Comments on ‘A comparative study of ANN and neuro-fuzzy for the prediction of dynamic constant of rockmass’

Singh et al (2005) examined the potential of the ANN and neuro-fuzzy systems application for the prediction of dynamic constant of rockmass. However, the model proposed by them has some drawbacks according to fuzzy logic principles. This discussion will focus on the main fuzzy logic principles which authors and potential readers should take into consideration.     

Neural network prediction of nitrate in groundwater of Harran Plain, Turkey

Monitoring groundwater quality by cost-effective techniques is important as the aquifers are vulnerable to contamination from the uncontrolled discharge of sewage, agricultural and industrial activities. Faulty planning and mismanagement of irrigation schemes are the principle reasons of groundwater quality deterioration. This study presents an artificial neural network (ANN) model predicting concentration of nitrate, the most common pollutant in shallow aquifers, in groundwater of Harran Plain. The samples from 24 observation wells were monthly analysed for 1 year. Nitrate was found in almost all groundwater samples to be significantly above the maximum allowable concentration of 50 mg/L, probably due to the excessive use of artificial fertilizers in intensive agricultural activities. Easily measurable parameters such as temperature, electrical conductivity, groundwater level and pH were used as input parameters in the ANN-based nitrate prediction. The best back-propagation (BP) algorithm and neuron numbers were determined for optimization of the model architecture. The Levenberg–Marquardt algorithm was selected as the best of 12 BP algorithms and optimal neuron number was determined as 25. The model tracked the experimental data very closely (R = 0.93). Hence, it is possible to manage groundwater resources in a more cost-effective and easier way with the proposed model application.     

Numerical estimation of REV and permeability tensor for fractured rock masses by composite element method

The Monte Carlo method is used to generate parent stochastic discrete fracture network, from which a series of fractured rock samples of different sizes and orientations are extracted. The fracture network combined with a regular grid forms composite element mesh of the fractured rock sample, in which each composite element is composed of sub‐elements incised by fracture segments. The composite element method (CEM) for the seepage is implemented to obtain the nodal hydraulic potential as well as the seepage flow rates through the fractured rock samples. The application of CEM enables a large quantity of stochastic tests for the fractured rock samples because the pre‐process is facilitated greatly. By changing the sizes and orientations of the samples, the analysis of the seepage characteristics is realized to evaluate the variation of the permeability components, the existence of the permeability tensor and the representative element volume. The feasibility and effectiveness are illustrated in a numerical example. Copyright © 2008 John Wiley & Sons, Ltd.     

PSO-RBFNN模型及其在岩土工程非线性时间序列预测中的应用

岩土工程受力变形演化是一个典型的非线性问题,其演化的高度非线性和复杂性,很难用简单的力学、数学模型描述,但可用粒子群优化径向基神经网络对岩土工程应力、位移非线性时间序列进行动态实时预测。网络径向基层的单元数通过均值聚类法确定后,所有其它参数：中心位置、形状参数、网络权值,均通过粒子群优化算法在全局空间优化确定。工程实例应用表明,该模型预测结果准确、精度高,有良好的应用前景。     

基于AGA的SVM需水预测模型研究

需水预测是一个由城市人口、工业水平、社会经济水平共同作用的多因素、多层次的复杂非线性系统.其结果将直接影响受区域水资源承载力约束的产业结构、布局形态等决策.作为一种集中参数预报方法,支持向量机方法具有对未来样本的较好的泛化性能,对于这类资料缺乏、系统结构尚欠清晰的问题可以取得较好的模拟和预测结果.基于此,本文将支持向量机方法引入需水预测领域,建立了需水预测支持向量机模型.同时,本文将加速遗传算法和支持向量机方法耦合起来,构造了支持向量机模型参数的自适应优化算法.模型在珠海市的应用实例表明:与简单遗传算法比较,AGA的模型参数寻优效率更高;与BP神经网络模型相比,SVM模型较好地解决了小样本、经验性等问题,并取得了较高的预测精度.     

