Search Results - (( parameter optimization based algorithm ) OR ( interval estimation methods algorithm ))

Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm by Farzin, Saeed, Singh, Vijay, Karami, Hojat, Farahani, Nazanin, Ehteram, Mohammad, Kisi, Ozgur, Allawi, Mohammed Falah, Mohd, Nuruol Syuhadaa, El-Shafie, Ahmed

“…Design of hydraulic structures, flood warning systems, evacuation measures, and traffic management require river flood routing. A common hydrologic method of flood routing is the Muskingum method. The present study attempted to develop a three-parameter Muskingum model considering lateral flow for flood routing, coupling with a new optimization algorithm namely, Improved Bat Algorithm (IBA). …”
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Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS by Hassan, S., Khanesar, M.A., Jaafar, J., Khosravi, A.

“…In this paper, heuristic optimization approaches such as genetic algorithm and artificial bee colony are used to optimize the parameters of the antecedent part of interval type-2 fuzzy logic systems. …”
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Towards enhanced remaining useful life prediction of lithium-ion batteries with uncertainty using optimized deep learning algorithm by Reza M.S., Hannan M.A., Mansor M., Ker P.J., Rahman S.A., Jang G., Mahlia T.M.I.

“…In addition, to validate the prediction performance of the proposed LSA + LSTM model, extensive comparisons are performed with other popular optimization-based deep learning methods including artificial bee colony (ABC) based LSTM (ABC + LSTM), gravitational search algorithm (GSA) based LSTM (GSA + LSTM), and particle swarm optimization (PSO) based LSTM (PSO + LSTM) model using different error matrices. …”

Semiparametric inference procedure for the accelarated failure time model with interval-censored data by Karimi, Mostafa

“…The rank-based methods, estimating algorithms, and resampling techniques that are developed do not involve the difficulties of the existing estimating procedures. …”
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Non-Parametric and Parametric Estimations of Cure Fraction Using Right-and Interval-Censored Data by Aljawdi, Bader

“…In this thesis, we considered two methods via the expectation maximization (EM) algorithm for cure rate estimation based on the BCH model using the two censoring types common to cancer clinical trials; namely, right and interval censoring. …”
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Comparison between specifications of linear regression and spatial-temporal autoregressive models in mass appraisal valuation for single storey residential property by Jahanshiri, Ebrahim

“…Furthermore, various spatial, temporal and spatio-temporal neighbourhood and weighting schemes, optimization algorithms and lag and error modelling scenarios were created and tested with the data. …”
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Non-parametric maximum likelihood estimation of cure fraction for interval survival data. by I. Aljawadi, Bader Ahmad, Abu Bakar, Mohd Rizam, Ibrahim, Noor Akma

“…The Nonparametric maximum likelihood estimation method is used for interval censored data based on the bounded cumulative hazard (BCH) model. …”
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The computation of confidence intervals for the state parameters of power systems by Khan, Z., Razali, R.B., Daud, H., Nor, N.M., Fotuhi-Firuzabad, M., Krebs, K.L.

“…Methods: The feasible interval estimates for the system state parameters have been modelled in this study by considering the random uncertainty in the processing measurements. …”
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The computation of confidence intervals for the state parameters of power systems by Khan, Z., Razali, R.B., Daud, H., Nor, N.M., Fotuhi-Firuzabad, M., Krebs, K.L.

“…Methods: The feasible interval estimates for the system state parameters have been modelled in this study by considering the random uncertainty in the processing measurements. …”
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An analytical approach on parametric estimation of cure fraction based on weibull distribution using interval censored data. by I. Aljawadi , Bader Ahmad, Abu Bakar, Mohd Rizam, Ibrahim, Noor Akma

“…We propose this cure rate model based on the Weibull distribution with interval censored data. Maximum likelihood estimation (MLE) method is proposed to estimate the parameters within the framework of expectation-maximization (EM) algorithm, Newton Raphson method also employed. …”
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Operational structural damage identification using de-noised modal feature in machine learning / Chen Shilei by Chen , Shilei

“…In conclusion, the supervised learning method using FRF change is convenient and effective in identifying the damage state of the plate, and can be optimized through mode shape assessment. …”
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Turnbull versus Kaplan-Meier estimators of cure rate estimation using interval censored data by Aljawadi, Bader Ahmad I., Abu Bakar, Mohd Rizam, Ibrahim, Noor Akma

“…Thus, the non-parametric estimation methods are employed by means of the EM algorithm. …”
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Cure fraction model for interval censoring with a change point based on a covariate threshold by Taweab, Fauzia, Ibrahim, Noor Akma, Mohd Rizam

“…Maximum likelihood estimators of the model parameters are obtained using the Expectation Maximization (EM) algorithm. …”
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Parametric maximum likelihood estimation of cure fraction using interval-censored data by Aljawadi, Bader Ahmad I., Abu Bakar, Mohd Rizam, Ibrahim, Noor Akma, Al-Omari, Mohamad

“…The parametric maximum likelihood estimation method was used for estimation of the cure fraction based on application of the bounded cumulative hazard (BCH) model to interval-censored data. …”
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Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems by Kek, Sie Long

“…The main idea is the integration of optimal control and parameter estimation. In this work, a simplified model-based optimal control model with adjustable parameters is constructed. …”
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Parametric cure fraction models for interval-censoring with a change-point based on a covariate threshold by Ali Taweab, Fauzia

“…The parametric maximum likelihood estimation method is employed to verify the performance of the MCM within the framework of the expectation-maximization (EM) algorithm while the estimation methods for other models are employed in a simpler and straightforward setting. …”
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On Adopting Parameter Free Optimization Algorithms for Combinatorial Interaction Testing by Kamal Z., Zamli, Alsariera, Yazan A., Nasser, Abdullah B., Alsewari, Abdulrahman A.

“…In doing so, this paper reviews two existing parameter free optimization algorithms involving Teaching Learning Based Optimization (TLBO) and Fruitfly Optimization Algorithm (FOA) in an effort to promote their adoption for CIT.…”
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Finite impulse response optimizers for solving optimization problems by Ab Rahman, Tasiransurini

“…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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Finite impulse response optimizers for solving optimization problems by Tasiransurini, Ab Rahman

“…Selecting optimal parameters’ values may improve an algorithm’s performance. …”
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Rank-based inference for the accelerated failure time model in the presence of interval censored data by Karimi, Mostafa, Ibrahim, Noor Akma, Abu Bakar, Mohd Rizam, Arasan, Jayanthi

“…In this paper a class of asymptotically normal rank estimators is developed which can be aquired via linear programming for estimating the parameters of the model, and a two-step iterative algorithm is introduce for solving the estimating equations. …”
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