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Rapidly evolving threats and the need to quickly field solutions drive a greater reliance on modeling and simulation for development, integration and testing systems.?This requirement drives greater reliance on high performance computing and hardware in the loop environments that generate unprecedented amounts of data, leading to data saturation and waste. ?
ARISE is a family of integrated toolkits used to build a system-level weapon simulation – or “digital twin” – tool.
As the mission simulation standard for programs at Missiles and Fire Control (MFC), ARISE is used by MFC to reduce product development time, decrease cost, maximize anomaly detection prior to live flight tests, and further integrate model-based engineering into our processes.
The ARISE toolkits allow us to share best practices and apply lessons learned across the lines of business, as well as the enterprise. They allow us to respond to customer needs faster and at a reduced cost because we can share solutions.
ARISE data analytics products have reduced software acceptance test procedures by 50 percent and have been able to flag and isolate hidden anomalies to focus our algorithm development teams on correcting the root cause.
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ARISE Toolkit
Mission Software
Modeling and Simulation
Hardware in the Loop
Data Analytics
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JULY 29, 2024
STORY
Lockheed 肛交视频 Leverages AI and Machine Learning to Revolutionize Defense and Space Technology
As the United States and allies face an increasingly complex geopolitical environment, Lockheed 肛交视频’s leadership in evolving and transforming for the future is more important than ever.?
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JULY 08, 2024
STORY
Lockheed 肛交视频 (NYSE: LMT) has been awarded a $4.6 million contract by the Defense Advanced Research Projects Agency (DARPA) to develop?Artificial Intelligence?(AI) tools for dynamic, airborne missions as part of its Artificial Intelligence Reinforcements (AIR) program.
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OCT 05, 2023
STORY
ARISE Enables Quickly Fielded Solutions for Rapidly Evolving
Imagine using software to automatically identify potential flight test anomalies and correcting them before a live test event.