Search Results - (( rainfall distribution from algorithm ) OR ( peer evaluation drops algorithm ))

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    Meta-heuristic approaches for reservoir optimisation operation and investigation of climate change impact at Klang gate dam by Lai, Vivien Mei Yen

    Published 2023
    “…Consequently, seeking managing of reservoir optimisation operations had always been at the forefront and to improve managing, algorithms have had been presented over the past few decades, beginning with conventional algorithms, followed by heuristic algorithms, and finally, the meta-heuristic algorithms (MHAs). …”
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    Final Year Project / Dissertation / Thesis
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    TRMM Satellite Algorithm Estimates to Represent the Spatial Distribution of Rainstorms by Marina, Patrick, Mah, Yau Seng, Putuhena, Frederik Josep, Wang, Yin Chai, Onni Suhaiza, Selaman

    Published 2016
    “…These findings suggest that satellite algorithm estimations from TRMM are suitable to represent the spatial distribution of extreme rainfall.…”
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    Article
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    Investigating the relationship between the urban heat island effect and short-duration extreme rainfall in Kuala Lumpur by Tan, Yan Kai

    Published 2025
    “…Hourly rainfall data exceeding the 99th percentile from 2007 to 2023 were used to assess spatiotemporal variation, diurnal distribution and trends. …”
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    Final Year Project / Dissertation / Thesis
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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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    Thesis
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    A Comparative Study of Z-Score and Min-Max Normalization for Rainfall Classification in Pekanbaru by Rahmad Ramadhan, Laska, Anne Mudya, Yolanda

    Published 2024
    “…This study focuses on normalizing rainfall data in Pekanbaru from 2019 to 2023. The objective is to compare various data normalization techniques, including Min-Max Normalization and Z-Score Normalization. …”
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    Article
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    Determination of dengue hemorrhagic fever disease factors using neural network and genetic algorithms / Yuliant Sibaroni, Sri Suryani Prasetiyowati and Iqbal Bahari Sudrajat by Yuliant, Sibaroni, Sri Suryani, Prasetiyowati, Iqbal Bahari, Sudrajat

    Published 2020
    “…Based on the initial study conducted, there are 6 factors that have the potential to influence the number of DHF cases in an area, namely temperature (X1), rainfall (X2), population density (X3), altitude (X4), distribution of males (X5), and distribution of education level (X6). …”
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    Article
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