体育竞赛结果的预测模型

讨论体育竞赛结果的预测问题。应用概率论与多目标最优化的方法,导出了预测结果的计算公式。     

复杂模型EEAC法稳定域的解析计算

提出一种在复杂模型下应用ＥＥＡＣ法时暂态稳定域的计算方法，得出了等值单机无穷大系统总的加速面积为相当于发电机暂态电势保持其初始值不变时的加速面积与反映电扩附加面积之和的结论，首次较精确地定量计及了这部分变化的面积，在复杂模型下完全保留了ＥＥＡＣ法的全解析性。     

气退式航炮两级缓冲器的计算机辅助设计

本文介绍了气退式航炮两级缓冲器计算机辅助设计的基本原理、主要功能部件和数理模型,以及在此基础上编制的计算机数字仿真程序。文中最后介绍了仿真运算中定点逼近的自动变步长方法。     

Equivalent turbogenerator model for design of multivariable controllers in multimachine systems

The design of multivariable controllers for turbogenerators is usually based on single-machine infinite-bus representations, which are not valid for multimachine power systems. Alternatively, an overall control strategy may be sought for all the generators in the system, but this arrangement is not feasible in practice and involves major mathematical difficulties. The paper describes a method for designing physically-realizable multivariable controllers for individual turbogenerators in multimachine systems, without the assumption of an infinite bus. This employs an equivalent model for each generator, which includes the effects of interconnections with other units in the power system. The method has been used to design optimal state-space controllers for a three-machine system, and results obtained by nonlinear computer simulation show that good performance is achieved.     

Policy analysis model of a large electrical supply system

A simulation model of the capacity-acquisition process in a large electricity-supply system is described, and its output is compared with the actual behavior of the system. The model was built to be used in the testing and assessment of alternative capacity-acquisition policies, particularly the demand-forecasting element of such policies. A simple experiment is described that indicates that the performance of the acquisition policy is sensitive to relatively small changes in the forecasting technique employed. The value of the model in corporate planning is considered briefly.     

Results of test on microprocessor-based voltage and speed regulators carried out on a large physical model complex

Results of experimental tests carried out with microprocessor-based voltage and speed regulators using a digital-analogue-physical model complex of a large power system at the Siberian Power Institute of the USSR Academy of Sciences are described. The physical test facility, and the test objectives and procedures are also outlined. Tests were carried out on a Soviet-built microprocessor AVR and a Canadian-built microprocessor AVR and speed governor. The work described shows that the development of speed and voltage regulators using microprocessors is a feasible and promising proposition.     

An integration architecture for the automation of a continuous production complex

The development of integrated automation systems for continuous production plants is a very complicated process. A variety of factors must be taken into account, such as their different components (e.g., production units control systems, planning systems, financial systems, etc.), the interaction among them, and their different behavior (continuous or discrete). Moreover, the difficulty of this process is increased by the fact that each component can be viewed in a different way depending on the kind of decisions to be made, and its specific behavior. Modeling continuous production complexes as a composition of components, where, in turn, each component may also be a composite, appears to be the simplest and safest way to develop integrated automation systems. In order to provide the most versatile way to develop this kind of system, this work proposes a new approach for designing and building them, where process behavior, operation conditions and equipment conditions are integrated into a hierarchical automation architecture.     

An intelligent system for multivariate statistical process monitoring and diagnosis

A knowledge-based system (KBS) was designed for automated system identification, process monitoring, and diagnosis of sensor faults. The real-time KBS consists of a supervisory system using G2 KBS development software linked with external statistical modules for system identification and sensor fault diagnosis. The various statistical techniques were prototyped in MATLAB, converted to ANSI C code, and linked with the G2 Standard Interface. The KBS automatically performs all operations of data collection, identification, monitoring, and sensor fault diagnosis with little or no input from the user. Navigation throughout the KBS is via menu buttons on each user-accessible screen. Selected process variables are displayed on charts showing the history of the variables over a period of time. Multivariate statistical tests and contribution plots are also shown graphically. The KBS was evaluated using simulation studies with a polymerization reactor through a nonlinear dynamic model. Both normal operation conditions as well as conditions of process disturbances were observed to evaluate the KBS performance. Specific user-defined disturbances were added to the simulation, and the KBS correctly diagnosed both process and sensor faults when present.     

A model of traffic crashes in New Zealand

The aim of this study was to examine the changes in the trend and seasonal patterns in fatal crashes in New Zealand in relation to changes in economic conditions between 1970 and 1994. The Harvey and Durbin (Journal of the Royal Statistical Society 149 (3) (1986) 187-227) structural time series model (STSM), an 'unobserved components' class of model, was used to estimate models for quarterly fatal traffic crashes. The dependent variable was modelled as the number of crashes and three variants of the crash rate (crashes per 10,000 km travelled, crashes per 1,000 vehicles, and crashes per 1000 population). Independent variables included in the models were unemployment rate (UER), real gross domestic product per capita, the proportion of motorcycles, the proportion of young males in the population, alcohol consumption per capita, the open road speed limit, and dummy variables for the 1973 and 1979 oil crises and seat belt wearing laws. UERs, real GDP per capita, and alcohol consumption were all significant and important factors in explaining the short-run dynamics of the models. In the long-run, real GDP per capita was directly related to the number of crashes but after controlling for distance travelled was not significant. This suggests increases in income are associated with a short-run reduction in risk but increases in exposure to a crash (i.e. distance travelled) in the long-run. A 1% increase in the open road speed limit was associated with a long-run 0.5% increase in fatal crashes. Substantial reductions in fatal crashes were associated with the 1979 oil crisis and seat belt wearing laws. The 1984 universal seat belt wearing law was associated with a sustained 15.6% reduction in fatal crashes. These road policy factors appeared to have a greater influence on crashes than the role of demographic and economic factors.     

Optimal design of radial basis function neural networks for fuzzy-rule extraction in high dimensional data

The design of an optimal radial basis function neural network (RBFNF) is not a straightforward procedure. In this paper we take advantage of the functional equivalence between RBFN and fuzzy inference systems to propose a novel efficient approach to RBFN design for fuzzy rule extraction. The method is based on advanced fuzzy clustering techniques. Solutions to practical problems are proposed. By combining these different solutions, a general methodology is derived. The efficiency of our method is demonstrated on challenging synthetic and real world data sets.