The federal financing of large-scale engineering projects
Abstract The financial condition of the federal government can not be a source of comfort to the managers of large-scale projects. On the one hand, a gradual absorption of the large deficits into a growing economy increases the financial risks of large projects. On the other hand, the significant cuts in federal spending are likely to fall disproportionately on these same projects. As a result strategic thinking about such ventures will need to include: a) financial mechanisms that place greater reliance on private resources, states and localities and, with that reliance, allow greater non-federal participation in project design and management; b) the way that the financial structure of a large-scale project can build and nurture the coalition of interests essential for its survival; c) the concept that a large scale project is a provider of services, rather than an object of intrinsic value; and d) meshing the financial and technological characteristics of a macro-engineering project with these new realities.
The Space Shuttle Program: A Policy Failure?
The 5 January 1972 announcement by President Richard Nixon that the United States would develop during the 1970's a new space transportation system—the space shuttle—has had fundamental impacts on the character of U.S. space activities. In retrospect, it can be argued that the shuttle design chosen was destined to fail to meet many of the policy objectives established for the system; the shuttle's problems in serving as the primary launch vehicle for the United States and in providing routine and cost-effective space transportation are in large part a result of the ways in which compromises were made in the 1971-72 period in order to gain White House and congressional approval to proceed with the program. The decision to develop a space shuttle is an example of a poor quality national commitment to a major technological undertaking.
A Short-Term and High-Resolution Distribution System Load Forecasting Approach Using Support Vector Regression With Hybrid Parameters Optimization
This paper proposes an approach for distribution system load forecasting, which aims to provide highly accurate short-term load forecasting with high resolution utilizing a support vector regression (SVR) based forecaster and a two-step hybrid parameters optimization method. Specifically, because the load profiles in distribution systems contain abrupt deviations, a data normalization is designed as the pretreatment for the collected historical load data. Then an SVR model is trained by the load data to forecast the future load. For better performance of SVR, a two-step hybrid optimization algorithm is proposed to determine the best parameters. In the first step of the hybrid optimization algorithm, a designed grid traverse algorithm (GTA) is used to narrow the parameters searching area from a global to local space. In the second step, based on the result of the GTA, particle swarm optimization is used to determine the best parameters in the local parameter space. After the best parameters are determined, the SVR model is used to forecast the short-term load deviation in the distribution system. The performance of the proposed approach is compared to some classic methods in later sections of this paper.