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Titlebook: Intelligent Data Analytics for Decision-Support Systems in Hazard Mitigation; Theory and Practice Ravinesh C. Deo,Pijush Samui,Zaher Mundh

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楼主: Hoover
发表于 2025-3-25 05:15:53 | 显示全部楼层
Hydrological Drought Investigation Using Streamflow Drought Index, of severe and extreme drought or wet events were unlikely in both stations, except SDI-24 (extreme drought) at Kedar station. The chances of occurrence for moderate drought and wet conditions were relatively more frequent in both stations. Hence, the efforts must be made to harvest the excess water
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,Modulation of Tropical Cyclone Genesis by Madden–Julian Oscillation in the Southern Hemisphere,ly identified. Overall, an increase in the number of TC formations was recorded for the enhanced convective phase of the MJO compared to the dry phase. The modulation of TC genesis by MJO appeared to be pronounced with a ratio of 2:1 to the east of 70° E (for the SIO) and 7:1 to the west of 170° W (
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Intelligent Data Analytics for Time Series, Trend Analysis and Drought Indices Comparison,is able to detect changes in the SPEI trend with associated confidence levels and confidence intervals. The study found the location R4 (in arid/semi-arid region) to have undergone 26 changes in SPEI trend compared to R1, R2 and R3 with 0, 9 and 6, respectively. The location of study matters where i
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Conjunction Model Design for Intermittent Streamflow Forecasts: Extreme Learning Machine with Discrl with five previous flow values as inputs provided the best accuracy compared to other corresponding models. DWT considerably increased the accuracy of single models in forecasting intermittent streamflow of both stations. The RMSE of the best ELM and ANN models were decreased by 38 (61)% and 59 (6
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Morphological Changes of Floodplain Reach of Jhelum River, India, from 1984 to 2018,and persisted up to 2010, then started decreasing up to 2018. Similarly, a shift of 100 m was observed in segment . towards the end of the observation period. The maximum change in sinuosity index occurred in the segments ., ., . and . and the minimum change in sinuosity has been observed in segment
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Artificial Neural Networks for Prediction of Steadman Heat Index,termination, the Willmott’s Index of Agreement, and Nash–Sutcliffe Coefficient of Efficiency. The designed model appears to be a suitable intelligent data analytic tool for weather prediction, climate change studies, and probable evaluation of dry climatic conditions in the near future replying to h
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