scholarly journals Prediction of the Suspended Transport Rate of River Reach

2020 ◽  
Vol 55 (2) ◽  
Author(s):  
Thair Sharif Khayyun
Keyword(s):  
Relative Error ◽  
Field Measurements ◽  
Transport Rate ◽  
Coefficient Of Determination ◽  
Rate Equations ◽  
Transfer Rates ◽  
Upstream Direction ◽  
River Reach ◽  
New Equation ◽  
Discrepancy Ratio

A new suspended transport rate equation using field measurements that apply to the Euphrates River’s reach in the upstream direction from the Ramadi barrage in Iraq was developed via multiple linear regression. The governing parameters were carefully chosen based on dimensional analysis and grouped into four parameters: shields, transport, mobility, and particles. The ability of the suspended transport rate equations of Karim-Kennedy and van Rijn were tested. A total of 25 series of field data for which the concentration of suspended load, average flow depth, sediment particle size, flow velocity, and the width of the water surface were applied. A comparison of the suspended transfer rates in the river reach and the calculated transport rates in the modified equation showed good coincidence. The evaluation results showed that the new equation performed better than the three equations used. The performance of the new equation was determined utilizing three statistical criteria (the coefficient of determination, discrepancy ratio and relative error). The computed suspended transport rates were found within a discrepancy ratio of 1.02 for the measured values and a relative error of 13.4%. The performance of the Van Rijn formula performed better, with a discrepancy ratio of 1.26 for the measured values and a relative error 39%, than the other two equations. The percentage of data that ranged between 0.5–2.0 of the discrepancy ratio varied between 72–100% for the three equations and the new equation.

scholarly journals Optimization Method for Forecasting Confirmed Cases of COVID-19 in China

2020 ◽  
Vol 9 (3) ◽  
pp. 674 ◽  
Author(s):  
Mohammed A. A. Al-qaness ◽  
Ahmed A. Ewees ◽  
Hong Fan ◽  
Mohamed Abd El Aziz
Keyword(s):  
Relative Error ◽  
Computing Time ◽  
World Health ◽  
Coefficient Of Determination ◽  
Flower Pollination Algorithm ◽  
Percentage Error ◽  
Anfis Model ◽  
Local Optima ◽  
Inference System ◽  
Proposed Model

In December 2019, a novel coronavirus, called COVID-19, was discovered in Wuhan, China, and has spread to different cities in China as well as to 24 other countries. The number of confirmed cases is increasing daily and reached 34,598 on 8 February 2020. In the current study, we present a new forecasting model to estimate and forecast the number of confirmed cases of COVID-19 in the upcoming ten days based on the previously confirmed cases recorded in China. The proposed model is an improved adaptive neuro-fuzzy inference system (ANFIS) using an enhanced flower pollination algorithm (FPA) by using the salp swarm algorithm (SSA). In general, SSA is employed to improve FPA to avoid its drawbacks (i.e., getting trapped at the local optima). The main idea of the proposed model, called FPASSA-ANFIS, is to improve the performance of ANFIS by determining the parameters of ANFIS using FPASSA. The FPASSA-ANFIS model is evaluated using the World Health Organization (WHO) official data of the outbreak of the COVID-19 to forecast the confirmed cases of the upcoming ten days. More so, the FPASSA-ANFIS model is compared to several existing models, and it showed better performance in terms of Mean Absolute Percentage Error (MAPE), Root Mean Squared Relative Error (RMSRE), Root Mean Squared Relative Error (RMSRE), coefficient of determination ( R 2 ), and computing time. Furthermore, we tested the proposed model using two different datasets of weekly influenza confirmed cases in two countries, namely the USA and China. The outcomes also showed good performances.

BP Neural Network Based Animation Production Prediction

2014 ◽  
Vol 539 ◽  
pp. 475-478
Author(s):  
Ran Tao ◽  
Da Chao Yuan ◽  
Gang Yi Hu
Keyword(s):  
Neural Network ◽  
Relative Error ◽  
Bp Neural Network ◽  
Prediction Method ◽  
Coefficient Of Determination ◽  
Mean Relative Error ◽  
Training Samples ◽  
The Mean ◽  
Production Prediction

In order to research the basic condition of animation production, this article chooses BP Neural Network to predict the animation production. We select 13 test samples, selected nine of them randomly as training samples, and the remaining four as the test samples. The coefficient of determination is 0.99839 and the mean relative error is 0.186125. The result shows that BP Neural Network is an effective prediction method.

