企鹅珍珠贝人工苗生长的初步观察   总被引：3，自引：0，他引：3  

梁飞龙  毛勇  余祥勇 《广东海洋大学学报》2001,21(1):6-9

为了解企鹅珍珠贝生长规律，观察了壳高2.5～5.0mm的出池幼苗，按月测量其生长参数和成活率，以及环境因子。结果表明，企鹅珍珠贝生长最快的月份为7～11月和次年4～6月，壳长，壳高和壳宽月均增加量分别为3.8～13.0mm、4.7～11.2mm、2.3～3.8mm，月成活率97.8%～98.6%。企鹅珍珠贝生长最慢月份是11月至次年3月。  相似文献   

Neural network prediction of nitrate in groundwater of Harran Plain, Turkey   总被引：2，自引：0，他引：2  

M. Irfan Yesilnacar  Erkan Sahinkaya  Muhsin Naz  Bestamin Ozkaya 《Environmental Geology》2008,56(1):19-25

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.  相似文献   

Spatial Variability of Rock Depth in Bangalore Using Geostatistical, Neural Network and Support Vector Machine Models     

T. G. Sitharam  Pijush Samui  P. Anbazhagan 《Geotechnical and Geological Engineering》2008,26(5):503-517

Geospatial technology is increasing in demand for many applications in geosciences. Spatial variability of the bed/hard rock is vital for many applications in geotechnical and earthquake engineering problems such as design of deep foundations, site amplification, ground response studies, liquefaction, microzonation etc. In this paper, reduced level of rock at Bangalore, India is arrived from the 652 boreholes data in the area covering 220 km². In the context of prediction of reduced level of rock in the subsurface of Bangalore and to study the spatial variability of the rock depth, Geostatistical model based on Ordinary Kriging technique, Artificial Neural Network (ANN) and Support Vector Machine (SVM) models have been developed. In Ordinary Kriging, the knowledge of the semi-variogram of the reduced level of rock from 652 points in Bangalore is used to predict the reduced level of rock at any point in the subsurface of the Bangalore, where field measurements are not available. A new type of cross-validation analysis developed proves the robustness of the Ordinary Kriging model. ANN model based on multi layer perceptrons (MLPs) that are trained with Levenberg–Marquardt backpropagation algorithm has been adopted to train the model with 90% of the data available. The SVM is a novel type of learning machine based on statistical learning theory, uses regression technique by introducing loss function has been used to predict the reduced level of rock from a large set of data. In this study, a comparative study of three numerical models to predict reduced level of rock has been presented and discussed.  相似文献   

Freely floating-body simulation by a 2D fully nonlinear numerical wave tank     

Weoncheol Koo  Moo-Hyun Kim 《Ocean Engineering》2004,31(16):221-2046

Nonlinear interactions between large waves and freely floating bodies are investigated by a 2D fully nonlinear numerical wave tank (NWT). The fully nonlinear 2D NWT is developed based on the potential theory, MEL/material-node time-marching approach, and boundary element method (BEM). A robust and stable 4th-order Runge–Kutta fully updated time-integration scheme is used with regriding (every time step) and smoothing (every five steps). A special φ_n-η type numerical beach on the free surface is developed to minimize wave reflection from end-wall and wave maker. The acceleration-potential formulation and direct mode-decomposition method are used for calculating the time derivative of velocity potential. The indirect mode-decomposition method is also independently developed for cross-checking. The present fully nonlinear simulations for a 2D freely floating barge are compared with the corresponding linear results, Nojiri and Murayama’s (Trans. West-Jpn. Soc. Nav. Archit. 51 (1975)) experimental results, and Tanizawa and Minami’s (Abstract for the 6th Symposium on Nonlinear and Free-surface Flow, 1998) fully nonlinear simulation results. It is shown that the fully nonlinear results converge to the corresponding linear results as incident wave heights decrease. A noticeable discrepancy between linear and fully nonlinear simulations is observed near the resonance area, where the second and third harmonic sway forces are even bigger than the first harmonic component causing highly nonlinear features in sway time series. The surprisingly large second harmonic heave forces in short waves are also successfully reproduced. The fully updated time-marching scheme is found to be much more robust than the frozen-coefficient method in fully nonlinear simulations with floating bodies. To compare the role of free-surface and body-surface nonlinearities, the body-nonlinear-only case with linearized free-surface condition was separately developed and simulated.  相似文献   

