Search Results - (( parameter selection models algorithm ) OR ( parameter extraction method algorithm ))

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  1. 1

    Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms by Ridha, Hussein Mohammed

    Published 2020
    “…Therefore, precisely modeling method to determine the unknown parameters of the PV module is essential to give a realistic evaluation for the extracted energy of the PV array. …”
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    Thesis
  2. 2

    NARX modelling for steam distillation pilot plant using binary particle swarm optimisation technique / Najidah Hambali by Hambali, Najidah

    Published 2019
    “…This study proposes a system identification of SDPP using NARX model. The model structure selection of polynomial NARX had been focused on Binary Particle Swarm Optimisation (BPSO) algorithm. …”
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    System identification of essential oil extraction system using non-linear autoregressive model with exogenous inputs (NARX) / Farahida Awadz by Awadz, Farahida

    Published 2010
    “…Model structure selection was performed by applying the Binary Particle Swarm Optimization (BPSO) algorithm which been developed by (J.Kennedy and R.Eberhart, 1997). …”
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  5. 5

    CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING by ISLAM, BADAR UL ISLAM

    Published 2017
    “…The solution set (i.e. optimized weight/bias matrix of ANN) provided by the optimized and improved genetic algorithm and modified BP based model is extracted and used in the design and development of a prototype device of the proposed model. …”
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  6. 6

    Class binarization with self-adaptive algorithm to improve human activity recognition by Zainudin, Muhammad Noorazlan Shah

    Published 2018
    “…However, the learning complexity of classification is increased due to the expansion number of learning model. Therefore, feature selection using Relief-f with self-adaptive Differential Evolution (rsaDE) algorithm is proposed to select the most significant features. …”
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  7. 7

    Static image of hand gesture for numerical sign language recognition system using backfrofagation neural network / Erman Ibrahim by Ibrahim, Erman

    Published 2007
    “…To ensure the performance of the system, a number of experiments are done by adjusting the parameters of the BP training algorithm. The result of the experiment shows the percentage of successful recognition. …”
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    Modeling, Testing and Experimental Validation of Laser Machining Micro Quality Response by Artificial Neural Network by Sivarao, Subramonian

    Published 2009
    “…The model was then fed with new sets of machining parameters to experimentally validate the model’s ability in predicting the cut quality. …”
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  10. 10

    Finite Element Modeling Of Ballistic Penetration into Fabric Armor by Talebi, Hossein

    Published 2006
    “…These parameters were friction, boundary conditions, projectile nose diameter and projectile nose angle. …”
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  11. 11

    Obso based fractional pid for mppt-pitch control of wind turbine systems by Mehedi, I.M., Al-Saggaf, U.M., Vellingiri, M.T., Milyani, A.H., Saad, N.B., Yahaya, N.Z.B.

    Published 2022
    “…The OBSO algorithm is derived from the integration of oppositional based learning (OBL) concept with the traditional BSO algorithm in order to improve the convergence rate, which is then applied to effectively choose the parameters involved in the FOPID controller. …”
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    Monitoring and assessment of weld penetration condition during pulse mode laser welding using air-borne acoustic signal by Mohd Fadhlan, Mohd Yusof

    Published 2021
    “…Therefore, this particular work aims to investigate the characteristics of acoustic sound signal from PW Fiber laser, develop an appropriate signal processing algorithm to suppress the effect of noise on the extracted sound features, and develop an empirical model for weld depth estimation. …”
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    Heart sound diagnosis using nonlinear ARX model / Noraishah Shamsuddin by Shamsuddin, Noraishah

    Published 2011
    “…A Lipschitz method and Leven berg Marquardt algorithm is used to determine the model order number and train the network respectively. …”
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  16. 16

    Decoding of visual activity patterns from fMRI responses using multivariate pattern analyses and convolutional neural network by Zafar, R., Kamel, N., Naufal, M., Malik, A.S., Dass, S.C., Ahmad, R.F., Abdullah, J.M., Reza, F.

    Published 2017
    “…MVPA-CNN based proposed algorithm is compared with region of interest (ROI) based method and MVPA based estimated values. …”
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  17. 17

    Improved Malware detection model with Apriori Association rule and particle swarm optimization by Adebayo, Olawale Surajudeen, Abdul Aziz, Normaziah

    Published 2019
    “…These rule models are used together with extraction algorithm to classify and detect malicious android application. …”
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  18. 18

    EEG-Based Person Authentication Modelling Using Incremental Fuzzy-Rough Nearest Neighbour Technique by Liew, Siaw Hong

    Published 2016
    “…Similarly, six feature extraction methods, i.e. Wavelet Packet Decomposition (WPD), mean of amplitude, coherence, crosscorrelation, hjorth parameter and mutual information were used construct the proposed person authentication model. …”
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  19. 19

    Detection of corneal arcus using rubber sheet and machine learning methods by Ramlee, Ridza Azri

    Published 2019
    “…The elements extracted from the confusion matrix parameters (i.e. accuracy, specificity, sensitivity, AUC, precision and f-score) are used in benchmarking the optimal performance of classification algorithms. …”
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  20. 20

    Perturbation stochastic model updating of a bolted structure / Mohamad Azam Shah Aziz Shah by Aziz Shah, Mohamad Azam Shah

    Published 2022
    “…Consequently, (3) FE models of the bolted structure were developed and an appropriate FE model was selected based on the EMA result counterpart. (4) The appropriate FE model was improved using multidimensional analysis by improving the poor correlation of the FE model with EMA, then the appropriate initial value of the high-dimensional uncertain parameters was extracted from the improved model. …”
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