Search Results - (( java adaptation optimization algorithm ) OR ( parameter interaction modified algorithm ))

A Modified ACO-based Search Algorithm for Detecting Protein Functional Module From Protein Interaction Network by Jamaludin, Sallim, Rozlina, Mohamed, Roslina, Abd Hamid

“…Some shortcomings were identified and addressed by proposing a Modified Ant Colony Optimization Algorithm (ACO-PFMDM), which introduces two new scheme for controlling the two main parameters of ACO to solve PFMDP. …”
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Parallel distributed genetic algorithm development based on microcontrollers framework by Krishnan P.S., Kiong T.S., Koh J.

Modeling the properties of terminal blend crumb rubber modified bitumen with crosslinking additives by Jegatheesan N., Ibrahim M.R., Ahmed A.N., Koting S., El-Shafie A., Katman H.Y.B.

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A Hybrid ACO-Graph Entropy for Functional Modules Detection From Protein-Protein Interaction Network by Jamaludin, Sallim, Rozlina, Mohamed, Che, Yahaya, Roslina, Abdul Hamid

“…Some shortcomings were identified and addressed by proposing a Modified Ant Colony Optimization Algorithm (ACO-PFMDM), which introduces two new scheme for controlling the two main parameters of ACO to solve PFMDP. …”
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Application of conjugate gradient approach for nonlinear optimal control problem with model-reality differences by Leong, Wah June, Sie, Long Kek, Teo, Kok Lay, Sim, Sy Yi

“…In doing so, an expanded optimal control problem is introduced such that system optimization and parameter estimation are mutually interactive. Accordingly, the optimality conditions are derived after the Hamiltonian function is defined. …”
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Application of conjugate gradient approach for nonlinear optimal control problem with model-reality difference by Sie, Long Kek, Wah, June Leong, Sy, Yi Sim, Kok, Lay Teo

“…In doing so, an expanded optimal control problem is introduced such that system optimization and parameter estimation are mutually interactive. Accordingly, the optimality conditions are derived after the Hamiltonian function is defined. …”
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MULTIVARIABLE CLOSED-LOOP SYSTEM IDENTIFICATION USING ITERATIVE LEAKY LEAST MEAN SQUARES METHOD by MOHAMED OSMAN, MOHAMED ABDELRAHIM

“…In this research. novel algorithms have been developed to: (I) isolate the less interacting channe Is using a modified partial correlation algorithm. (2) achieve unbiased and consistent parameter estimates using an iterative LLMS algorithm and (3) develop parsimonious models for closed-loop MIMO systems. …”
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Interaction effect of process parameters and Pd-electrocatalyst in formic acid electro-oxidation for fuel cell applications: Implementing supervised machine learning algorithms by Hossain S.K.S., Ali S.S., Rushd S., Ayodele B.V., Cheng C.K.

Simultaneous computation of model order and parameter estimation for ARX model based on single swarm and multi swarm simulated Kalman filter by Kamil Zakwan, Mohd Azmi, Zuwairie, Ibrahim, Pebrianti, Dwi, Mohd Saberi, Mohamad

“…Simultaneous Model Order and Parameter Estimation (SMOPE) and Simultaneous Model Order and Parameter Estimation based on Multi Swarm (SMOPE-MS) are two techniques of implementing meta-heuristic algorithm to iteratively establish an optimal model order and parameters simultaneously for an unknown system. …”
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Modified least trimmed squares method for face recognition / Nur Azimah Abdul Rahim by Abdul Rahim, Nur Azimah

“…The genetic algorithm configuration for n (number of observations) and p (parameter) was changed to assess the performance of modified method. …”
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Optimization of chemotherapy using metaheuristic optimization algorithms / Prakas Gopal Samy by Prakas Gopal , Samy

“…The HM emerges as a dominant strategy, driven by the Multi-Objective Differential Evolution (MODE) algorithm under literature-based control parameter settings for the mathematical model. …”
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Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions by Saraswati, Galuh Wilujeng

“…The project has also implemented the optimization process onto the proposed ANFIS model through the hybrid of Genetic Algorithm on the fuzzy membership function of the ANFIS model. …”
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Improved model for blood glucose control using Multi-Parametric Model Predictive Control (MP-MPC) / Nur Farhana Mohd Yusof by Mohd Yusof, Nur Farhana

“…As a result, we managed to have a good correlation on interactions between the parameters in glucose-insulin intervention. …”
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A comprehensive analysis of surface electromyography for control of lower limb exoskeleton by Abdelhakim, Deboucha

“…Unlike other control methods applied to industrial robotic systems in the sense of giving specific trajectory to be tracked, ERD physically interacts alongside with the user. To attain high cognitive interaction and safe human-machine system, there is a need to detect the user‘s movement intention. …”
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A centralised multi-objective model predictive control for biventricular assist devices / Vivian Koh Ci Ai by Vivian Koh , Ci Ai

“…Therefore, the second objective was to modify a conventional centralised MPC algorithm to cater for the state and time-varying factors of the CVS-BiVAD system. …”
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Comparison of quadratic Trigonometric B-Spline and Cubic B-Spline in designing objects / Ainna Solihah Awaluddin by Awaluddin, Ainna Solihah

“…By designing curves of an object using Wolfram Mathematica, the study integrates an interactive application for both methods to demonstrates the curve behaviour by modifying the shape parameters and control points of the objects. …”
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Effect of graphene oxide as a nanomaterial on the bond behaviour of engineered cementitious composites by applying RSM modelling and optimization by Bheel, N., Mohammed, B.S., Ali, M.O.A., Shafiq, N., Radu, D.

“…The response surface methodology (RSM) is employed for developing predictive algorithms, which are then utilised in performing multi-variate optimization on bond-slip parameters, including bond strength, bond slip and bond energy. …”
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Instance matching framework for heterogeneous semantic web content over linked data environment by Mansir, Abubakar

“…The output of each algorithm is evaluated, the results have shown that each algorithm performs well and outperforms the existing algorithms on all test cases in terms better output generation and effective handling of heterogeneity from different domains, which is a necessary concern in all data-intensive problems. …”
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