scholarly journals MODEL TESTS ON LITTORAL SAND TRANSPORT RATE

1982 ◽  
Vol 1 (18) ◽  
pp. 80
Author(s):  
J.W. Kamphuis ◽  
O.F.S.J. Sayao
Keyword(s):  
Energy Dissipation ◽  
Wave Energy ◽  
Dissipation Rate ◽  
Field Measurements ◽  
Energy Dissipation Rate ◽  
Transport Rate ◽  
Sand Transport ◽  
Similarity Parameter ◽  
Wave Energy Dissipation ◽  
Mobile Bed

This paper is an analysis of two sets of experimental results on littoral sand transport. A littoral sand transport expression is proposed, relating littoral transport rate to surf similarity parameter and hence to wave energy dissipation rate. The expression indicates that the "constant' in the CERC formula is dependent on the mobile bed beach slope and on the breaker index. The expression is also compared with some of the few published field measurements.

scholarly journals Estimación de la evapotranspiración real en zonas de llanura mediante productos de humedad de suelo de la misión SMAP

2018 ◽  
pp. 17
Author(s):  
E. Walker ◽  
G. A. García ◽  
V. Venturini
Keyword(s):  
Great Plains ◽  
Land Surface ◽  
Water Cycle ◽  
Coefficient Of Determination ◽  
Southern Great Plains ◽  
Passive Sensors ◽  
New Equation ◽  
Humid Period ◽  
Pampas Region

<p>Evapotranspiration (ET) is an important process in the water cycle and in the land-surface energy balance. Over the last decades, remote sensing has provided valuable information to quantify ET. However, methodologies that use data from microwave passive sensors, such as “Soil Moisture Active Passive” (SMAP) mission, have been recently developed. In this work, a formulation to derive the relative evapotranspiration and ET from <em>in situ</em> and microwave data, is presented. The methodology is based on a modification of the original Komatsu (2003) equation by introducing a calibration parameter to represent the wind speed and vegetation effects and estimate the relative evapotranspiration. This new equation was used on the Bouchet’s complementary relationship with the Priestley-Taylor’s equation, to estimate ET at regional scales. The results were compared with observed data in the Southern Great Plains – USA (SGP) area, indicating that the new model estimated ET with a root mean square error (RMSE) of 0.88 mmd<sup>–1</sup> and a coefficient of determination (R<sup>2</sup> ) greater than 0.8. The calibrated model was applied in an extremely humid period in Argentinean Pampas region with results near to potential rates.</p>

scholarly journals LONGSHORE TRANSPORT OF SAND

1968 ◽  
Vol 1 (11) ◽  
pp. 18 ◽  
Author(s):  
Douglas L. Inman ◽  
Paul D. Komar ◽  
Anthony J. Bowen
Keyword(s):  
Energy Flux ◽  
Surf Zone ◽  
Field Measurements ◽  
Breaking Waves ◽  
Transport Rate ◽  
Wave Power ◽  
Longshore Transport ◽  
Wave Conditions

Simultaneous field measurements of the energy flux of breaking waves and the resulting longshore transport of sand in the surf zone have been made along three beaches and for a variety of wave conditions. The measurements indicate that the longshore transport rate of sand is directly proportional to the longshore component of wave power.

scholarly journals Measurements and Analysis of Primary Ship Waves in the Stockholm Archipelago, Sweden

2020 ◽  
Vol 8 (10) ◽  
pp. 743
Author(s):  
Björn Almström ◽  
Magnus Larson
Keyword(s):  
Large Data ◽  
Field Measurements ◽  
Physical Processes ◽  
Data Set ◽  
Ship Waves ◽  
Stockholm Archipelago ◽  
New Equation ◽  
Water Level Measurements ◽  
Marine Vessels ◽  
Better Than

Primary ship waves generated by conventional marine vessels were investigated in the Furusund fairway located in the Stockholm archipelago, Sweden. Continuous water level measurements at two locations in the fairway were analyzed. In total, 466 such events were extracted during two months of measurements. The collected data were used to evaluate 13 existing predictive equations for drawdown height or squat. However, none of the equations were able to satisfactorily predict the drawdown height. Instead, a new equation for drawdown height and period was derived based on simplified descriptions of the main physical processes together with field measurements, employing multiple regression analysis to derive coefficients in the equation. The proposed equation for drawdown height performed better than the existing equations with an R2 value of 0.65, whereas the equation for the drawdown period was R2 = 0.64. The main conclusion from this study is that an empirical equation can satisfactorily predict primary ship waves for a large data set.

