Site planning, building design and specific building elements are the main parameters handled to analyse the climatic considerations.
Energetic parameters handle the structural robustness in both cases, but while environmental robustness is a global outcome, mutational robustness is local.
All the motor parameters handled by the premotor cortex modules in both ILGM and ILGA are kinematics parameters dynamics is completely ignored by these modules and handled entirely by the primary motor module.
Finding the hyperplane while maximizing the margin is formulated as the following optimization problem: (3) min 1 2 w T w + C ∑ i = 1 N ξ i subject to: y i (〈 w, ϕ (x i ) 〉 + b ) ≥ 1 − ξ i, ξ i ≥ 0, (i = 1, …, N ), where C is the cost parameter constant, ξ i is parameter for handling nonseparable data, and the index i labels the N training cases.
Experimental results show that the system has a high operation speed, real time and multi-parameter handling capability.
Even though the parameter optimizer handles any number of parameters simultaneously, a comprehensive optimization would in general be far too computationally expensive.
Various critical aspects in numerical modelling like boundary conditions, material input parameters, and handling severe distortion of the Lagrangian based finite elements are appropriately explained.
However, there has been some progress in developing both large sample and finite sample robustness of SEM parameters in handling non-normal data and outliers [ 25, 26].
In DE, the scaling factor F and crossover rate C r determine the correction and speed of convergence, while another important parameter, NP, the population size, remains a user-assigned parameter to handle problem complexity.
