Physical Sciences and Mathematics Commons^™

Investigations of aircrew sustained operations (SUSOPS) have been criticized for employing tasks with no apparent

external validity. Because measures obtained directly from aviators flying high-performance aircraft are difficult to

obtain, a laboratory compromise is needed. High-fidelity flight simulators used for aircrew training offer the most

realistic simulation, but their availability is limited. Personal computer-based flight simulators may provide adequate

simulation in, the laboratory at a rea.sonable cost. This report describes a representative research protocol using a

commercially available flight simulator during a simulated aircrew SUSOP.

The major difficulty in applicability of genetic algorithms to various optimization problems is the lack of general methodology for handling constraints. This paper discusses a new such methodology and presents results from the experimental system GENOCOP (for GEnetic algorithm for Numerical Optimization for COnstrainted Problems). The system not only handles any objective function with any set of linear constraints, but also effectively reduces the search space. The results indicate that this approach is superior to traditional methods when applied to the nonlinear transportation problem.

With many physical problems, measurement of spectral distribution, cosmic radiation, aerial and satellite imaging indirect sensing/recording devices are used. In many of these cases, the recording systems can be modeled by a Fredholm integral equation of the first kind. An inversion of the kernel representing a system, in the presence of noise, is an ill-posed problem. The direct inversion often yields an unacceptable solution. In this paper, we suggest an artificial neural network (ANN) architecture to solve certain kinds of ill-posed problems. The weights in the model are initialized using eigen-vectors and eigen-values of the kernel matrix that characterize the …