Search Results - (( simulation optimization model algorithm ) OR ( using vectorization _ algorithm ))

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  1. 1

    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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    Article
  2. 2

    The potential of a novel support vector machine trained with modified mayfly optimization algorithm for streamflow prediction by Adnan R.M., Kisi O., Mostafa R.R., Ahmed A.N., El-Shafie A.

    Published 2023
    “…Balancing; Forecasting; Stream flow; Support vector machines; Exploitation and explorations; Machine learning models; Optimisations; Optimization algorithms; Prediction modelling; Simulated annealing integrated with mayfly optimization; Streamflow prediction; Support vector regression models; Support vector regressions; Support vectors machine; Simulated annealing; algorithm; mayfly; optimization; prediction; streamflow; support vector machine; Jhelum River…”
    Article
  3. 3

    Optimization of support vector machine parameters in modeling of Iju deposit mineralization and alteration zones using particle swarm optimization algorithm and grid search method by Abbaszadeh M., Soltani-Mohammadi S., Ahmed A.N.

    Published 2023
    “…Copper deposits; Deposits; Geology; Learning algorithms; Mineralogy; Static Var compensators; Support vector machines; Three dimensional computer graphics; Alteration zones; Grid search; Grid-search method; Mineralization zone; Model Selection; Particle swarm optimization algorithm; Penalty parameters; Performance; Support vector classifiers; Support vectors machine; Particle swarm optimization (PSO); accuracy assessment; algorithm; classification; computer simulation; copper; geological survey; mineral alteration; mineralization; numerical model; ore deposit; parameterization; performance assessment; porphyry; resource assessment; support vector machine; three-dimensional modeling; Iran…”
    Article
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    Vector Evaluated Gravitational Search Algorithm (VEGSA) for multi-objective optimization problems by Zuwairie, Ibrahim, Badaruddin, Muhammad, Kamarul Hawari, Ghazali, Lim, Kian Sheng, Sophan Wahyudi, Nawawi, Zulkifli, Md. Yusof

    Published 2012
    “…The proposed algorithm, which is called Vector Evaluated Gravitational Search Algorithm (VEGSA), uses a number of populations of particles. …”
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    Conference or Workshop Item
  6. 6

    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
    “…In order to enhance SVM performance, these problems must be solved simultaneously because error produced from the feature subset selection phase will affect the values of the SVM parameters and resulted in low classification accuracy.Most approaches related with solving SVM model selection problem will discretize the continuous value of SVM parameters which will influence its performance.Incremental Mixed Variable Ant Colony Optimization (IACOMV) has the ability to solve SVM model selection problem without discretising the continuous values and simultaneously solve the two problems.This paper presents an algorithm that integrates IACOMV and SVM.Ten datasets from UCI were used to evaluate the performance of the proposed algorithm.Results showed that the proposed algorithm can enhance the classification accuracy with small number of features.…”
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    Article
  7. 7

    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
    “…The three different optimization algorithms used in this study are the genetic algorithm (GA), particle swarm optimization (PSO) algorithm and shark machine learning algorithm (SMLA). …”
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    Article
  8. 8
  9. 9

    Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

    Published 2016
    “…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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    Thesis
  10. 10

    Sensor-less vector control using adaptive observer scheme for controlling the performance of the induction motor / Mazhar Hussain Abbasi by Mazhar, Hussain Abbasi

    Published 2013
    “…Simulation is done by using the observer which uses optimal feedback gain as an example of process from algorithm design to verification of logic. …”
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    Thesis
  11. 11

    Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

    Published 2018
    “…To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
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    Thesis
  12. 12
  13. 13

    Novel reservoir system simulation procedure for gap minimization between water supply and demand by Allawi, Mohammed Falah, Jaafar, Othman, Mohamad Hamzah, Firdaus, El-Shafie, Ahmed

    Published 2019
    “…In this research, an optimization algorithm, namely, the shark machine learning algorithm (SMLA) that has high inertia for obtaining its targets, is proposed that mimics the natural shark process. …”
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    Article
  14. 14

    A new particle swarm optimization for wireless mesh routing protocol by Abd. Rahman, Tharek

    Published 2008
    “…We test the propose algorithm in network simulator 2 (ns2). Based on the results, we proven that PSO-SIIW algorithm can be applied to MPR calculation in OLSR.…”
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    Monograph
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    A STUDY OF TORQUE VECTORING AND TRACTION CONTROL FOR AN ALL-WHEEL DRIVE ELECTRIC VEHICLE by MOHAMAD NOOR IMAN, Mohd Nor

    Published 2013
    “…In addition, an optimal control algorithm will be developed for best performance to minimize energy losses using MATLAB/Simulink software. …”
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    Final Year Project
  17. 17

    A New Optimization Technique Of Support Vector Machine For Electricity Market Price Forecasting by Wan Abdul Razak, Intan Azmira, Zainal Abidin, Izham, Yap, Keem Siah, Sulaima, Mohamad Fani, Hassan, Elia Erwani, Gan, Chin Kim

    Published 2019
    “…Therefore, a hybrid of Least Square Support Vector Machine (LSSVM) and Bacterial Foraging Optimization Algorithms (BFOA) is proposed in this research to provide an accurate price forecast with optimized LSSVM parameters (gamma and sigma) and features. …”
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    Technical Report
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    A study of torque vectoring and traction control for an all-wheel drive electric vehicle by Maharun, M., Mohd Nor, M.N.I.

    Published 2014
    “…In addition, an optimal control algorithm will be developed for best performance to minimize energy losses using MATLAB/Simulink software. …”
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    Conference or Workshop Item
  20. 20

    Minimization of torque ripple and flux droop using optimal DTC switching and sector rotation strategy by Ahmad Tarusan, Siti Azura

    Published 2022
    “…A five-level cascaded H-bridge (CHB) inverter was used in the optimal DTC switching strategy because it had many voltage vectors and could be used for a variety of speed operations. …”
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    Thesis