scholarly journals Implementation and evaluation of prognostic representations of the optical diameter of snow in the SURFEX/ISBA-Crocus detailed snowpack model

2014 ◽  
Vol 8 (2) ◽  
pp. 417-437 ◽  
Author(s):  
C. M. Carmagnola ◽  
S. Morin ◽  
M. Lafaysse ◽  
F. Domine ◽  
B. Lesaffre ◽  
...  
Keyword(s):  
Snow Water Equivalent ◽  
Quantitative Description ◽  
Field Measurements ◽  
Rate Of Change ◽  
Rate Equations ◽  
Snow Properties ◽  
Snow Water ◽  
New Formulation ◽  
Snow Microstructure ◽  
The Impact

Abstract. In the SURFEX/ISBA-Crocus multi-layer snowpack model, the snow microstructure has up to now been characterised by the grain size and by semi-empirical shape variables which cannot be measured easily in the field or linked to other relevant snow properties. In this work we introduce a new formulation of snow metamorphism directly based on equations describing the rate of change of the optical diameter (dopt). This variable is considered here to be equal to the equivalent sphere optical diameter, which is inversely proportional to the specific surface area (SSA). dopt thus represents quantitatively some of the geometric characteristics of a porous medium. Different prognostic rate equations of dopt, including a re-formulation of the original Crocus scheme and the parameterisations from Taillandier et al. (2007) and Flanner and Zender (2006), were evaluated by comparing their predictions to field measurements carried out at Summit Camp (Greenland) in May and June 2011 and at Col de Porte (French Alps) during the 2009/10 and 2011/12 winter seasons. We focused especially on results in terms of SSA. In addition, we tested the impact of the different formulations on the simulated density profile, the total snow height, the snow water equivalent (SWE) and the surface albedo. Results indicate that all formulations perform well, with median values of the RMSD between measured and simulated SSA lower than 10 m2 kg−1. Incorporating the optical diameter as a fully fledged prognostic variable is an important step forward in the quantitative description of the snow microstructure within snowpack models, because it opens the way to data assimilation of various electromagnetic observations.

scholarly journals Constitutive Equations for Describing the Warm and Hot Deformation Behavior of 20Cr2Ni4A Alloy Steel

Metals ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. 1169
Author(s):  
Haoran Wang ◽  
Wei Wang ◽  
Ruixue Zhai ◽  
Rui Ma ◽  
Jun Zhao ◽  
...  
Keyword(s):  
Flow Stress ◽  
Alloy Steel ◽  
Relative Error ◽  
Constitutive Equations ◽  
Type Equation ◽  
Coefficient Of Determination ◽  
Original Strain ◽  
Compression Tests ◽  
Absolute Relative Error ◽  
Average Absolute Relative Error

Isothermal hot compression tests of 20Cr2Ni4A alloy steel were performed under temperatures of 973–1273 K and strain rates of 0.001–1 s−1. The behavior of the flow stress of 20Cr2Ni4A alloy steel at warm and hot temperatures is complicated because of the influence of the work hardening, the dynamic recovery, and the dynamic recrystallization. Four constitutive equations were used to predict the flow stress of 20Cr2Ni4A alloy steel, including the original strain-compensated Arrhenius-type (osA-type) equation, the new modified strain-compensated Arrhenius-type (msA-type) equation, the original Hensel–Spittel (oHS) equation and the modified Hensel–Spittel (mHS) equation. The msA-type and mHS are developed by revising the deformation temperatures, which can improve prediction accuracy. In addition, we propose a new method of solving the parameters by combining a linear search with multiple linear regression. The new solving method is used to establish the two modified constitutive equations instead of the traditional regression analysis. A comparison of the predicted values based on the four constitutive equations was performed via relative error, average absolute relative error (AARE) and the coefficient of determination (R2). These results show the msA-type and mHS equations are more accurate and efficient in terms of predicting the flow stress of the 20Cr2Ni4A steel at elevated temperature.

Sign in / Sign up

Export Citation Format

Share Document