Mooring optimization of floating platforms using a genetic algorithm

This paper presents a new procedure for the optimization of the mooring design of floating platforms, in which an automatic design sequence is also established. Regarding the optimization philosophy, the following aspects are dealt with:

• The optimization of the platform heading and its mooring pattern, taking into account the environmental force spreading;

• optimum line length or line tension for each mooring line, associated to the optimization of the mooring line materials and sizes.

Basically, the main goal of this paper is to introduce a new method, which will provide the quickest way to find the best mooring system, defined here as that which minimizes platform responses.A genetic algorithm (GA) is applied in this contribution, and this paper describes exactly the procedure of developing a GA code directed toward the solution of mooring design optimization problems. In order to prove the efficiency and the vast potential of the proposed algorithm as a design tool, sample moorings are analyzed for different environmental conditions and the final results, including the time required to run them, are presented.     

日本海主要海峡体积输运的季节变化特征

利用变分资料同化技术对P矢量方法进行优化处理,并采用此优化后的P矢量方法优化计算了日本海环流和日本海主要海峡的体积输运.日本海的主要环流系统,比如对马暖流(TWC)及其分支,东朝鲜暖流(EKWC)和日本近岸分支(JNB),极地锋海流(PFC),和日本海中的反气旋式涡,都能够被很好地一一反映出来.另外,优化后的P矢量方法...     

LA‐ICP‐MS Analysis of Small Samples: Carbonate Reference Materials and Larval Fish Otoliths

This article proposes a methodology to analyse the composition of very small carbonate samples such as larval fish otoliths. The chemical composition of otoliths, which are carbonate structures in the inner ear, is often used to explore population dynamics in fishes. Recent advances in laser ablation‐inductively coupled plasma‐mass spectrometry have suggested its potential application to this field. In this study, analyses were performed using a 193 nm ArF Resonetics LA system, coupled to an Agilent 7700X‐ICP‐MS, with the following ablation parameters: a beam diameter of 5 μm, energy of 3 mJ, 2.7 J cm^?2, laser repetition rate of 10 Hz and translation speed of 2.5 μm s^?1. NIST SRM 610 glass was used as the primary calibration material. Performing this protocol, characterisation of a USGS GP‐4 reference material was achieved with suitable precision and accuracy, but the USGS MACS‐3 reference material appeared more heterogeneous under the ablation conditions tested. Calibration was performed using two different beam diameters (5 and 11 μm). Capelin (Mallotus villosus) otoliths measuring between 10 and 20 μm in diameter were tested. Even though a smaller beam diameter and lower energy were used compared with those normally employed to analyse larger otoliths, the method was successful.     

利用改进遗传算法求解整周模糊度

本文首先通过整数高斯变换,降低了各整周模糊度分量之间的相关性,并在此基础上提出了均匀设计与遗传算法相结合的方法进行整周模糊度搜索,最后进行了基线解算实验。解算结果表明,该算法用于模糊度求解极大提高了搜索效率。     

CSD和CDD结合下的最优遥感特征指数集构建及其在湿地信息提取中的应用

依托中分辨率成像光谱仪完整的数据序列和丰富的光谱信息,遥感特征指数在湿地生态系统发展变化的状态、趋向和规律研究方面发挥着不可替代的优势.传统类间距离判别的遥感特征指数选取中常存在过分依赖数据统计特征、入选指数与目标地类间生态学意义不明确、分类模型普适性差等局限性.基于此,本研究以河北省白洋淀湿地自然保护区为例,提出类可...     

L1-L2范数联合约束稀疏脉冲反演的应用

稀疏脉冲反演实际上就是利用反褶积原理, 从带有噪声的地震道中计算出具有稀疏分布特征的反射系数的振幅和时间.稀疏脉冲反演是非线性优化问题, 通常都是把非线性优化问题转化为线性优化问题, 然后用线性优化算法求解.以范数约束为基础, 提出L1-L2范数联合约束求解的方法.该算法采用了目前国际流行的内点算法, 与传统的优化算法相比, 这种算法具有精度高, 速度快的优点.通过研究人工模型和南海某油田实际数据, 表明该算法的计算结果和测井记录吻合好, 提高了地震分辨率, 目的层段分辨率优于8m.利用反射系数剖面预测的储层厚度和开发井吻合很好, 大大地降低了资源量计算的风险和油田开发的不确定性.      

自适应非线性有限元的多重网格法求解及应用

描述了非线性自适应有限元的多重网格法求解过程。 通过算例说明了方法的有效性以及自适应多重网格有限元用于开挖施工过程模拟分析的优越性。     

基于异步迭代算法的冲击地压预测

采用三层BP神经网络方法对冲击地压建立了数学模型。网络的训练算法采用具有松弛因子的动态异步迭代法,该算法在克服网络的麻痹现象及局部极小问题上都优于目前常用的训练方法,因而,采用此算法对网络进行了训练及震级的预报。基于新汶矿务局华丰煤矿1999～2000年的冲击地压现场监测数据,把冲击地压的能量、产生波的幅值、频次做为输入数据,相应期间的最大震级为输出数据,组成神经网络的训练样本及测试样本,对原始数据进行了数学预处理,网络结构采用了输入层3个结点,中间层7个结点,输出层1个结点的前向神经网络;网络最终的训练误差为0.06,预测结果的相对误差率平均为 9.2 %,预测效果比较理想。     

使用自然语言处理和分层匹配方法的地理信息服务语义发现

设计了一种基于自然语言处理和分层匹配的地理信息服务语义发现框架,实现用户输入关键词与地理信息服务的语义匹配。框架基于Word Net知识库,利用消歧技术确定所提取词汇的含义;根据所提取的信息来源以及相关关系将地理信息服务上下文划分为6个信息层匹配,并使用遗传算法确定各信息层在匹配过程中具有的权重。最后将所提出的发现方法与常用的发现方法做实验验证,结果表明该方法可以提高地理信息服务语义发现的查准率。     

基于遗传小波神经网络的海底声学底质识别分类

分割海底声纳探测图像,提取单元特征向量进行主成份分析,选取均值、标准差、对比度、相关系数、能量及同质性作为训练特征向量,构建小波神经网络。利用遗传算法优化小波神经网络的初始权值及小波参数,对砂、礁石、泥3种底质类型分别进行训练,并得到3种底质的测试精度都在90%以上,优于单独利用小波神经网络进行训练时的测试精度,克服了小波神经网络训练时易陷入局部极小的固有缺陷,表明基于遗传算法的小波神经网络可有效用于海底底质声纳图像的识别和分类。