The phrase "ability of evolutionary" is not correct in English as it lacks clarity and proper grammatical structure.
It could be used in a context discussing the capabilities or potential of evolutionary processes, but it needs to be rephrased for clarity.
Example: "The ability of evolutionary mechanisms to adapt to changing environments is crucial for survival."
Alternatives: "capacity for evolution" or "evolutionary potential".
This model has both the features of a fuzzy Petri net and the learning ability of evolutionary algorithms.
We also see no evidence for the neutral evolution of increased solution robustness, but show that this may be due to the ability of evolutionary algorithms to focus search on volumes of the fitness landscape with above average robustness.
It reflects the ability of evolutionary analyses to contribute to the broader social sciences and humanities.
The performance of COEAs mainly depends on the search ability of evolutionary algorithm and the effectiveness of constraint-handling technique.
That is, the processes of evolution, the available evidence of evolutionary change, the ability of evolutionary theory to explain phenomena, the evolution of humans, the age of the earth and the scientific community's views of evolutionary theory.
In the present work, we tested the ability of evolutionary genetics information to inform the choice of the optimum enzymes for converting pyruvate to succinate from three species.
The experiments presented in this paper were designed to examine the ability of an evolutionary cellular development model to evolve various synaptic plasticity regimes.
Here, we tested the ability of molecular evolutionary analysis to identify appropriate genes from various species.
In order to enhance the optimization ability of the quantum evolutionary algorithms, a new quantum-behaved evolutionary algorithm is proposed.
Recent research efforts have provided hints towards the innate ability of population-based evolutionary algorithms to tackle multiple distinct optimization tasks at once by combining them into a single unified search space.
The convergence ability of Pareto-based evolutionary algorithms sharply reduces for many objective optimization problems because solutions are difficult to rank by the Pareto dominance due to large size of non-dominance area.
