scholarly journals Comparative Investigations of Tidal Current Velocity Prediction Considering Effect of Multi-Layer Current Velocity

Energies ◽  
2020 ◽  
Vol 13 (23) ◽  
pp. 6417
Author(s):  
Bo Feng ◽  
Peng Qian ◽  
Yulin Si ◽  
Xiaodong Liu ◽  
Haixiao Yang ◽  
...  

Accurate tidal current prediction plays a critical role with increasing utilization of tidal energy. The classical prediction approach of the tidal current velocity adopts the harmonic analysis (HA) method. The performance of the HA approach is not ideal to predict the high frequency components of tidal currents due to the lack of capability processing the non-astronomic factor. Recently, machine learning algorithms have been applied to process the non-astronomic factor in the prediction of tidal current. In this paper, a tidal current velocity prediction considering the effect of the multi-layer current velocity method is proposed. The proposed method adopts three machine learning algorithms to establish the prediction models for comparative investigations, namely long-short term memory (LSTM), back-propagation (BP) neural network, and the Elman regression network. In the case study, the tidal current data collected from the real ocean environment were used to validate the proposed method. The results show that the proposed method combined with the LSTM algorithm had higher accuracy than both the commercial tidal prediction tool (UTide) and the other two algorithms. This paper presents a novel tidal current velocity prediction considering the effect of the multi-layer current velocity method, which improves the accuracy of the power flow prediction and contributes to the research in the field of tidal current velocity prediction and the capture of tidal energy.

Author(s):  
Agus Margiantono ◽  
Titik Nurhayati ◽  
Wahib Hasbullah

In some places in the village of Bedono Demak Regency there is a location with high tidal current velocity, the coordinates of the Location is 6 ° 55'29.0 "S 110 ° 29'11.4" E. In this study estimated the amount of electric power that can be generated from tidal currents in the village Bedono. Estimates are made by modeling the location and the Darrieus turbine using the CFD (Computating Fluid Dinamyc) Software. From the research that has been done to get the results of electric power that can be produced in the village Bedono highest at 14-16 times 3469.413W and lowest 39.002W at 22-24 hours according to the CFD is the highest active power occurred at 14-16 at 3197.064W and the lowest 35.941W at 22-24 hours.


2020 ◽  
Vol 104 ◽  
pp. 102346 ◽  
Author(s):  
J. Tondut ◽  
T. El Tawil ◽  
J. Thiébot ◽  
N. Guillou ◽  
M. Benaouicha

2019 ◽  
Vol 7 (2) ◽  
pp. 46 ◽  
Author(s):  
Tony El Tawil ◽  
Nicolas Guillou ◽  
Jean-Frédéric Charpentier ◽  
Mohamed Benbouzid

Estimating the energy potential of tidal stream site is a key feature for tidal energy system deployment. This paper aims to compare two methods of prediction of tidal current velocities. The first one is based on the use of a fully three-dimensional (3D) numerical approach. However, while being accurate, the numerical model is highly time-consuming. The second method is based on a linear approximation of the tidal current, which only requires preliminary knowledge of local current velocities time series during two typical tidal cycles. This second method allows a very quick evaluation of the tidal stream resource during a long time period. The proposed comparison is done in three different locations of a high potential tidal energy site in west of France. It is carried out in terms of current velocity and energy harnessing for several turbines technology options (with and without yaw). The achieved results show that the linear approximation gives satisfactory evaluation of the tidal stream potential and can be a very interesting tool for preliminary site evaluation and first technology options selection. However, the fully 3D numerical model can obviously be very useful in more advanced steps of a project.


2020 ◽  
Vol 39 (5) ◽  
pp. 6579-6590
Author(s):  
Sandy Çağlıyor ◽  
Başar Öztayşi ◽  
Selime Sezgin

The motion picture industry is one of the largest industries worldwide and has significant importance in the global economy. Considering the high stakes and high risks in the industry, forecast models and decision support systems are gaining importance. Several attempts have been made to estimate the theatrical performance of a movie before or at the early stages of its release. Nevertheless, these models are mostly used for predicting domestic performances and the industry still struggles to predict box office performances in overseas markets. In this study, the aim is to design a forecast model using different machine learning algorithms to estimate the theatrical success of US movies in Turkey. From various sources, a dataset of 1559 movies is constructed. Firstly, independent variables are grouped as pre-release, distributor type, and international distribution based on their characteristic. The number of attendances is discretized into three classes. Four popular machine learning algorithms, artificial neural networks, decision tree regression and gradient boosting tree and random forest are employed, and the impact of each group is observed by compared by the performance models. Then the number of target classes is increased into five and eight and results are compared with the previously developed models in the literature.


2020 ◽  
pp. 1-11
Author(s):  
Jie Liu ◽  
Lin Lin ◽  
Xiufang Liang

The online English teaching system has certain requirements for the intelligent scoring system, and the most difficult stage of intelligent scoring in the English test is to score the English composition through the intelligent model. In order to improve the intelligence of English composition scoring, based on machine learning algorithms, this study combines intelligent image recognition technology to improve machine learning algorithms, and proposes an improved MSER-based character candidate region extraction algorithm and a convolutional neural network-based pseudo-character region filtering algorithm. In addition, in order to verify whether the algorithm model proposed in this paper meets the requirements of the group text, that is, to verify the feasibility of the algorithm, the performance of the model proposed in this study is analyzed through design experiments. Moreover, the basic conditions for composition scoring are input into the model as a constraint model. The research results show that the algorithm proposed in this paper has a certain practical effect, and it can be applied to the English assessment system and the online assessment system of the homework evaluation system algorithm system.


2019 ◽  
Vol 1 (2) ◽  
pp. 78-80
Author(s):  
Eric Holloway

Detecting some patterns is a simple task for humans, but nearly impossible for current machine learning algorithms.  Here, the "checkerboard" pattern is examined, where human prediction nears 100% and machine prediction drops significantly below 50%.


Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 1290-P
Author(s):  
GIUSEPPE D’ANNUNZIO ◽  
ROBERTO BIASSONI ◽  
MARGHERITA SQUILLARIO ◽  
ELISABETTA UGOLOTTI ◽  
ANNALISA BARLA ◽  
...  

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