end{aligned} (43) Equivalently, the modified evolution equations for (B^{i}) (see Appendix B) read begin{aligned}& partial_{t} bigl(sqrt{gamma} B^{j} bigr) + partial_{i} bigl( sqrt{gamma} bigl(mathcal {V}^{i}B^{j}- mathcal {V}^{j}B^{i}-B^{i} beta^{j} bigr) bigr) & quad = - sqrt{gamma}B^{i} partial_{i} beta^{j} - sqrt{gamma}alphagamma^{ij} partial_{i}phi.
In the slow-time acceleration technique, a modified evolution equation is developed in which the longest time scale is much shorter than that of the original system, and which has the same multi-time scale asymptotic structure as the original system.
In the present study, a novel modified differential evolution [Angira, R., Babu, B.V., 2005a. Optimization of non-linear chemical processes using modified differential evolution (MDE). Proceedings of the Second Indian International Conference on Artificial Intelligence (IICAI-05), Pune, India, December 20 22, pp. 911 923.
For example, the forelimbs of humans, birds, crocodiles, bats, dolphins, and rodents have been modified by evolution to perform different functions, but they are all evolutionarily traceable to the fins of crossopterygian fishes, in which that basic arrangement of bones was first established.
The automated extraction procedure based on modified differential evolution is demonstrated to be efficient and effective.
Parameters of the inverse neural NARX model are optimized with the modified differential evolution (MDE) algorithm.
For this reason, we address this problem as an optimization problem, solved by using a modified differential evolution algorithm.
The cost obtained from modified differential evolution (MDE) [10], clonal selection algorithm (CSA) [15] and teaching learning based optimization (TLBO) [16] is also shown in Table 11.
Our modified differential evolution (MDE) algorithm utilizes only one set of population as against two sets in original DE at any given point of time in a generation.
In this paper, a novel modified differential evolution (mDE) algorithm for advanced form-finding of tensegrity structures is proposed to define an appropriate candidate for strut members.
The proposed methodology is developed in the framework of a modified stochastic evolution mechanism in order to tame the computational complexity.
