Search Results - (( rainfall distribution new algorithm ) OR ( parameters estimation graph algorithm ))

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    Effect of LiDAR mounting parameters and speed on HDL graph SLAM-Based 3D mapping for autonomous vehicles by Law, Jia Seng, Muhammad Aizzat, Zakaria, Younus, Maryam, Yong, Ericsson, Ismayuzri, Ishak, Mohamad Heerwan, Peeie, Muhammad Izhar, Ishak

    Published 2025
    “…This study investigates the physical calibration of a LiDAR sensor mounted on a moving vehicle and its effect on 3D map generation using the HDL Graph SLAM algorithm. HDL Graph SLAM was selected as the offline post-processing method due to its self-correcting functions for estimating and auto-correcting positional errors from LiDAR data. …”
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    The use of radar-rainfall inputs for quantitative precipitation estimation (QPE) in Klang River Basin / Suzana Ramli by Ramli, Suzana

    Published 2015
    “…Flooding is a natural disaster that often occurs in Malaysia due to its heavy rainfall distribution. Lately, the exceptional amount of rainfall worsens the flood situation. …”
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    Mixture model of the Exponential, Gamma and Weibull distributions to analyse heterogeneous survival data by Mohammed, Yusuf Abbakar, Yatim, Bidin, Ismail, Suzilah

    Published 2015
    “…Aims: In this study a survival mixture model of three components is considered to analyse survival data of heterogeneous nature.The survival mixture model is of the Exponential, Gamma and Weibull distributions.Methodology: The proposed model was investigated and the Maximum Likelihood (ML) estimators of the parameters of the model were evaluated by the application of the Expectation Maximization Algorithm (EM).Graphs, log likelihood (LL) and the Akaike Information Criterion (AIC) were used to compare the proposed model with the pure classical parametric survival models corresponding to each component using real survival data.The model was compared with the survival mixture models corresponding to each component.Results: The graphs, LL and AIC values showed that the proposed model fits the real data better than the pure classical survival models corresponding to each component.Also the proposed model fits the real data better than the survival mixture models corresponding to each component. …”
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    Machine learning for mapping and forecasting poverty in North Sumatera: a datadriven approach by Marpaung, Faridawaty, Ramadhani, Fanny, Dinata, Dewan

    Published 2024
    “…The best model was created using the grid search cross-validation, while the best prediction results were created using the RF algorithm, with the following parameters: n-estimator = 50, max depth = 10, min samples split = 2, and min samples leaf = 1. …”
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    Comparison between specifications of linear regression and spatial-temporal autoregressive models in mass appraisal valuation for single storey residential property by Jahanshiri, Ebrahim

    Published 2013
    “…Effects such as normality treatment, definition of neighbourhoods and weights and choice of autocorrelation parameter and parameter estimation are some of the complexities that are inherent to these models. …”
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    An impulsive noise analyser using amplitude probability distribution (APD) for broadband-wired communication by Zainal Abidin, Ahmadun Nijar

    Published 2011
    “…The noises are characterised using α-stable distribution which exhibits its own distinct APD parameters. The APD curve can be related with the single modulation scheme communication channel performance for estimation of bit error probability. …”
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    Climate change impact on hydrological, sediment, and nutrient in Langat River basin: an assessment using integrated model / Nor Faiza Abd Rahman by Abd Rahman, Nor Faiza

    Published 2019
    “…The results of the study also suggested that an automatic weather generator can simplify the preparation of weather data from six months to one month. A new automated weather generator input model for rainfall-runoff simulation (SWAT model) has been successfully developed to close the gap by integrating NCO, netCDF, Grads and CDO in a MATLAB environment. …”
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