An Intelligent Early Flood Forecasting and Prediction Leveraging Machine and Deep Learning Algorithms with Advanced Alert System

نویسندگان

چکیده

Flood disasters are a natural occurrence around the world, resulting in numerous casualties. It is vital to develop an accurate flood forecasting and prediction model order curb damages limit number of victims. Water resource allocation, management, planning, warning forecasting, damage mitigation all benefit from rain forecasting. Prior recent decades’ worth research, this domain demonstrated be promising prospects time series tasks. Therefore, main aim study build based on exponential smoothing-long-short term memory (ES-LSTM) structure recurrent neural networks (RNNs) for predicting hourly precipitation seasons; classify using artificial network (ANN) decision tree (DT) algorithm. We employ dataset Australian commonwealth office meteorology named Historical Daily Weather test effectiveness proposed model. The findings showed that ES-LSTM RNN had achieved 3.17 6.42 terms mean absolute percentage error (MAPE), respectively. Meanwhile, ANN DT models obtained accuracy rate 96.65% 84.0%, Finally, outcomes revealed best results compared other models.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

An Advanced Press Review System Combining Deep News Analysis and Machine Learning Algorithms

In our media-driven world the perception of companies and institutions in the media is of major importance. The creation of press reviews analyzing the media response to company-related events is a complex and time-consuming task. In this demo we present a system that combines advanced text mining and machine learning approaches in an extensible press review system. The system collects document...

متن کامل

development and implementation of an optimized control strategy for induction machine in an electric vehicle

in the area of automotive engineering there is a tendency to more electrification of power train. in this work control of an induction machine for the application of electric vehicle is investigated. through the changing operating point of the machine, adapting the rotor magnetization current seems to be useful to increase the machines efficiency. in the literature there are many approaches wh...

15 صفحه اول

assessment of deep word knowledge in elementary and advanced iranian efl learners: a comparison of selective and productive wat tasks

testing plays a vital role in any language teaching program. it allows teachers and stakeholders, including program administrators, parents, admissions officers and prospective employers to be assured that the learners are progressing according to an accepted standard (douglas, 2010). the problems currently facing language testers have both practical and theoretical implications but the first i...

Modeling and forecasting US presidential election using learning algorithms

The primary objective of this research is to obtain an accurate forecasting model for the US presidential election. To identify a reliable model, artificial neural networks (ANN) and support vector regression (SVR) models are compared based on some specified performance measures. Moreover, six independent variables such as GDP, unemployment rate, the president’s approval rate, and others are co...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Processes

سال: 2023

ISSN: ['2227-9717']

DOI: https://doi.org/10.3390/pr11020481