Transferring practical algorithms and
guidelines from the Source Domain to the Target Domain is cost-effective in
System development. The strength of Analogical Inferences can indicate similar
properties between the Source Domain and Target Domain. Therefore, practical
algorithms and guidelines can adapt to the Target Domain. Besides, System developers
may consider that target and source domains can be allocated to the same system
platform in a high integration mode.
Analogical Inference can genuinely
configure into mental representations of the Target Domain under some
circumstances. Parameter adaptation in the Target Domain can be valid for the
algorithm. System developers explore knowledge beyond Source domains as
theoretical frameworks for system development. The Source Domain contains
knowledge that can ensure practical algorithms and consistency of system
performances in the target domain.
Invisible entities can emerge and instantiate in Non-Biological Systems
when system developers apply analogical inferences with low structural mapping,
focusing primarily on functional mechanisms within the system platform.
