人工智能在冰雹识别及临近预报中的初步应用

基于广东10部S波段多普勒天气雷达的三维拼图资料,利用机器学习技术开发了一种冰雹识别和临近预报的人工智能算法。算法设计时以雷达回波反射率的垂直和水平扫描数据为基础训练集,将冰雹云的雷达反射率扫描数据作为正样本,将其他雷达反射率扫描数据作为负样本,通过贝叶斯分类法对正、负样本数据集进行机器学习,训练人工智能识别冰雹云内在规律的能力。训练时以广东省2008-2013和2015-2016年的数据作为训练集,使用了2014年广东省12次冰雹过程的数据做检验。对比检验的结果表明,人工智能法比传统的概念模型法击中率高9个百分点。研究结果表明了人工智能对冰雹这类非线性强天气过程具有较强的识别能力。      

Soft computing approach for real-time estimation of missing wave heights

This paper presents soft computing approach for estimation of missing wave heights at a particular location on a real-time basis using wave heights at other locations. Six such buoy networks are developed in Eastern Gulf of Mexico using soft computing techniques of Artificial Neural Networks (ANN) and Genetic Programming (GP). Wave heights at five stations are used to estimate wave height at the sixth station. Though ANN is now an established tool in time series analysis, use of GP in the field of time series forecasting/analysis particularly in the area of Ocean Engineering is relatively new and needs to be explored further. Both ANN and GP approach perform well in terms of accuracy of estimation as evident from values of various statistical parameters employed. The GP models work better in case of extreme events. Results of both approaches are also compared with the performance of large-scale continuous wave modeling/forecasting system WAVEWATCH III. The models are also applied on real time basis for 3 months in the year 2007. A software is developed using evolved GP codes (C++) as back end with Visual Basic as the Front End tool for real-time application of wave estimation model.     

Sea Level Prediction in the Yellow Sea From Satellite Altimetry With a Combined Least Squares-Neural Network Approach

Accessible high-quality observation datasets and proper modeling process are critically required to accurately predict sea level rise in coastal areas. This study focuses on developing and validating a combined least squares-neural network approach applicable to the short-term prediction of sea level variations in the Yellow Sea, where the periodic terms and linear trend of sea level change are fitted and extrapolated using the least squares model, while the prediction of the residual terms is performed by several different types of artificial neural networks. The input and output data used are the sea level anomalies (SLA) time series in the Yellow Sea from 1993 to 2016 derived from ERS-1/2, Topex/Poseidon, Jason-1/2, and Envisat satellite altimetry missions. Tests of different neural network architectures and learning algorithms are performed to assess their applicability for predicting the residuals of SLA time series. Different neural networks satisfactorily provide reliable results and the root mean square errors of the predictions from the proposed combined approach are less than 2?cm and correlation coefficients between the observed and predicted SLA are up to 0.87. Results prove the reliability of the combined least squares-neural network approach on the short-term prediction of sea level variability close to the coast.     

基于层次分析法的南麂列岛海域人工鱼礁社会效果评价

人工鱼礁建设具有生态效果、经济效果和社会效果。为科学指导人工鱼礁的建设方向,进一步促进海洋牧场建设以及海洋渔业资源和海洋生态环境的可持续发展,文章采用改进的层次分析法,从人工鱼礁与社会的适应性、对社会环境的影响、对社会生活的影响以及对其他行业发展的影响4个方面,选取政策符合性等10个评价指标,通过问卷调查的方式,对南麂列岛海域人工鱼礁的社会效果进行评价,填补该研究领域的空白。研究结果表明:根据各评价指标的权重和效果判定值,南麂列岛海域人工鱼礁产生了较好的社会效果,其中海洋生态环境、项目长远性、改善渔民生活质量和海洋捕捞业等指标发挥作用较大;未来将开展长期和连续的调查研究,提高评价可信度。     

常德-张家界高速公路某大桥桥基砂土液化评价

结合常德张家界高速公路某大桥桥基工程,在DSD160型电磁式振动三轴试验仪上,通过往返加荷三轴试验,对饱和砂土进行了液化试验研究,探讨了基于动三轴液化试验结果判断饱和砂土液化的方法。并尝试了这种室内研究反应分析的液化可能性估计方法与地震剪应力时程相结合的综合判断方法。在该高速公路大桥桥基的饱和砂土液化评价中,采用这种综合判断方法,对大桥桥基砂土液化进行了判断。在判断场地是否液化后,对其液化危害程度进行了等级划分,给出了该工程场地在未来遭受到不同超越概率下的地震作用时发生液化的危害程度,得到了一些有工程实用意义的结果。     

