Abstract: A method for use of airport runway capacity includes receiving, at an air traffic control system at an airport, airport data related to movement areas of the airport, time data related to a time period, aircraft data related to a plurality of aircraft expected to operate into and out of the airport during the time period, and environmental data related to environmental conditions predicted for the airport during the time period. The method further includes computing a probability distribution for inter-aircraft spacing by applying the airport data, the time data, the aircraft data, and the environmental data to a trained Bayesian network, producing the probability distribution for the inter-aircraft spacing as an output observation of the trained Bayesian network, and, using the probability distribution and a confidence value, identifying an inter-aircraft spacing value for the plurality of aircraft expected to operate into and out of the airport during the time period.

Abstract: A method for safe and efficient use of airport runway capacity includes receiving, at an air traffic control system at an airport, airport data related to movement areas of the airport, time data related to a time period, aircraft data related to a plurality of aircraft expected to operate into and out of the airport during the time period, and environmental data related to environmental conditions predicted for the airport during the time period. The method further includes computing a probability distribution for inter-aircraft spacing by applying the airport data, the time data, the aircraft data, and the environmental data to a trained Bayesian network, producing the probability distribution for the inter-aircraft spacing as an output observation of the trained Bayesian network, and, using the probability distribution and a confidence value, identifying an inter-aircraft spacing value for the plurality of aircraft expected to operate into and out of the airport during the time period.

Abstract: A method for safe and efficient use of airport runway capacity includes receiving, at an air traffic control system at an airport, airport data related to movement areas of the airport, time data related to a time period, aircraft data related to a plurality of aircraft expected to operate into and out of the airport during the time period, and environmental data related to environmental conditions predicted for the airport during the time period. The method further includes computing a probability distribution for inter-aircraft spacing by applying the airport data, the time data, the aircraft data, and the environmental data to a trained Bayesian network, producing the probability distribution for the inter-aircraft spacing as an output observation of the trained Bayesian network, and, using the probability distribution and a confidence value, identifying an inter-aircraft spacing value for the plurality of aircraft expected to operate into and out of the airport during the time period.

Abstract: A runway capacity forecast system includes machine instructions stored in a non-transitory computer readable storage medium, the machine instructions, when executed, causing a processor to access data items related to a runway of interest for a time horizon of interest, the data items comprising environment factors for the runway of interest and the time horizon of interest, flight operation factors, and aircraft performance factors for aircraft scheduled on the runway of interest and during the time horizon of interest; extract data elements from the data items; reformat the data elements as analyzable data elements and store the analyzable data elements in an analyzable data structure; apply a probabilistic model to selected ones of the analyzable data elements to provide a forecast runway capacity for the runway of interest during the time horizon of interest the first product; and using the forecast runway capacity, determine one or more impacts based on the forecast capacity.

Abstract: A peer-to-peer (P2P) networking system is disclosed that provides a large, persistent object repository with the ability to easily scale to significant size. Data security is provided using a distributed object data access mechanism to grant access to data objects to authorized users. Data objects stored within the object repository are provided a plurality of security options including plain text data, objects, encrypted data objects, and secure, secret sharing data objects. A data object query processing component permits users to locate requested information within the P2P networking system.