Search Results - (( wave applications a algorithm ) OR ( simulation optimization model algorithm ))

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  1. 1

    Healthcare Data Analysis Using Water Wave Optimization-Based Diagnostic Model by Kaur, Arvinder, Kumar, Yugal

    Published 2021
    “…This paper presents a new diagnostic model for various diseases. In the proposed diagnostic model, a water wave optimization (WWO) algorithm was implemented for improving the diagnosis accuracy. …”
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    Article
  2. 2

    Efficient Numerical Modelling of Extreme Wave by Tan , Vi Nie

    Published 2020
    “…While exploring the model into more wave cases, the accuracy and efficiency of the simulation process is satisfaction. …”
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    Final Year Project
  3. 3

    Efficient Numerical Modelling of Extreme Waves by Tan, Vi Nie

    Published 2020
    “…While exploring the model into more wave cases, the accuracy and efficiency of the simulation process is satisfaction. …”
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    Final Year Project
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    Iterative And Single-Step Solutions Of Two Dimensional Time-Domain Inverse Scattering Problem Featuring Ultra Wide Band Sensors by Binajjaj, Saeed Ali Saeed

    Published 2010
    “…First, the algorithms‘ performances were evaluated using numerical simulation employing two different scanning geometries: limited and full view scanning geometries, where the applicability of these algorithms was accessed by comparing the reconstructed images with actual model. …”
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    Thesis
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    Evaluation of lightning return stroke current using measured electromagnetic fields by Mahdi, Izadi

    Published 2012
    “…Moreover, the field expressions due to inclined lightning channel are proposed and substantiated with the measured fields directly in the time domain, while a realistic channel base current function and the general form of engineering current model are applied. This research proposed an inverse procedure algorithm using the proposed general fields’ expressions and the particle swarm optimization algorithm (PSO) in the time domain where the full channel base current wave shape in time domain can be determined. …”
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    Thesis
  8. 8

    Development of a State-Space Observer for Active Noise Control Systems by Muhssin, Mazin T.

    Published 2009
    “…The secondary path of the ANC system is modeled by using the LMS algorithm to complete the design of the Filtered-X Least Mean Square (FXLMS) controller. …”
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    Thesis
  9. 9

    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
  10. 10

    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
  11. 11

    Process Planning Optimization In Reconfigurable Manufacturing Systems by Musharavati, Farayi

    Published 2008
    “…The five (5) AADTs include; a variant of the simulated annealing algorithm that implements heuristic knowledge at critical decision points, two (2) cooperative search schemes based on a “loose hybridization” of the Boltzmann Machine algorithm with (i) simulated annealing, and (ii) genetic algorithm search techniques, and two (2) modified genetic algorithms. …”
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    Thesis
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    OPTIMAL DESIGN AND ANALYSIS OF A DC–DC SYNCHRONOUS CONVERTER USING GENETIC ALGORITHM AND SIMULATED ANNEALING by K., S. Rama Rao., C. , -K, Chew

    Published 2009
    “…Converter models for simulation are designed for the forward and backup modes of operation. …”
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    Citation Index Journal
  14. 14

    OPTIMAL DESIGN AND ANALYSIS OF A DC–DC SYNCHRONOUS CONVERTER USING GENETIC ALGORITHM AND SIMULATED ANNEALING by K.S., Rama Rao, C. K., Chew

    Published 2009
    “…Converter models for simulation are designed for the forward and backup modes of operation. …”
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    Citation Index Journal
  15. 15

    GENETIC ALGORITHM WITH DEEP NEURAL NETWORK SURROGATE FOR THE OPTIMIZATION OF ELECTROMAGNETIC STRUCTURE by MOHAMMED SHARIFF, NUR ATIQAH

    Published 2020
    “…This paper will report on an initial study of the usage of Genetic Algorithm (GA) merged with Deep Neural Network based surrogate model to optimize simulation for electromagnetic structure. …”
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    Final Year Project
  16. 16

    Enhanced genetic algorithm optimization model for a single reservoir operation based on hydropower generation: case study of Mosul reservoir, northern Iraq by Al‑Aqeeli, Yousif H., Lee, Teang Shui, Abd Aziz, Samsuzana

    Published 2016
    “…The purpose of this study was to formulate and improve an approach of a genetic algorithm optimization model (GAOM) in order to increase the maximization of annual hydropower generation for a single reservoir. …”
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    Article
  17. 17

    Optimization of Prediction Error in CO2 Laser Cutting process by Taguchi Artificial Neural Network Hybrid with Genetic algorithm by Nukman, Y., Hassan, M.A., Harizam, M.Z.

    Published 2013
    “…The potential of genetic algorithm in optimization was utilized in the proposed hybrid model to minimize the error prediction for regions of cutting conditions away from the Taguchi based factor level points. …”
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    Article
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    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
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