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The systematic solution of highly complex problems requires a long view and plenty of patience.
The methodology is quite general and can be applied to the systematic solution of difficult estimation problems in many fields, when sources of uncertainty can be identified and modeled.
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In summary, the systematic solutions are usually to reduce the complexity of data to accelerate the computation time of KDD and to improve the accuracy of the analytics result.
In this paper, a case study was used to demonstrate the application of this systematic solution.
When it comes to determining closed form solutions for equations without a Lie symmetry, decomposition is the only systematic solution procedure at hand.
The formulation and systematic solution of this problem has shown better results when all the variables of the Rankine cycle and the compositions of the working fluid are considered simultaneously.
For the vast majority of equations without a Lie symmetry decomposition is the only available systematic solution procedure.
Consistency of this model with the physics of the problem is demonstrated and a systematic solution to the corresponding equations is developed.
In addition, because of the non linear nature of the resulting model, a systematic solution procedure is proposed in order to guarantee the model convergence.
The study demonstrates the development of a systematic solution that integrated knowledge of urban planning, landscape ecology, environmental science, and hydrology.
Note that the main objective of the DCMS project is to provide a systematic solution to the problems mentioned above.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com