Investigation on modeling of non-buoyant body typed point absorbing wave energy converter using Adaptive Network-based Fuzzy Inference System

Amarkarthik, Arunachalam; Sivakumar, K.

doi:10.1016/j.ijome.2016.01.004

Cited by 6 publications

(4 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Find the resubstitution OLS residuals using ( 15) and the standard error estimateσ 2 e using ( 17), where n = 126 9. Calculate the [p × p]-dimensional covariance matrix of the model parameters by plugging (26) in (18):…”

Section: Diagnostics Of the Linearity Assumptionmentioning

confidence: 99%

“…For example, a powerful bootstrap heteroscedasticity test based on the difference between (45) and ( 18) is proposed in [52]. In [53], several general information matrix tests for model misspecification in regression models are proposed, based on the difference of the two matrix estimates (18) and (45).…”

Section: Diagnostics Of the Homoscedasticity Assumptionmentioning

confidence: 99%

“…The grey box methods are not very popular for the OWC design. The only emerging exception is a method based on the adaptive neuro-fuzzy inference system (ANFIS) which have been applied to different types of WEC devices [18,19]. It combines a multilayer artificial neural network (ANN) with fuzzy logic.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Regression Diagnostics with Predicted Residuals of Linear Model with Improved Singular Value Classification Applied to Forecast the Hydrodynamic Efficiency of Wave Energy Converters

Tenekedjiev

Abdussamie

et al. 2021

Applied Sciences

View full text Add to dashboard Cite

In the preliminary stages of design of the oscillating water column (OWC) type of wave energy converters (WECs), we need a reliable cost- and time-effective method to predict the hydrodynamic efficiency as a function of the design parameters. One of the cheapest approaches is to create a multiple linear regression (MLR) model using an existing data set. The problem with this approach is that the reliability of the MLR predictions depend on the validity of the regression assumptions, which are either rarely tested or tested using sub-optimal procedures. We offer a series of novel methods for assumption diagnostics that we apply in our case study for MLR prediction of the hydrodynamics efficiency of OWC WECs. Namely, we propose: a novel procedure for reliable identification of the zero singular values of a matrix; a modified algorithm for stepwise regression; a modified algorithm to detect heteroskedasticity and identify statistically significant but practically insignificant heteroscedasticity in the original model; a novel test of the validity of the nullity assumption; a modified Jarque–Bera Monte Carlo error normality test. In our case study, the deviations from the assumptions of the classical normal linear regression model were fully diagnosed and dealt with. The newly proposed algorithms based on improved singular value decomposition (SVD) of the design matrix and on predicted residuals were successfully tested with a new family of goodness-of-fit measures. We empirically investigated the correct placement of an elaborate outlier detection procedure in the overall diagnostic sequence. As a result, we constructed a reliable MLR model to predict the hydrodynamic efficiency in the preliminary stages of design. MLR is a useful tool at the preliminary stages of design and can produce highly reliable and time-effective predictions of the OWC WEC performance provided that the constructing and diagnostic procedures are modified to reflect the latest advances in statistics. The main advantage of MLR models compared to other modern black box models is that their assumptions are known and can be tested in practice, which increases the reliability of the model predictions.

show abstract

Section: Diagnostics Of the Linearity Assumptionmentioning

confidence: 99%

Section: Diagnostics Of the Homoscedasticity Assumptionmentioning

confidence: 99%

See 1 more Smart Citation

Regression Diagnostics with Predicted Residuals of Linear Model with Improved Singular Value Classification Applied to Forecast the Hydrodynamic Efficiency of Wave Energy Converters

Tenekedjiev

Abdussamie

et al. 2021

Applied Sciences

View full text Add to dashboard Cite

show abstract

“…13 Townsend and Shenoi 14 investigated that an energy recovery system that uses a gyroscope feed to generate relative motion within the vessel, thereby generating power from waveinduced rolling and pitching motions. Ruriko et al, 15 Engstrm et al, 16 and Amarkarthik and Sivakumar 17 developed the point absorption wave energy converter. What's more, Horno et al 18 and Paduano et al 19 proposed a unit utilizing the current energy.…”

Section: Introductionmentioning

confidence: 99%

Numerical investigation on the effect of the vessel rolling angle and period on the energy harvest

Zhang

Yang³

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part M:

View full text Add to dashboard Cite

In order to harvest effectively the mechanical energy produced in the process of vessel rolling, an energy harvest unit installed on the vessel is designed to utilize the mechanical energy. Firstly, the structure of the unit is proposed, and the relevant mathematical model is established. The solution of the mathematical model is given by Newmark- β method. Then, the influence of vessel rolling period and angle on the unit’s power and related parameters of the block is studied by MATLAB simulation. The results show that when the vessel is rolling, the energy harvest unit has a considerable power generation effect, the rolling period and angle of the vessel have a great impact on the power of the unit. Under the condition of the same period, the vessel with a larger rolling angle corresponds to larger peak gravity component, peak angular displacement, peak linear velocity of block and average power of the unit. In addition, under the same sea conditions, numerical simulations carried out on the rolling motion of 70,000, 100,000, and 150,000-ton bulk vessels and related parameters of the unit, indicating that the instantaneous power of the unit is not uniform in actual sea conditions, but it can output power continuously.

show abstract

Fuzzy Sets Applications in Complex Energy Systems: A Literature Review

Kahraman

Öztayşi

Onar

et al. 2018

Studies in Systems, Decision and Control

View full text Add to dashboard Cite

Investigation on modeling of non-buoyant body typed point absorbing wave energy converter using Adaptive Network-based Fuzzy Inference System

Cited by 6 publications

References 22 publications

Regression Diagnostics with Predicted Residuals of Linear Model with Improved Singular Value Classification Applied to Forecast the Hydrodynamic Efficiency of Wave Energy Converters

Regression Diagnostics with Predicted Residuals of Linear Model with Improved Singular Value Classification Applied to Forecast the Hydrodynamic Efficiency of Wave Energy Converters

Numerical investigation on the effect of the vessel rolling angle and period on the energy harvest

Fuzzy Sets Applications in Complex Energy Systems: A Literature Review

Contact Info

Product

Resources

About