人工神经网络在地质学判别分析中的应用

将现代人工神经网络方法应用于地质学的判别分析，通过实例计算表明，无论是对于两组判别分析还是多组判别分析，人工神经网络方法都是切实可行的。     

A Linear Programming Model for Seabed Oil-Gas Pipe Network

This paper analyzes the pipe network system of oil-gas collection and transportation foroffshore oilfield development.A"0-1"integer linear programming model is constructed to optimize theinvestment of seabed pipe network.The mathematical model is solved by the spanning tree method ofgraph theory and network analysis.All spanning trees of a network graph compose all the feasible solu-tions of the mathematical model.The optimal solution of the model is the spanning tree with the minimumcost among all spanning trees.This method can be used to optimize the seabed pipe network system andgive a minimum cost plan for the development of offshore marginal oilfield groups.     

应用遗传神经网格方法分析赤潮监测数据

简要介绍了遗传神经网络方法的原理 ,探讨了应用遗传神经网络方法研究辽东湾海域丹麦细柱藻 (Leptocylindrusdanicus)赤潮与其环境因子之间的关系 ,计算了各环境因子对丹麦细柱藻赤潮的贡献。结果表明 ,温度、盐度、DIN的变化对研究海域丹麦细柱藻种群密度的增长有比较重要的影响 ,DIN是营养限制因子。遗传神经网络是分析赤潮监测数据的有效方法 ,值得进一步探索     

Neural network for wave forecasting among multi-stations

Unlike in the open sea, the use of wind information for forecasting waves may encounter more ambiguous uncertainties in the coastal or harbor area due to the influence of complicated geometric configurations. Thus this paper attempts to forecast the waves based on learning the characteristics of observed waves, rather than the use of the wind information. This is reported in this paper by the application of the artificial neural network (ANN), in which the back-propagation algorithm is employed in the learning process for obtaining the desired results. This model evaluated the interconnection weights among multi-stations based on the previous short-term data, from which a time series of waves at a station can be generated for forecasting or data supplement based on using the neighbor stations data. Field data are used for testing the applicability of the ANN model. The results show that the ANN model performs well for both wave forecasting and data supplement when using a short-term observed wave data.     

海底油气集输管网可靠性评估

对海底油气集输管网进行了可靠性评估，提出了一种适用于树状海底油气集输管网可靠性评价的方法，将流可靠度和单元重要度的概念引入到海底油气集输管网可靠性的分析中，该方法能够有效地评价海底油气集输管网的可靠性。     

一种基于异步串行口的IBM-PC局部网

在综合的科学考察船上以异步通讯口实现的IBM-PC局部网具有较好的性能价格比。本文介绍了该网的联网环境、网络系统的组成及其拓扑结构、网络的服务功能以及网络软、硬件的安装和配置。     

可靠性约束下的海底油气集输管网系统优化

在管网系统满足一定可靠度的基础上，以费用最小为优化目标，对系统进行了优化，求出了满足一定可靠度指标的费用最小的管网布置方案。对树状网络可靠性进行了评估，提出了一个0-l规划模型，并运用图论和网络理论将管网系统的优化问题转变为求可靠度至少为α的网络固的最小生成树问题。     

The Vema Transverse Ridge (Central Atlantic)

Transverse ridges are elongate reliefs running parallel and adjacent to transform/fracture zones offsetting mid-ocean ridges. A major transverse ridge runs adjacent to the Vema transform (Central Atlantic), that offsets the Mid-Atlantic Ridge by 320 km. Multibeam morphobathymetric coverage of the entire Vema Transverse ridge shows it is an elongated (300 km), narrow (<30 km at the base) relief that constitutes a topographic anomaly rising up to 4 km above the predicted thermal contraction level. Morphology and lithology suggest that the Vema Transverse ridge is an uplifted sliver of oceanic lithosphere. Topographic and lithological asymmetry indicate that the transverse ridge was formed by flexure of a lithospheric sliver, uncoupled on its northern side by the transform fault. The transverse ridge can be subdivided in segments bound by topographic discontinuities that are probably fault-controlled, suggesting some differential uplift and/or tilting of the different segments. Two of the segments are capped by shallow water carbonate platforms, that formed about 3–4 m.y. ago, at which time the crust of the transverse ridge was close to sea level. Sampling by submersible and dredging indicates that a relatively undisturbed section of oceanic lithosphere is exposed on the northern slope of the transverse ridge. Preliminary studies of mantle-derived ultramafic rocks from this section suggest temporal variations in mantle composition. An inactive fracture zone scarp (Lema fracture zone) was mapped south of the Vema Transverse ridge. Based on morphology, a fossil RTI was identified about 80 km west of the presently active RTI, suggesting that a ridge jump might have occurred about 2.2 m.a. Most probable causes for the formation of the Vema Transverse ridge are vertical motions of lithospheric slivers due to small changes in the direction of spreading of the plates bordering the Vema Fracture Zone.     

Magnetic anomalies in the canary basin and the Mesozoic evolution of the central North Atlantic

The data from a recent magnetic compilation by Verhoefet al. (1991) off west Africa were used in combination with data in the western Atlantic to review the Mesozoic plate kinematic evolution of the central North Atlantic. The magnetic profile data were analyzed to identify the M-series sea floor spreading anomalies on the African plate. Oceanic fracture zones were identified from magnetic anomalies and seismic and gravity measurements. The identified sea floor spreading anomalies on the African plate were combined with those on the North American plate to calculate reconstruction poles for this part of the central Atlantic. The total separation poles derived in this paper describe a smooth curve, suggesting that the motion of the pole through time was continuous. Although the new sea floor spreading history differs only slightly from the one presented by Klitgord and Schouten (1986), it predicts smoother flowlines. On the other hand, the sea floor spreading history as depicted by the flowlines for the eastern central Atlantic deviates substantially from that of Sundvik and Larson (1988). A revised spreading history is also presented for the Cretaceous Magnetic Quiet Zone, where large changes in spreading direction occurred, that can not be resolved when fitting magnetic isochrons only, but which are evident from fracture zone traces and directions of sea floor spreading topography.Deceased 11 November 1991     

Prediction of Load Carrying Capacity of Corroded Reinforced Concrete Beam

A novel method for prediction of the load carrying capacity of a corroded reinforced concrete beam (CRCB) is presented in the paper. Nine reinforced concrete beams, which had been working in an aggressive environment for more than 10 years, were tested in the laboratory. Comprehensive tests, including flexural test, strength test for corroded concrete and rusty rebar, and pullout test for bond strength between concrete and rebar, were condueted. The flexural test results of CRCBs reveal that the distribution of surface cracks on the beams shows a fractal behavior. The relationship between the fractal dimensions and mechanical properties of CRCBs is then studied. A prediction model based on artificial neural network (ANN) is established by the use of the fractal dimension as the corrosion index, together with the basic intbrmation of the beam. The validity of the prediction model is demonstrated through the experimental data, and satisfactory resuits are achieved.