拖缆式验潮仪结构设计和实现     

王莉娜  刘保良  赵先龙  阮锐  邵海涛  严晓明 《海洋测绘》2006,26(6):68-70

以2003年完成定型生产并投入使用的新型号拖缆式验潮仪为例,简要介绍了设备的设计思想、实现方法和新特技术的应用,涉及到嵌入式计算机的选型、智能探头、汉字和图形人机界面、多路串行通讯、潮汐数据实时获取和系统在应用升级等设计细节。  相似文献   

智能潜器的集成仿真系统     

庞永杰  徐玉如  尚游  彭良 《海洋工程》1997,(4)

本文介绍了智能潜器集成仿真系统的硬、软件结构．通过这一系统所展示的水下虚拟仿真环境能够在研究和开发智能潜器的控制体系结构、潜器载体的水动力学、信息融合和目标识别等工作中发挥巨大作用  相似文献   

红树林遥感智能分类方法研究   总被引：13，自引：0，他引：13  

滕骏华  刘宇 《台湾海峡》1997,16(3):331-338

利用ＧＩＳ信息中的红树林地域分布规律作向导，充分利用械树林区的光谱信息进行红树林植被信息提取。在对比研究常规的红树林图象自理方法的基础上，提出了适用于红树林植被信息遥感监测的智能分类方法。  相似文献   

三疣梭子蟹全人工工厂化育苗技术     

孙玉忠  王雪梅  宋全山  王玉华  王磊 《海洋湖沼通报》2002,(3):76-79

2000年笔者在日照市水产研究所利用1450m^3水进行梭子蟹全人工工厂化育苗生产，共出Ⅱ-Ⅲ期幼蟹512．7万只，创造了出苗量为3500只／m^3，总产值为150多万元的直接经济效益，同时对幼体培育的密度进行了初步试验，结果表明：从Z1至M期幼体培育密度10－15万／m^3为宜，M期以后密度以0．8－1．5万／m^3为宜。  相似文献   

水下智能潜器的神经网络运动控制   总被引：10，自引：4，他引：10  

彭良  卢迎春  万磊  孙俊岭 《海洋工程》1995,(2)

本文介绍一种基于神经网络的水下智能潜器的运动控制方法，该方法通过在线学习，融控制与滤波为一体。计算机仿真与水池实验验证表明，该方法的控制与滤波性能良好，对环境的学习与适应能力强。该方法事实上可用于一般动力系统的控制。  相似文献   

烧伤病人应用CHIMEHERB人工皮的临床评价     

唐晓熹  许伟石 《中国海洋大学学报(自然科学版)》1989,(Z3)

本研究初步评价CHIMEHERB人工皮的治疗效果.74例,105个创面应用人工皮:供皮区47个创面,愈合时间平均为9±1.94d(天),油纱布对照为11.7±1.93d(P<0.01);14个浅Ⅱ°新鲜创面,70％在3～5d内逐渐干燥与创面紧密粘附,平均愈合时间为9.8±3.09d;11个存留上皮组织的削痂深Ⅱ°创面,平均5.7±1.7d干燥,平均愈合时间为10.55±3.09d,不需植自体皮;8个削痂刨面至脂肪组织或切痂创面4～9d更植自体皮,其存活率近乎100％,2个创面因残留坏死组织而失败;人工皮应用于16个自体皮间隙创面,除三个网状植皮和一个条状植皮创面失败外,所植自体皮都在人工皮下扩展融合,未观察到占位现象;对后期残余小创面有良好的效果.本研究结果提示人工皮对创面愈合具有有利影响.主要适用于供皮区、浅Ⅱ°新鲜创面、深Ⅱ°脱痂和削痂后存留上皮组织较多的创面、自体皮间隙创面和后期残余小创面,不适宜于深Ⅲ°新鲜创面.  相似文献