Sentence examples for error fitness from inspiring English sources

For this optimization problem, brightness varies inversely proportional to the error fitness value, so the position of the brightest firefly gives the optimum result corresponding to the least error fitness in multidimensional search space.

We propose a faster MOGA where the error fitness function is replaced by a fitness function based on the correlation between endmembers.

Each solution in Harmony Memory (HM) is generated on the basis of memory consideration rule, a pitch adjustment rule and a re-initialization process which gives the optimum result corresponding to the least error fitness in multidimensional search space.

The Manufacturer's Data Sheet information is used as a basis for the purpose of parameter optimization, with an average absolute error fitness function formulated; and a numerical iterative method used to solve the voltage-current relation of the PV module.

This is done by substituting the unmixing error fitness function in Equation (7) by a fitness function based on the maximum correlation between the endmembers f CORR ( E ) = max c i j, e i, e j ∈ E, (10).

Many of these approaches use a prediction error fitness measure, such that they select an architecture based on its generalization to new observations [ 46], while others use a classification error, or training error [ 43].

The differences between calculated outlet pressures and the reference values are considered as an error or fitness function of optimization tool.

A total of 288 models were designed using GA and PSO algorithms and their validity were confirmed using root mean square error (RMSE) fitness function and mean absolute percentage error (MAPE) as shown in Eqs.

The simulation results obtained for some well known benchmark examples justify the efficacy of the proposed OHS based system identification approach over GA, PSO and DE in terms of convergence speed, identifying the system plant coefficients and mean square error (MSE) fitness values produced for both same order and reduced order models of adaptive IIR filters.

The simulation results obtained for some well known benchmark examples justify the efficacy of the proposed system identification approach using FFA over GA, PSO and DE in terms of convergence speed, identifying plant coefficients and mean square error (MSE) fitness values produced for both same order and reduced order models of adaptive IIR filters.

The proponents of the translation-error hypothesis reasonably counter the above objections by showing that the distribution of the code error scores (fitness values) has a Gaussian-like shape where the better, more robust codes form a long tail such that the process of adaptation is non-linear, so approaching the absolute minimum is highly improbable [ 14, 30, 40, 41].