中国对虾(Fenneropenaeus Chinensis)自然感染与人工感染WSSV抗病力的比较

取30个通过人工授精和自然交尾建立的中国对虾家系,分别进行人工感染和自然感染实验。实验过程中,两实验组样本总体存活率在35%左右时统计各家系的存活率,以分析其抗白斑综合征病毒情况。用四格表的卡方检验分析中国对虾各家系存活率,结果发现23个家系的存活率在两种感染方式实验间差异不显著(P0.05),两种感染方式实验间家系存活率一致性为77%。用独立样本T检验对两种感染方式实验中4个杂交组合的存活率进行比较,结果发现4个杂交组合的存活率在两种感染方式实验间差异不显著(P0.05),说明人工感染和自然感染实验对中国对虾抗病力的反映情况基本是一致的。另外,对两个实验中各家系的抗病力进行分析,综合结果表明有5个家系对WSSV可能有较强的抗病力。     

人工育珠对三角帆蚌(Hyriopsis cumingii)遗传基因影响的初步研究

采用酚-氯仿和试剂盒两种提取法对三角帆蚌怀珠群与非怀珠群各6个个体进行基因组DNA的提取,然后在优化RAPD(随机扩增多态性DNA)检测条件基础上,从80个随机引物中筛选出12个扩增较好且多态性强的引物进行RAPD扩增,产物通过水平板琼脂糖凝胶电泳和垂直板聚丙烯酰胺凝胶电泳两种方法进行检验并对DNA的多态性进行分析。结果显示在怀珠群和非怀珠群检测到的位点数、多态位点比例、平均Shannon多态性信息指数、平均Nei's基因多样性指数、群体内个体间平均遗传相似率和平均遗传距离分别为100、33%、0.1927、0.1324、0.904、0.096,95、47.37%、0.2711、0.1879、0.861、0.139,群体间的平均遗传距离为0.821,非怀珠群的变异性大于怀珠群;本研究还获得了两群体各自的特异扩增谱带及两群体间表达差异较大谱带,这些位点很可能是由人工育珠所引起。根据MEGA4.0软件的UPGMA和NJ程序构建的分子系统树可直观地将两群体分开。     

Beach nourishments at Coolangatta Bay over the period 1987–2005: Impacts and lessons

Erosion of the southern Gold Coast beaches (SE Queensland, Australia) was exacerbated after the extension of the Tweed River training walls in the early 1960s. To achieve the objective of restoring and maintaining beach amenity, significant nourishment works have been undertaken in Coolangatta Bay over the past 30 years. Particularly, under the Tweed River Entrance Sand Bypassing Project (TRESBP) since 1995, a number of nourishment campaigns and the implementation of a permanent sand bypass system in 2001 have resulted in significant changes of Coolangatta Bay morphology. The present case study investigates the influence of both wave climate and nourishment works on the area extending from the updrift Snapper Rocks area to downdrift Kirra Beach. SWAN spectral wave model is implemented at Coolangatta Bay area and forced by the global wave model WW3 to estimate wave forcing and the potential natural longshore drift entering in Coolangatta. Specific transects extracted from accurate bathymetric surveys are used to investigate and quantify Coolangatta Bay sedimentation for the period 1987–2005. A network of Argus video stations provides high sample rate information on the shoreline evolution. Results show that, over the past 10 years, Coolangatta Bay has infilled rapidly. Sedimentation reached up to 6 m in some areas between 1995 and 2005, with beach width increasing by 200 m at Kirra Beach. Rapid seaward shoreline migration is consistent with the intense over-pumping of sand relative to the natural potential to move sand alongshore. The nourishment strategy used during this project has successfully delivered large amounts of sand to the southern Gold Coast embayment, although it has been up to now controversial from many community perspectives. The artificial sand bypassing process proved to be much more efficient than depositing the dredged sand in the nearshore area which requires a significant period of low energy condition in order for the deposited sediment to migrate shoreward and weld to the shore. This case study confirms that, when carefully undertaken, sand bypassing is a sustainable and flexible soft engineering approach which can work in concert with natural processes.     

日本鬼鱼由工厂化育苗技术研究

从北部湾沿海采捕的日本鬼鱼由 ( Inimicus japonicus)亲鱼 ,经暂养后进行催产 ,雌鱼每千克体重注射 L RH-A3 1 0μg DOM 5mg或 HCG 60 0～ 80 0 IU LRH-A3 3 0～ 4 0μg;雄鱼注射同样药物 ,剂量减半。共采卵 1 0 9万粒 ,平均受精率 89.0 % ,平均孵化率 90 .0 % ,共培育出体长 1 .8～ 2 .3 cm的幼鱼 2 6.8万尾 ,平均成活率 3 0 .7%。     

运用人工神经网络作汛期降水预报

本文提出汛期降水预报的人工神经网络方法，并选择一组标样进行了具体分析，预报成功率达100％，结果表明，该方法性能良好，可望成为汛期降水预报的有效手段。