Scientific Foundation of Real-Time Input-Output Tabulation and AI
—Combinations and Connections between Optimal Input-Output Planning Model and AI ()
ABSTRACT
Be it the era of current Industry 3.0 (3D printing) or the era of Industry 4.0
(customised production) in the future, as far as globalisation is concerned,
based on combinations of automation & information and intelligence, the application
of Big Data, new Cloud Computing technologies, Internet of Things
or new internet industry and AI will usher in a huge revolution to human
beings, which will consequently rock foundations of modern economy, politics,
social sciences, management and accounting, etc. and even bring about
fundamentally changes and development, and hence an era for technology
industry going novelty, i.e. customised production. Commercial re-group and
the drastic society change will influence not only the overall ecological pattern
around the world but also human beings’ value system, knowledge system
and life style. Many seeming probabilities today will become impossible
while the impossible at the moment will go real in the future. Under such
complicated, constantly changing and rapidly developing circumstance, only
when the passive situation of tabulating and interpreting is completely changed,
can national economy’s smooth operation be directed by the objective law of
coordinated development, and thus, to achieve the utmost economic efficiency.
The scientific foundation of the real-time input-output tabulation method and
AI is rightly designed on the basis of the above dreaming realisation. This
thesis will take the real-time analysis of the optimal input-output planning
model and a timely analysis of input-output statistical model as an example to
illustrate how to realise the good wish.
Share and Cite:
Kang, N. (2019) Scientific Foundation of Real-Time Input-Output Tabulation and AI
—Combinations and Connections between Optimal Input-Output Planning Model and AI.
American Journal of Industrial and Business Management,
9, 1831-1872. doi:
10.4236/ajibm.2019.99119.
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