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The method presented has two salient features.
Thus, the method presented has good potential to accurately model tillage forces in a range of soil and operating conditions.
The method presented has a general character and applies to conservative as well as non-conservative systems.
The method presented has been developed in an action research-based approach in an aerospace company where a product design team validated and evaluated the material criticality method.
According to comparison between the obtained results, it shows that the improved method presented has better performance rather than empirical and current methods in neural network designing in petroleum applications for these predictions.
The method presented has a number of desirable properties, including conservation of charge, preservation of a uniform distribution, and generality on nonuniform meshes with arbitrary particle mesh interpolation schemes.
Similar(52)
Each of the methods presented has varying data and resource demands and is associated with specific strengths and limitations, which must be considered when selecting the most appropriate methods for end-user needs.
All the embedded methods presented have no added computational effort compared to their standard counterparts.
So far, all the integration methods presented have been concerned with continuous processes.
Although the methods presented have broad applications, an extensive example exploring various measures of technological similarity based on the USPTO patent classification system is included.
The statistical methods presented have important limitations, which we also briefly discuss.
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CEO of Professional Science Editing for Scientists @ prosciediting.com