Short-Term Tide Prediction
نویسندگان
چکیده
Ever since the first fishermen ventured into the sea, tides have been the subject of intense human observation. As a result computational models and ‘tide predicting machines’, mechanical computers for predicting tides have been developed over 100 years ago. In this work we propose a statistical model for short-term prediction of sea levels at high tide in the tide influenced part of the Weser at Vegesack. The predictions are made based on water level measurements taken at different locations downriver and in the German Bight. The system has been integrated tightly into the decision making process at the Bremen Dike Association on the Right Bank of the Weser.
منابع مشابه
Tidal prediction using time series analysis of Buoy observations
Although tidal observations which are extracted from coastal tide gages, have higher accuracy due to their higher sampling rate, installing these types of gages can impose some spatial limitation since we cannot use every part of sea to install them. To solve this limitation, we can employ satellite altimetry observations. However, satellite altimetry observations have lower sampling rate. Acco...
متن کاملShort term electric load prediction based on deep neural network and wavelet transform and input selection
Electricity demand forecasting is one of the most important factors in the planning, design, and operation of competitive electrical systems. However, most of the load forecasting methods are not accurate. Therefore, in order to increase the accuracy of the short-term electrical load forecast, this paper proposes a hybrid method for predicting electric load based on a deep neural network with a...
متن کاملShort Term Load Forecasting Using Empirical Mode Decomposition, Wavelet Transform and Support Vector Regression
The Short-term forecasting of electric load plays an important role in designing and operation of power systems. Due to the nature of the short-term electric load time series (nonlinear, non-constant, and non-seasonal), accurate prediction of the load is very challenging. In this article, a method for short-term daily and hourly load forecasting is proposed. In this method, in the first step, t...
متن کاملPrediction of Covid-19 Prevalence and Fatality Rates in Iran Using Long Short-Term Memory Neural Network
Introduction: The rapid spread of COVID-19 has become a critical threat to the world. So far, millions of people worldwide have been infected with the disease. The Covid-19 pandemic has had significant effects on various aspects of human life. Currently, prediction of the virus's spread is essential in order to be safe and make necessary arrangements. It can help control the rate of its outbrea...
متن کاملPrediction of Covid-19 Prevalence and Fatality Rates in Iran Using Long Short-Term Memory Neural Network
Introduction: The rapid spread of COVID-19 has become a critical threat to the world. So far, millions of people worldwide have been infected with the disease. The Covid-19 pandemic has had significant effects on various aspects of human life. Currently, prediction of the virus's spread is essential in order to be safe and make necessary arrangements. It can help control the rate of its outbrea...
متن کامل