矿物数字博物馆的建设构想与实现

在基于互联网的应用、信息数字化、多种技术发展较为成熟及适应公众需求的基础上,对矿物数字博物馆的建设做了简要的分析,将矿物按矿物一结晶学分类方案将馆藏矿物进行合理的分类,设计了七大功能结构和相应的子结构,并对矿物所要展示的内容设定了标准.建设矿物数字博物馆旨在利用三维技术、多媒体技术、文字信息等,将矿物从宏观的外形到抽象的晶体形态和微观的晶体结构及其最小单位结构通过网络的形式具体展现给观众.矿物数字博物馆的建设可以为人们认知整个矿物世界搭建一个良好的平台,在科研教学、推动国民科学普及教育、培养创新人才方面发挥重要作用.     

Circulation in the Gulf of Aqaba (Red Sea) during winter—spring

This study is devoted to oceanographic features of the semi-enclosed Gulf of Aqaba, Red Sea. The data were recorded in winter—spring 1999 on the R/V Meteor cruise leg 44/2. Temperature and salinity profiles were measured at six positions (I—VI). The shipboard NarrowBand Acoustic Doppler Current Profiler (NB ADCP) 150 kHz continuously recorded current profiles down to 350 m en route. The research revealed that the current near the Strait of Tiran front (position VI) represents a semidiurnal signal of an internal tide wave (∼12 h period; 0.2 ms⁻¹ amplitude) that might be generated by the barotropic tide at the sill of the Strait. A sequence of cyclonic and anticyclonic eddy pairs is found along the axis of the Gulf of Aqaba during winter-spring seasons. These sub-mesoscale signals are dominant above the main thermocline and might be caused by wind forcing and the narrowness of the Gulf; it might remain in other seasons with different dimensions in relation to the depth of thermocline. The total diameter of each pair was twice the baroclinic Rossby radius (R ≈ 10 km). A single anti-cyclonic eddy was observed in the upper 300 m in the northern tip of the Gulf with a diameter of about 5–8 km.     

钢筋混凝土梁结构断裂损伤诊断方法

提出一种基于BP神经网络的结构破损诊断方法,该方法以结构破损前后柔度的变化作为破损诊断网络输入,为了解决由于系统响应样本数据空间分布不均匀对网络收敛速度及网络诊断影响问题,对网络训练样本采用广义空间格点进行了交换,模拟算例及应用实例均表明,本文方法能准确诊断结构破损位置与破坏程度,是一种有效的结构破损诊断方法.     

Modeling of Multi-Freedom Ship Motions in Irregular Waves with Fuzzy Neural Networks

1 .IntroductionAshiptravelingatseaundergoesundesirablewave inducedmotions ,namely ,surge ,sway ,heav ing ,rolling ,pitchingandyaw .Thesemotionsoftencauseproblemstothecrew ,theonboardequip mentand ,intheworstcase ,thesafetyofthevessel.Tominimizethewave inducedshipmotions ,controlsystemsmaybeapplied .Theaccuratemodelingofshipmotionsisthereforeveryimportantforshipdesignanddesignofmotioncontrolsystems .Manyresearchershavedevelopedshipmotionpredictionmethodsbasedonthepotentialflowtheo ries (Dong ,…     

Neural Network-Based Active Control for Offshore Platforms

1 .IntroductionWiththedevelopmentofoceantechnology ,moreandmoreextremelylargeandlongflexibleoff shoreplatformsusedforoilexplorationanddrillingoperationarebuiltinhostileoceanenvironments .Ingeneral,thiskindofplatformsisanonlineardistributedparametersystemanditsnaturalfrequencyfallsclosertothedominantwavefrequencieswiththeincreaseofwaterdepth .Besides ,itsstructureisverycomplexandtheexternalwaveforceontheplatformisuncertain .Thus ,theseplatformsarepronetoexcessivewave inducedoscillationsunderbot…