Drought Forecasting Using MLP Neural Networks

机译：利用MLP神经网络进行干旱预报

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For the past decades, drought has affected the natural environment of large areas of Peninsular Malaysia and drought monitoring and identification play an important role in the planning and management of natural resources and water resource systems in the country. Standardized precipitation index (SPI) has been used as a conventional tool to identify and monitor drought occurrences. However, to reduce and mitigate the adverse effects of drought impacts, effective forecasting of future droughts is necessary. In this paper, average long term monthly rainfall data for eight stations covering both the dry and wet seasons from Selangor river basin in Malaysia have been used to derive the SPI values for durations of 3 to 9 months. These drought indicators were used as time series for drought forecasting for the basin using the multi-layer artificial neural networks model. Results show that more accurate predictions are achieved using SPI of longer durations, i.e. 6 and 9 months.

机译：在过去的几十年中，干旱影响了马来西亚半岛大片地区的自然环境，干旱监测和识别在该国自然资源和水资源系统的规划和管理中发挥着重要作用。标准化降水指数（SPI）已被用作识别和监测干旱情况的常规工具。但是，为了减少和减轻干旱影响的不利影响，必须对未来的干旱进行有效的预测。在本文中，已使用马来西亚雪兰莪河流域八个干旱和潮湿季节的八个站点的平均长期每月降雨数据得出了持续时间为3到9个月的SPI值。这些干旱指标被用作使用多层人工神经网络模型进行流域干旱预报的时间序列。结果表明，使用较长持续时间（即6和9个月）的SPI可以实现更准确的预测。

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《2015 8th International Conference on u- and e-Service, Science and Technology》|2015年|62-65|共4页
会议地点 Jeju Island(KR)
作者
Daniel Hong; Kee An Hong;
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原文格式 PDF
正文语种 eng
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关键词
Drought forecasting; Neural Network;

机译：干旱预报；神经网络;

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1. Forecasting Different Types of Droughts Simultaneously Using Multivariate Standardized Precipitation Index (MSPI), MLP Neural Network, and Imperialistic Competitive Algorithm (ICA) [J] . Pouya Aghelpour, Vahid Varshavian Complexity . 2021,第a期

机译：使用多元标准化降水指数（MSPI），MLP神经网络和帝国竞争算法（ICA）同时预测不同类型的干旱
2. Drought Forecasting Using Neural Networks, Wavelet Neural Networks, and Stochastic Models: Case of the Algerois Basin in North Algeria [J] . Djerbouai Salim, Souag-Gamane Doudja Water Resources Management . 2016,第7期

机译：使用神经网络，小波神经网络和随机模型进行干旱预测：以北阿尔及利亚的阿尔及尔盆地为例
3. Standard Precipitation Index Drought Forecasting Using Neural Networks, Wavelet Neural Networks, and Support Vector Regression [J] . A.Belayneh, J.Adamowski Applied computational intelligence and soft computing . 2012,第8期

机译：使用神经网络，小波神经网络和支持向量回归的标准降水指数干旱预报
4. Drought Forecasting Using MLP Neural Networks [C] . Daniel Hong, Kee An Hong International Conference on u- and e-Service, Science and Technology . 2015

机译：使用MLP神经网络的干旱预测
5. Developing an accurate forecasting model for temporal and spatial ambulance demand via artificial neural networks: A comparative study of existing forecasting techniques vs. an artificial neural network. [D] . Setzler, Hubert Holland, III. 2007

机译：通过人工神经网络为时空救护车需求开发准确的预测模型：现有预测技术与人工神经网络的比较研究。
6. Forecasting SPEI and SPI Drought Indices Using the Integrated Artificial Neural Networks [O] . Petr Maca, Pavel Pech 2016

机译：使用集成人工神经网络预测SPEI和SPI干旱指数
7. Forecasting Different Types of Droughts Simultaneously Using Multivariate Standardized Precipitation Index (MSPI), MLP Neural Network, and Imperialistic Competitive Algorithm (ICA) [O] . Pouya Aghelpour, Vahid Varshavian 2021

机译：使用多元标准化降水指数（MSPI），MLP神经网络和帝国竞争算法（ICA）同时预测不同类型的干旱
8. Automatic Target Recognition in SAR Imagery Using a MLP Neural Network [R] . Sandirasegaram, N. M. 2002

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Drought Forecasting Using MLP Neural Networks

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