Identification studies using NARX (Nonlinear AutoRegressive with eXogenous input) models employing simulated systems and real plant data are used to demonstrate that the algorithm is able to detect significant variables and terms faster and to select a simpler model structure than other well-known EC methods.…”
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  20. 20
    A Comparative Analysis of Peak Load Shaving Strategies for Isolated Microgrid Using Actual Data

    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. …”
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