Sentence examples for intelligence for decision-making from inspiring English sources

The main aim here is to use data from various sources, to apply processing models, to visualise results, to build a knowledge-base and to use intelligence for decision-making and exchange outcomes.

It is therefore crucial to design and develop control and conversion systems that represent the key instrument where intelligence for decision-making is applied, in order to validate and ensure its optimal operation as part and parcel of the electrical system.

Smart energy management in decentralised renewable systems requires computational intelligence to implement pivotal energy-aware/cost-aware procedures in decision-making for a conceptualised next generation Smart Village microgrid platform.

Before he gave his written informed consent for this case report to be published, he was in healthy enough mental and physical condition that would have allowed them to provide informed consent for publication with his free will, good enough intelligence for decision making ability and clear consciousness.

This study presents an expert system (ES) for the management of petroleum contaminated sites in which a variety of artificial intelligence (AI) techniques were used to construct a support tool for site remediation decision-making.

The book did not argue against the possibility of artificial intelligence but rather was a passionate criticism of systems that substituted automated decision-making for the human mind.

Decision-making options belong to the key research challenges of e.g., economics, management science, psychology and artificial intelligence.

The versatility of this DE controller permits implementing different methodologies for decision making / conflict resolution, including artificial intelligence techniques, as well as optimization of the resource assignment and part throughput.

Offer opportunities for decision making.

5. "Cross-Boundary Intelligence for Better Decision Making" The ESM solution must span organizational boundaries across the entire enterprise in a cohesive and collaborative manner, and not permit fragmentation with regards to its overall cyber defense.

Numbers won't add up and biases will lead to poor intelligence and decision making.