I need an image about this definition: Systems engineering is a process that hel
I need an image about this definition: Systems engineering is a process that helps manage the complexity of large systems.. It is a way to ensure that all the different parts of a system work together smoothly and efficiently.. Considers the business and technical requirements of customers to provide a high-quality solution that meets the demands of customers and other stakeholders., is suitable for its intended real-world use and avoids or minimizes unintended harmful consequences. The work of a systems engineer involves a large number of variables related to complex systems., In addition to optimizing existing systems. An important concept in systems engineering is algorithms. normally, An algorithm is a sequence of steps, in order and without ambiguity, that must be followed to solve a problem. The first step is to understand the problem you need to solve, with the greatest possible abstraction and precision, desarrollando So la primera versión de tu algoritmo. The second step is to improve the initial algorithm, trying to see all the possible situations that can occur, trying to eliminate redundancies and, So, optimize the steps.
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I need an image about this definition: Systems engineering is a process that helps manage the complexity of large systems
..
It is a way to ensure that all the different parts of a system work together smoothly and efficiently
..
Considers the business and technical requirements of customers to provide a high-quality solution that meets the demands of customers and other stakeholders
.,
is suitable for its intended real-world use and avoids or minimizes unintended harmful consequences
.
The work of a systems engineer involves a large number of variables related to complex systems
.,
In addition to optimizing existing systems
.
An important concept in systems engineering is algorithms
.
normally
,
An algorithm is a sequence of steps
,
in order and without ambiguity
,
that must be followed to solve a problem
.
The first step is to understand the problem you need to solve
,
with the greatest possible abstraction and precision
,
desarrollando So la primera versión de tu algoritmo
.
The second step is to improve the initial algorithm
,
trying to see all the possible situations that can occur
,
trying to eliminate redundancies and
,
So
,
optimize the steps
.
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