Explores whether flexible nonlinear models (including neural networks and genetic algorithms) can reveal otherwise unexpected patterns of relationship in typical school-productivity data. Applying three types of algorithms alongside regression modeling to school-level data in 183 elementary schools proves the hypothesis and reveals new directions…

Applies neural network methods for forecasting 1991-95 per-pupil expenditures in U.S. public elementary and secondary schools. Forecasting models included the National Center for Education Statistics' multivariate regression model and three neural architectures. Regarding prediction accuracy, neural network results were comparable or superior to…

Presents algorithms for the simulation and motion display of the three basic kinematic devices: (1) four bar linkages; (2) the slider crank; and (3) the inverted slider crank mechanisms. The algorithms were implemented on a Commodore-VIC 20 microcomputer system with 6500 bytes of available memory. (Author/JN)