Search Results - (( data application need algorithm ) OR ( parameter optimization system algorithm ))

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  1. 1

    Evaluating Bees Algorithm for Sequence-based T-way Testing Test Data Generation by M. H., Mohamed Zabil, Kamal Z., Zamli, K. C., Lim

    Published 2018
    “…In order to perform t-way testing, software testers need to prepare the test data. For a system with many configuration parameters, the test data could lead to combinatorial explosion problem, since all possible parameter combinations need to be considered. …”
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    Article
  2. 2

    Application of nature-inspired algorithms and artificial intelligence for optimal efficiency of horizontal axis wind turbine / Md. Rasel Sarkar by Md. Rasel, Sarkar

    Published 2019
    “…There is no particular study which focuses on the optimization and prediction of blades parameters using natural inspired algorithms namely Ant Colony Optimization (ACO), Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO) and Adaptive Neuro-fuzzy Interface System (ANFIS) respectively for optimal power coefficient (�436�45D ). …”
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    Thesis
  3. 3

    TBat: A Novel Strategy for Minimization of T-Way Interaction Test Suite Based on the Particle Swarm Optimization and the Bat Algorithm by Kamal Z., Zamli, Alsariera, Yazan A.

    Published 2016
    “…For these reasons, many combinations of possible input parameters, hardware/software environments, and system conditions need to be checked against for conformance based on the system’s specification. …”
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    Conference or Workshop Item
  4. 4

    Mobility management schemes based on multiple criteria for optimization of seamless handover in long term evolution networks by Hussein, Yassein Soubhi

    Published 2014
    “…The tremendous growth of mobile devices and their attendant applications demand for wireless communication networks supporting high data rates with large capacity. …”
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    Thesis
  5. 5

    Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed by Borujeni, Sattar Chavoshi

    Published 2012
    “…Genetic algorithm (GA) was employed to adjust parameters of FES and optimize the system. …”
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  6. 6

    A decision support system for improving forecast using genetic algorithm and tabu search by Ismail, Zuhaimy

    Published 2008
    “…Hence, a good optimization technique is required to select the best parameter value to minimize the fitness function. …”
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    Article
  7. 7

    Fuzzy modelling and control for a nonlinear reboiler system of a distillation column by Ibrahim, Mohd. Faisal

    Published 2006
    “…Manipulated variables for the Fuzzy controller are heat from electrical heater and flowrate of silicon oil in the reboiler system. Genetic algorithm (GA) is used to tune the parameters of the Fuzzy controller. …”
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    FUZZY TOPSIS BASED SOLAR PV DESIGN OPTIMIZATION by Dunkcurn Niem A, Dakeh

    Published 2023
    “…The software design displayed the input and output data of the PV system with Fuzzy TOPSIS algorithm. …”
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    Final Year Project Report / IMRAD
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    Fitting time-varying coefficients SEIRD model to Covid-19 cases in Malaysia by Zulkarnain, Norsyahidah, Abdul Hadi, Muhammad Salihi, Mohammad, Nurul Farahain, Shogar, Ibrahim

    Published 2023
    “…However, this feature leads to an increasing number of unknowns needed to be solved to fit the model with the actual data. Several optimization algorithms under Python’s LMfit package, such as Levenberg-Marquardt, Nelder-Mead, Trust-Region Reflective and Sequential Linear Squares Programming; are employed to estimate the related parameters, in such that the numerical solution of the ODEs will fit the data with the slightest error. …”
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    Water quality monitoring using machine learning and IoT: a review by Hasan, Tahsin Fuad, Kabbashi, Nassereldeen Ahmed, Saleh, Tanveer, Alam, Md. Zahangir, Abd Wahab, Mohd Firdaus, Nour, Abdurahman Hamid

    Published 2024
    “…The paper explores various ML algorithms, including supervised and unsupervised learning and deep learning, along with their applications, and discusses the use of IoT sensors for real-time monitoring of water quality parameters such as pH, dissolved oxygen, temperature, and turbidity.…”
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  14. 14

    Solar irradiance forecasting and energy optimization for achieving nearly net zero energy building by Chakkaravarthy, Naveen, Subathra, M. S. P., Pradeep, P. Jerin, Manoj Kumar, Nallapaneni

    Published 2018
    “…The chosen building was set to the standard parameters in India, and then, the optimization was done with various customized parameters and systems available in India to reduce the energy consumption from 192.2 MMBtu/yr to 109.1 MMBtu/yr with a 7 kW Solar PV System to attain the net-zero energy concept.…”
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    Comprehensive comparison of various machine learning algorithms for short-term ozone concentration prediction by Yafouz A., AlDahoul N., Birima A.H., Ahmed A.N., Sherif M., Sefelnasr A., Allawi M.F., Elshafie A.

    Published 2023
    “…Forecasting; Learning algorithms; Machine learning; Monitoring; Neural networks; Ozone; Public health; Regression analysis; Air quality monitoring; Artificial neural network modeling; Gaussian process regression; Hyper-parameter; Hyper-parameter optimizations; Machine learning models; Ozone concentration; Ozone concentrations predictions; Quality monitoring system; Support vector regressions; Air quality…”
    Article
  18. 18

    Development of cost reduction mathematical model for natural gas transmission network system by Mehrdad, Nikbakht Eliaderany

    Published 2012
    “…In these systems, NG is sent to sales point through pipelines, and Compressor Stations (CSs). …”
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  19. 19

    Secure lightweight client for cloud-based E-Health Model by Zhang, Xiaowei

    Published 2023
    “…This algorithm verifies the identity and permission of non-group members to meet the strict privacy protection requirements of EHRs data. …”
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  20. 20

    Classification of labour pain using electroencephalogram signal based on wavelet method / Sai Chong Yeh by Sai , Chong Yeh

    Published 2020
    “…The training and parameters selection of the machine learning algorithms are conducted using EEG data collected from ten subjects in the laboratory. …”
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