Artificial Intelligence is successful and widely used in solving problems associated with complexity, and non-linearity. It is extensively used in almost all aspects of concrete technology. However,advances in ANN applications are trivial and not progressing for last four decades.. So, what are the latest developments and potential challenges in this area?
It has been used to predict the compression strength from a wide range of mix proportions.
Dear Mr Saad, I agree that it has been used to predict the compressive strength and I did mentioned that in my question that it has been extensively used in concrete technology. Many earlier work in concrte technology used ANN applications. However, advances in ANN applications are trivial and not progressing for last four decades.
So my question is what are the recent developments and potential challenges in applying these techniques in concrete technology?
You may follow the below links.....
http://fulltext.study/preview/pdf/896383.pdf
http://research.microsoft.com/en-us/um/people/horvitz/selman.htm
https://www.researchgate.net/profile/Jui-Sheng_Chou/publication/299428356_Metaheuristic_optimization_within_machine_learning-based_classification_system_for_early_warnings_related_to_geotechnical_problems/links/572eb4a408aeb1c73d129907.pdf
https://ea-stiftung.org/files/Artificial-Intelligence-Opportunities-and-Risks.pdf
Article Metaheuristic optimization within machine learning-based cla...
I was not aware that we have been using anything but AI when working with concrete!
Dear Gordon,
To design the optimal mix, technical personnel has to carry out several mix proportions, which is time consuming, wastage of materials and increase in cost of concrete productions. Further, to design high performance concrete, the conventional method is used which are based on previous experience and empirical relationship. However, these methods are incapable of modelling due to the complex relationship between concrete mix ingredients and the final concrete properties. So, many researchers are successful in modelling these relationships using AI to design the optical mix.
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