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This method uses multi-objective programming as its modeling framework.
The evolutionary data assimilation (EDA) method uses multi-objective evolutionary strategy to continuously evolve ensemble of model states and parameter sets where it adaptively determines the model error and the penalty function for different assimilation time steps.
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Zhang et al. [32] propose a cost-based feature selection method using multi-objective particle swarm optimization (PSO).
In this study, a formal optimization method using Multi-Objective Evolutionary Algorithm (MOEA) was developed to overcome such complexities.
This paper presents a new method for network inference, which uses multi-objective optimisation (MOO) to integrate multiple inference methods and experiments.
In this paper, we propose an efficient method by using multi-objective genetic algorithm (MSAGMOGA) to discover optimal alignments with affine gap in multiple sequence data.
Ramakrishna and Karunamoorthy (2006) used multi-objective optimization method using Taguchi's robust design approach for WEDM.
Along with the other variables, the selected fractal parameters were employed to estimate SWRC using multi-objective group method of data handling (mGMDH) and different topologies of artificial neural networks (ANNs).
Equation (13) can be solved by using multi-objective optimization methods and thus the robust control theory will be used to solve the performance optimization problem proposed by Eq. (13).
Then the system was optimized using multi-objective Genetic Algorithm (GA) method.
The primary objective of this work has achieved by using multi-objective algorithm genetic to conclude higher injection efficiency instead of conventional methods.
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