预测水驱油田开发动态的一种方法

水驱曲线法和数学模型法都是油藏工程中的重要方法，前者主要用于在一定的经济含水条件下预测水驱油田的可采储量和采收率，后者主要用于预测不同类型油田的产量、累积产量和一定经济极限产量下的可采储量。然而，前者与时间序列无关，后者与含水率序列无关，都有局限性。提出丙型水驱曲线公式与ＨＣＺ数学模型公式联解预测法，不但可以预测水驱油田产量、累积产量、含水率随时间的变化，还可预测可采储量、可动油储量和水驱波及体积系数的变化。图３表１参１２（陈志宏摘）     

Response level crossing rate of a linear system excited by a partially specified Gaussian load process

The problem of determining the maximum mean response level crossing rate of a linear system driven by a partially specified Gaussian load process has been considered. The partial specification of the load is given only in terms of its total average energy. The critical input power spectral (PSD) function, which maximizes the mean response level crossing rate, is obtained. The critical input PSD turns out to be highly narrow-banded which fails to capture the erratic nature of the excitation. Consequently, the trade-off curve between the maximum mean response level crossing rate and the maximum disorder in the input process, quantified in terms of its entropy rate, has been generated. The method of Pareto optimization is used to tackle the conflicting objectives of the simultaneous maximization of the mean response level crossing rate and the input entropy rate. The non-linear multi-objective optimization has been carried out using a recently developed multi-criteria genetic algorithm scheme. Illustrative example of determining the critical input of an axially vibrating rod, excited by a partially specified stationary Gaussian load process, has been considered.     

最小生成树的高效异步并行算法

在ＭＩＭＤ－ＳＭ并行计算模型上，本文给出了时间复杂性为Ｏ（ｎ（ｎ／ｐ＋ｌｏｇｐ））的最小生成树的异步并行算法，其中ｎ，ｐ（１≤ｐ≤ｎ）分别表示图的顶点数和处理机的个数。     

A Search for Hidden Relationships: Data Mining with Genetic Algorithms

This paper presents an algorithm that permits the search for dependencies among sets of data (univariate or multivariate time-series, or cross-sectional observations). The procedure is modeled after genetic theories and Darwinian concepts, such as natural selection and survival of the fittest. It permits the discovery of equations of the data-generating process in symbolic form. The genetic algorithm that is described here uses parts of equations as building blocks to breed ever better formulas. Apart from furnishing a deeper understanding of the dynamics of a process, the method also permits global predictions and forecasts. The algorithm is successfully tested with artificial and with economic time-series and also with cross-sectional data on the performance and salaries of NBA players during the 94–95 season.     

Machine assignment and part-families formation using group technology

The conventional way of solving the group technology (GT) problem is to start from an assignment of parts to machines and try to find a partitioning of machine cells and part families. The similarity between parts is measured based on commonality of the machines assigned to them. However, parts are assigned to machines based on their operation requirements and the operation capabilities of machines. Similarity between parts should be based on their required operations. In this paper, the authors attempt to solve or facilitate solving the GT problem at the assignment level. An algorithm for assigning parts to machines is provided which utilizes the types of operations required by parts and applies GT principles in producing the assignment. This leads to better partitioning of machine cells and part-families. Furthermore, operation sequences required by parts in determining the similarity between parts have been considered. An algorithm to form part-families based on the operation sequence similarity coefficient has been developed. The resulting families are then used by the assignment algorithm to produce machine assignments to part-families. The use of the algorithm is demonstrated by examples.     

Adaptive solutions to the mutual exclusion problem

Summary Algorithms for mutual exclusion that adapt to the current degree of contention are developed. Afilter and a leader election algorithm form the basic building blocks. The algorithms achieve system response times that are independent of the total number of processes and governed instead by the current degree of contention. The final algorithm achieves a constant amortized system response time. Manhoi Choy was born in 1967 in Hong Kong. He received his B.Sc. in Electrical and Electronic Engineerings from the University of Hong Kong in 1989, and his M.Sc. in Computer Science from the University of California at Santa Barbara in 1991. Currently, he is working on his Ph.D. in Computer Science at the University of California at Santa Barbara. His research interests are in the areas of parallel and distributed systems, and distributed algorithms. Ambuj K. Singh is an Assistant Professor in the Department of Computer Science at the University of California, Santa Barbara. He received a Ph.D. in Computer Science from the University of Texas at Austin in 1989, an M.S. in Computer Science from Iowa State University in 1984, and a B.Tech. from the Indian Institute of Technology at Kharagpur in 1982. His research interests are in the areas of adaptive resource allocation, concurrent program development, and distributed shared memory.A preliminary version of the paper appeared in the 12th Annual ACM Symposium on Principles of Distributed ComputingWork supported in part by NSF grants CCR-9008628 and CCR-9223094     

Influence of Missing Values on the Prediction of a Stationary Time Series

Abstract. The influence of missing observations on the linear prediction of a stationary time series is investigated. Simple bounds for the prediction error variance and asymptotic behaviours for short and long‐memory processes respectively are presented.     

A novel dynamic survivable routing in WDM optical networks with/without sparse wavelength conversion

In this paper, we study the dynamic survivable routing problem, both in optical networks without wavelength conversion and in optical networks with sparse wavelength conversion, and propose a novel hybrid algorithm for it based on the combination of mobile agents technique and genetic algorithms (GA). By keeping a suitable number of mobile agents in the network to cooperatively explore the network states and continuously report cycles (that are formed by two disjoint-link routes) into the routing tables, our new hybrid algorithm can promptly determine the first population of cycles for a new request based on the routing table of its source node, without the time consuming process associated with current GA-based lightpath protection schemes. We further improve the performance of our algorithm by introducing a more advanced fitness function that is suitable for both the above networks. Extensive simulation studies on the ns-2 network simulator show that our hybrid algorithm achieves a significantly lower blocking probability than the conventional survivable routing algorithms for all the cases we studied.     

从数据结构角度设计导游系统

从数据结构角度为旅游胜地设计导游系统。向游人提供景点的信息查询服务,根据指定的景点提供相关的景点信息。任意给定起点和终点,查询两点之间的最短路径。     

Simple algorithms for searching a polygon with flashlights

The k-searcher is a mobile guard whose visibility is limited to k rays emanating from her position, where the direction of each ray can be changed continuously with bounded angular rotation speed. Given a polygonal region P, is it possible for the k-searcher to eventually see a mobile intruder that is arbitrarily faster than the searcher within P? We present O(n²)-time algorithms for constructing a search schedule of the 1-searcher and the 2-searcher, respectively. Our framework for the 1-searcher can be viewed as a modification of that of LaValle et al. [Proc. 16th ACM Symp. on Computational Geometry, 2000, pp. 260-269] and is naturally extended for the 2-searcher.