![]() In flight, the pilots tracked at 245 knots - or 281 mph - as their coordinates popped on the screen. “It’s hard to describe the first time you open up the sliding door and see the ground on your first flight.” The Stratotanker is a plane that 26-year-old Covey’s grandfather used to stand guard for, he said. In the cockpit, fans blew as to keep the circuit breakers in the 1962 aircraft from overheating. The temperature in Las Vegas reached 111 degrees Wednesday. The two men both have mustaches and wore green jumpsuits. They flew to Nevada on the Stratotanker from McConnell Air Force Base in Wichita, Kansas. He and Covey serve in the 350th Air Refueling Squadron, known as the Red Falcons. To fight nausea while in flight, boom operator Staff Sgt. They operate their machinery from the back of the plane, lying on a pallet on their stomach in what is called the “boom pod.” The boom operators transferred fuel to seven jets over fluffy clouds and dusty skies Wednesday. It flew in circles 20,000 feet above the Nevada Test and Training Range. On Wednesday, the Stratotanker carried two pilots and two boom operators. It started July 19 and lasts through Saturday. The other two Red Flag exercises this year involved NATO members, but Red Flag 21-3 includes only the United States. The goal is to increase the military’s ability to succeed in combat and return home safely. Red Flag simulates combat situations in a controlled environment. “They can get it all done in the air.”Ĭovey’s flight was part of a combat training exercise during Red Flag, which is hosted three times a year at Nellis Air Force Base. “We can give them their gas close to where they’re fighting,” he said. They turned on a pump, which transferred the fuel to the fighter jet in midflight. When the boom hit the target, Covey radioed to the pilots up front. He steadied his control stick as an F-16’s white tail lights blinked. With precision, Airman 1st Class Jonathon Covey lowered the boom carrying the fuel tank. (Chase Stevens/Las Vegas Review-Journal) boom operator watched the fighter jet hover below his Boeing KC-135 Stratotanker. We note that, for the sake of completeness, we include considerable background material about neural networks also.A KC-135 refueling tanker is prepped before takeoff as part of Red Flag exercises at Nellis Air Force Base in Las Vegas on Wednesday, Aug. Thus, we found that the neural network implementation provided a high-speed, fault-tolerant, and robust computational cell for the identification of tactical maneuvers and suggestions for a best countermaneuver. For each layer, many different architectures and learning rules were tested the network described here gives the best results (55–95% accuracy for partial information). We found that due to high correlation of input data, a single hidden layer could not satisfactorily distinguish (with at least 55–85% accuracy) simple one-on-one maneuvers, such as the Turn-In, from more complex two-on-one maneuvers for this reason, two hidden layers were incorporated. These sequences serve as the symbolic input to the artificial neural network we have provided. Additional information can be used to establish which of the several alternative behaviors will actually take place. This method has been used to describe the forms of relationships between accelerations and velocities (not the values themselves.) All possible modes of a system can be identified while offering a complete parametrization of all possible tactical maneuvers. We find that the resulting sequences of vectors uniquely express the time evolution of interacting dynamic objects. We have broken our central dynamical problem down into several smaller subproblems (“eigencurves”), which describe the states of a continuous-trajectory dynamic system. This problem is solved using a qualitative representation of the maneuvers and their implementation as a neural network. The problem involves prediction and identification of continuous-trajectory air combat maneuvers where only partial/incomplete information is given. The goal of this paper is to consider, formulate, and solve prediction problems encountered in tactical air combat.
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