Search Results - (( variable integration based algorithm ) OR ( variable equations using algorithm ))

SURE-Autometrics algorithm for model selection in multiple equations by Norhayati, Yusof

“…Two sets of general unrestricted models (GUMS) are then formulated by adding a number of irrelevant variables to the specification models. The performance is measured by the percentages of SURE-Autometrics algorithm that are able to eliminate the irrelevant variables from the initial GUMS of two, four and six equations. …”
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Numerical algorithm of block method for general second order ODEs using variable step size by Nazreen Waeleh, Zanariah Abdul Majid

“…Consequently, a direct block multistep method with utilization of variable step size strategy is proposed. This method was developed for computing the solution at four points simultaneously and the derivation based on numerical integration as well as using interpolation approach. …”
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Parallel method using MPI for solving large systems of delay differential equations by Ishak, Fuziyah, Suleiman, Mohamed

“…The algorithm is based on a variable stepsize variable order block method. …”
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Numerical algorithm of block method for general second order ODEs using variable step size by Waeleh, Nazreen, Abdul Majid, Zanariah

“…Consequently, a direct block multistep method with utilization of variable step size strategy is proposed. This method was developed for computing the solution at four points simultaneously and the derivation based on numerical integration as well as using interpolation approach. …”
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Extended multiple models selection algorithms based on iterative feasible generalized least squares (IFGLS) and expectation-maximization (EM) algorithm by Nur Azulia, Kamarudin

“…This extension of Autometrics for model selection was also developed for multiple equations by integrating it with seemingly unrelated regressions equations (SURE) and estimated using feasible generalized least squares (FGLS), known as SURE-Autometrics algorithm. …”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

“…In the developed feature selection approach, multi-objective binary-valued backtracking search algorithm (MOBBSA) is used as an efficient evolutionary search algorithm to search within different combinations of input variables and selects the non-dominated feature subsets, which minimize simultaneously both the estimation error and the number of features. …”
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Comparison between Secant method, Newton method and Bisection method in solving nonlinear equation / Nurul Ashsyikin Yasir by Yasir, Nurul Ashsyikin

“…Throughout this project, it will help the researcher to finding a root for nonlinear equation using the best method.…”
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Partitioning techniques and their parallelization for stiff system of ordinary differential equations by Othman, Khairil Iskandar

“…A new code based on variable order and variable stepsize component wise partitioning is introduced to solve a system of equations dynamically. …”
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Parallel block methods for solving higher order ordinary differential equations directly by Omar, Zurni

“…The accuracy of the parallel block and 1-point methods is comparable particularly when finer step sizes are used. A new parallel algorithm for solving systems of ODEs using variable step size and order is also developed. …”
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What drives Chinese youth to use fitness-related health information on social media? an analysis of intrinsic needs, social media algorithms, and source credibility by Zhang, Xin, Tang, Qing Qing, Cai, Ying Ying

“…This study aims to address this gap by integrating Self-Determination Theory (SDT)-based internal factors and external factors (social media algorithms and source credibility). …”
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Operational matrix based on orthogonal polynomials and artificial neural networks methods for solving fractal-fractional differential equations by Shloof, Aml Melad Asan

“…Finally, ANNs employing a combination of power series methods in the GCFFD are developed to approximate solutions of higher-order linear FFDEs with both constant and variable coefficients. Initially, the algorithm utilized a truncated series. …”
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Dynamic two phase modelling and anfis-based control of ethylene copolymerization in catalytic Fluidized Bed Reactor / Mohammad Reza Abbasi by Mohammad Reza , Abbasi

“…Firstly, conventional Proportional-Integral-Differential (PID) controller was used to control the variables in both servo and regulatory scenarios. …”
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Modelling of Adsorption of Dyes from Aqueous Solution by Activated Carbon by Wong, Teck Ngin

“…These v sets of ODEs are then integrated using the numerical algorithm DIVPAG (IMSL library subroutine), which is based on variable order, variable step method implementing backward differential formula (Gear’s Method) and is suitable for stiff system of first order non-linear ODEs. …”
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Pembangunan dimensi baru bagi model regresi eksponen (kreb): aplikasi dalam sains kesihatan by Rohim, Rabi'atul 'Adawiyah Abdul

“…The main focus of this study is to establish a standard procedure for integrated exponential function algorithm, the KREB Model, with emphasis on the modelling techniques based on the scientific computational statistical method and the advanced statistical method by utilising the SAS software. …”
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The accuracy of the gas-kinetic BGK finite difference method for solving 3-D compressible inviscid flows by Ong, Jiunn Chit, Omar, Ashraf Ali, Asrar, Waqar

“…In constructing the desired algorithm, the convection flux terms were discretized by a semi-discrete finite difference method. …”
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Partial least squares integrated national water quality standards (NWQS) for indexing of water quality from industrial effluent by Emmanuel, Freda

“…Indexing with DOE-WQI equation method using six (6) pre-determined DOE-WQI parameters revealed that all stations falls under Class III with a slightly polluted status. …”
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Numerical methods for nonlinear optimal control problems using haar wavelet operational matrices / Waleeda Swaidan Ali by Waleeda Swaidan, Ali

“…The inequality constraints for trajectory variables are transformed into quadratic programming constraints by using the Haar wavelet collocation method. …”
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Computational Analysis of Gas Kinetic Bhatnagar-Grosskrook Scheme for Inviscid Compressible Flow by Ong, Jiunn Chit

“…Many numerical schemes have been developed in the field of computational fluid dynamics to simulate inviscid, compressible flows.Among those most notable and successful are the Godunov-type schemes and flux vector splitting schemes.Besides these numerical schemes, schemes based on the gas kinetic theory have been developed in the past few years.Stemming from this approach, the gas kinetic Bhatnagar-Gross-Krook (BGK) scheme is realized.In this thesis, the BGK scheme based on the BGK model of the approximate Boltzmann equation has been fully analyzed and developed accordingly.The numerical algorithms for the BGK scheme are first developed for simulating one-dimensional flow, and then follow by the-two dimensional flow realms. …”
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Optical soliton perturbation with quadratic-cubic nonlinearity / Mir Asma by Mir, Asma

“…These perturbation terms are mostly of Hamiltonian type that permits integrability of the perturbed NLSE. The spectrum of soliton solutions, that emerge from these algorithms are of bright, dark singular and combo solitons, which depends on the sign of discriminant and these findings are illustrated numerically too. …”
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Intelligence Integration Of Particle Swarm Optimization And Physical Vapour Deposition For Tin Grain Size Coating Process Parameters by Abdul Syukor, Mohamad Jaya, Mu*ath Ibrahim, Mohammad Jarrah, Mohd Asyadi Azam, Mohd Abid, Mohd Razali, Muhamad

“…Additionally,analysis of variance (ANOVA) was used to determine the significant factors influencing resultant TiN coating grain size.Based on that,a quadratic polynomial model equation was developed to represent the process variables and coating grain size.Then,in order to optimize the coating process parameters,genetic algorithms (GAs) were combined with the RSM quadratic model and used for optimization work.Finally,the models were validated using actual testing data to measure model performances in terms of residual error and prediction interval (PI).The result indicated that for RSM,the actual coating grain size of validation runs data fell within the 95% (PI) and the residual errors were less than 10 nm with very low values, the prediction accuracy of the model is 96.09%.In terms of optimization and reduction the experimental data,GAs could get the best lowest value for grain size then RSM with reduction ratio of ≈6%, ≈5%, respectively.…”
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