Description
Neural Network Driven Artificial Intelligence: Decision Making Based on Fuzzy Logic (Computer Science, Technology and Applications: Mathematics Research Developments)
With today’s growing and overloading volume of information, it is becoming tremendously difficult to analyze the huge amounts of data that contain this information. It makes it very strenuous and inconvenient to introduce an appropriate methodology of decision-making fast enough to the point that it can be considered as real-time. The demand for real-time processing information and related data both structured and unstructured is on the rise and consequently makes it harder and harder to implement correct decision making at the enterprise level to keep the organization robust and resilient against either manmade threats or natural disasters.
Neural networking and fuzzy systems combined show how Artificial Intelligence (AI) can be driven by these combinations as a trainable system that is more dynamic than static when it comes to machine and deep learning language to deal with both adversary and friendly events in real-time. Dynamic systems of AI that are built around such an innovative approach allows the robots of the future to be more adaptive with mechanisms such as principle adoption, self-organization, and the convergence of global stability from the viewpoint of business and intelligence security needed in today’s cyber world.
