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Qifan Wang, ; Sterman, John D.
doi: 10.1177/003754978504500104pmid: N/A
A disaggregate population model of China is presented: the age structure is represented by one-year cohorts; urban and rural populations are distinguished; birth and death rates, family size, life expectancy, and other demographic variables are determined endogenously. The model can be used to analyze population problems and to project population size, the age structure, the adult labor force, the elderly population, and so on. The model can be used in two modes: to project the consequences of various exogenous fertility levels and to determine endogenously birth rates and fertility by economic inputs such as food supply, GDP, and services. Socioeconomic factors important in the demo graphic transition are incorporated into the model, such as the effect of perceived life expectancy on fertility, the effects of tradi tional values, and the ability of government to influence family fertility choices. Policies and programs designed to control population growth, such as delayed marriage age, improved con traception, and restrictions on family size can be evaluated.Required inputs are industrial, service, and food output per worker, and also the level of pollution. The model should be thought of as a component of a comprehensive planning model which generates these inputs endogenously.Based on the system dynamics approach to modeling complex systems, the model is implemented in the DYNAMO simulation language.
doi: 10.1177/003754978504500105pmid: N/A
An elegant and well-developed theory exists for solving systems of linear equations. It has been applied successfully for decades in industrial and scientific applications and it forms the basis for linear programming. However many systems of linear equations for industrial applications may require all of the variables to be nonnegative or in an even more restricted area, and/or to be whole numbers. These conditions can create difficulties for the standard approach. So presented here is a new absolute value transformation and a multi-stage Monte Carlo simulation solu tion technique for dealing with the nonnegativity solution re quirement and other conditions. The new approach has the ad ditional advantage of working on nonlinear problems. The system of equations is transformed into a statistic (where the minimum of the statistic is the solution of the system). Then solving the system of equations becomes a problem of finding a way across the sampling distribution to the minimum, which will solve the system of equations.Regular Monte Carlo simulation to solve a system or optimiza tion problem suffers from only being able to roughly approx imate the answer. Multi-stage Monte Carlo simulation overcomes this obstacle by using a more sophisticated sampling scheme and additionally exploiting the well-behaved nature of the sampling distributions of transformed systems of equations.
Bailey, Patrick G.; Kopp, Harold J.; Cordes, Gail
doi: 10.1177/003754978504500106pmid: N/A
A BSTRACT The DATATRAN data base and executive program is currently under development by the Electric Power Research Institute (EPRI) for use and application by the nuclear utility industry. Since 1966, the computer code system has been under develop ment and has been extensively used by the Naval Reactors Pro gram. DATATRAN is being developed for use in a large number of general applications, including: (1) storage of experimental and plant transient data in hierarchical data set form, (2) auto matically linking data sets between computer codes, and (3) act ing as a program executive in executing series of computer codes while maintaining organization of the data between all of the codes. Various potential uses of the DATATRAN system, specific applications, and future research and development plans are reviewed in this paper.
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