C语言编程在智能化重力加速度测试仪中的应用

在基于单片机的智能化重力加速度测试仪中采用Ｃ语言编程简化了程序设计任务，对于汇编语言难于处理的浮点数运算及汉字打印输出可通过Ｃ语言编译器的内部库函数调用实现，介绍了一种专为８０５１系列单片机设计的Ｃ语言编译器Ｆｒａｎｋｉｌｉｎ Ｃ５１，它具有代码优化功能，能产生极高效率的机器码，并且提供了丰富的内部函数库。描述了Ｃ５１函数库所支持的ＩＥＥＥ标准浮点数的内存格式以及采用ｓｐｒｉｎｔｆ（）函数处理包括     

A Refinement Calculus for Shared-Variable Parallel and Distributed Programming

Parallel computers have not yet had the expected impact on mainstream computing. Parallelism adds a level of complexity to the programming task that makes it very error-prone. Moreover, a large variety of very different parallel architectures exists. Porting an implementation from one machine to another may require substantial changes. This paper addresses some of these problems by developing a formal basis for the design of parallel programs in the form of a refinement calculus. The calculus allows the stepwise formal derivation of an abstract, low-level implementation from a trusted, high-level specification. The calculus thus helps structuring and documenting the development process. Portability is increased, because the introduction of a machine-dependent feature can be located in the refinement tree. Development efforts above this point in the tree are independent of that feature and are thus reusable. Moreover, the discovery of new, possibly more efficient solutions is facilitated. Last but not least, programs are correct by construction, which obviates the need for difficult debugging. Our programming/specification notation supports fair parallelism, shared-variable and message-passing concurrency, local variables and channels. The calculus rests on a compositional trace semantics that treats shared-variable and message-passing concurrency uniformly. The refinement relation combines a context-sensitive notion of trace inclusion and assumption-commitment reasoning to achieve compositionality. The calculus straddles both concurrency paradigms, that is, a shared-variable program can be refined into a distributed, message-passing program and vice versa. Received July 2001 / Accepted in revised form May 2002     

Best L1 Piecewise Monotonic Data Modelling

Let us consider n data measurements of a univariate process that have been altered by random errors. We assume that an underlying model function has a substantially smaller number of turning points than the observed ones. We propose algorithms that make least the sum of the moduli of the errors by requiring k monotonic sections, alternately increasing and decreasing, in the sequence of the smoothed values. The main difficulty in this calculation is that the optimal positions of the joins of the monotonic sections have to be found automatically among so many combinations that it is impossible to test each one separately. Moreover, the calculation seems to be very intractable to general optimization techniques because O(n^k) local minima can occur. It is shown that dynamic programming can be used for separating the data into optimal disjoint sections of adjacent data, where each section requires a single L₁ monotonic calculation. This procedure is highly efficient, requiring at most O(kn²) computer operations and O(n) best L₁ monotonic calculations to subranges of data for a global minimum.     

Running programs backwards: The logical inversion of imperative computation

Imperative programs can be inverted directly from their forward-directed program code with the use of logical inference. The relational semantics of imperative computations treats programs as logical relations over the observable state of the environment, which is taken to be the state of the variables in memory. Program relations denote both forward and backward computations, and the direction of the computation depends upon the instantiation pattern of arguments in the relation. This view of inversion has practical applications when the relational semantics is treated as a logic program. Depending on the logic programming inference scheme used, execution of this relational program can compute the inverse of the imperative program. A number of nontrivial imperative computations can be inverted with minimal logic programming tools.     

Practical method for generation expansion planning based on dynamic programming

This paper presents an efficient method which provides the optimal generation mix and the optimal generation construction process. The approximation method in which the dynamic programming technique and gradient method are combined is applied to determine the optimal generation mix with hydropower generation technologies. The successive approximations dynamic programming (SADP) technique, which is very suitable for high-dimensional multistage decision process problems, is used for obtaining the optimal generation construction process. The effectiveness and feasibility of the developed technique are demonstrated on a practical power system model which has five types of generation technologies including a hydropower generation technology.     

二阶A型Cooper变换的增强型

对二阶Ａ型Ｃｏｏｐｅｒ变换进行增强，放宽可用性条件，并证明了其正确性，最后举例说明其应用。     

Object-extending class transformations

Reorganisation and evolution of class hierarchies is important for object-oriented system development and has received considerable attention in the literature. The contributions of this paper are: (1) a formal study of a set of extension relations and transformations on class hierarchies; (2) a presentation of a small set of primitive transformations which form a minimal and complete basis for the extension relations; and (3) an analysis of the impact of these transformations at the object level.The study leads to a better understanding of evolution and reuse of object-oriented software and class hierarchies. It also provides a terminology and a means of classification for design reuse. The theory presented in this paper is based on the Demeter data model, which gives a concise mathematical foundation for classes and their inheritance and part-of relationships. Parts of the theory have been implemented in the Demeter System ^TM C++, a CASE tool for object-oriented design and programming.     

Application of Differential Evolution for Irrigation Planning: An Indian Case Study

The present paper demonstrates the applicability of population based search optimization method, namely, Differential Evolution (DE) to a case study of Mahi Bajaj Sagar Project (MBSP), India. Ten different strategies of DE are employed to assess the ability of DE for solving higher dimensional problems as an alternative methodology for irrigation planning. The parameters considered in DE are population size, crossover constant and weighting factor. Linear Programming (LP) is utilized as a comparative approach to assess the ability of DE. Comparison of results of LP and the 10 DE strategies for the given parameters indicated that both the results are comparable even for high dimensional problems. Extensive sensitivity analysis studies, performed for 3,600 combinations of above parameters for the 10 DE strategies suggested that DE/rand-to-best/1/bin strategy is the best strategy giving maximum benefits taking minimum CPU time. It is concluded that DE can be utilized for efficient planning of any irrigation system with suitable modifications.     

浅谈程序设计中一题多解的教学方法

中等职业学校一般开设VB、VC及数据库等涉及程序设计的计算机课程。本文拟就程序设计中一题多解的教学方法进行探讨。     

模糊规划在炼油厂生产计划优化中的应用

生产计划的编制是炼油化工企业生产经营管理中的一个关键环节，然而由于市场变化的不确定性，使得企业的长远规划制定受到限制，笔者将模糊数学应用于炼厂生产计划的编制，通过模糊规划对炼油企业生产计划进行优化，使编得的生产计划在一定程度上反映市场的变化并使企业的生产效益最优，为企业管理决策者进行长期规划给予指导，给出了实例来说明该方法的可行性。