城市空气质量评价中的模糊支持向量机方法

传统的评价方法不能处理带有模糊信息的城市空气质量的评价问题。基于结构风险最小化原则建立了带有模糊信息的支持向量分类模型和算法,在此基础上提出基于模糊支持向量机的城市空气质量评价方法;根据空气中的总悬浮颗粒物、二氧化硫、二氧化氮、空气综合污染指数4个指标,对我国50个主要城市2003年空气质量进行了综合评价,选择10个城市的评价结果进行了测试,结果表明:根据2003年数据采用本方法得到的邢台、张家口和沧州的空气污染指数与河北省环保专家提供的数据误差小于0.1;西宁、银川、乌鲁木齐、汕头、南京、大连、武汉的综合空气污染指数与国家环保总局提供的数据误差均小于0.5。     

应用因子分析法对林分蓄积相关因子的分析

利用2006年新疆阿勒泰山国有林管理局经营区森林资源连续清查2 493块样地数据,从中提取落叶松样地261块,通过因子分析法对与林分蓄积相关的因子进行分析。采用主成分分析法,提取特征值大于1的3个公因子,累积方差贡献率64.38%。结果表明:第一公因子为平均胸径、平均树高、平均年龄,其定义为基本林分因子,其方差贡献率为32.89%;第二公因子为郁闭度和样木总株数,定义为林分密度因子,其方差贡献率为18.16%;第三公因子为海拔和坡向,定义为立地条件因子,其方差贡献率为13.33%.最后把样地分为建模样本和验证样本,进行了多元回归并对其进行了验证,结果与因子分析的结果一致。     

The Total Population Prediction of Ya＇an City from 2010 to 2020 Year

利用雅安市1985—2009年的人口统计数据,拟合出马尔萨斯人口模型、Logistic增长模型和一元线性回归模型。通过2006—2009年人口数量的预测值与实际值比较,最终选择模拟精度较高的马尔萨斯模型和Logistic模型对雅安市2010—2020年的总人口做出预测,预测结果表明雅安市2010年的总人口达到156.21万人,而到2020年总人口将达到162.81万人。同时在预测的基础上,探讨了雅安市人口发展的影响因素,为雅安市科学地制定国民经济和社会发展战略,实现人口与资源环境的可持续发展提供参考。     

水肥一体化对红麻生长、纤维产量与品质的影响

【目的】研究水肥一体化（滴灌施肥）对红麻生长、纤维产量和品质的影响,探讨红麻水肥利用特点,为红麻高产高效栽培提供参考。【方法】大田试验设6个滴灌施肥处理和1个对照（CK）,CK采用100%灌水量（16.183 m3）和100%施肥量（264.00 kgN/ha,88.04 kgP2O5/ha,176.09 kgK2O/ha）,撒施、沟灌;处理T1~T3均采用100%灌水量、施肥量分别为100%、75%和50%,处理T4~T6采用80%灌水量（12.947 m3）、施肥量分别为100%、75%和50%。收获时考察不同处理红麻农艺性状和纤维指标。【结果】与常规施肥、灌溉相比,6个滴灌施肥处理可显著促进红麻的生长和改善纤维品质,红麻株高、茎粗、皮厚、地上部干质量、纤维产量和纤维线密度分别显著增加13.2%~25.5%、0.7%~1.4%、10.6%~20.3%、12.5%~30.9%、15.1%~36.8%和7.2%~30.7%,其中以T1处理的综合效果最好,其次为T5、T2。T1处理的株高、地上部分干质量、纤维产量等最高,但大部分与T5处理差异不显著,而处理T5的纤维强力显著高于处理T1。【结论】滴灌施肥时,T5处理（80%灌水量：12.947 m3,75%施肥量：198.0 kgN/ha,66.03 kgP2O5/ha,132.07 kgK2O/ha）可获得较好的节水节肥效果,建议在红麻生产上推荐应用。     

规模水稻秧苗的运输优化研究

通过对规模水稻秧苗运输现状的阐述,了解规模水稻秧苗运输机械配套优化的薄弱问题。根据对规模水稻秧苗从大棚到本田运输系统的调研和分析,确定规模水稻秧苗运输的主要指标为载秧容量、运输距离、时间和路线等。以目标规划理论建立水稻秧苗大棚到本田的运输优化模型,并利用遗传算法求解得到优化方案,对提高规模水稻秧苗从大棚到本田运输效率具有重要的意义。     

基于无人机多光谱影像的夏玉米SPAD估算模型研究

快速获取作物叶片叶绿素含量对及时诊断作物健康状况、指导田间管理具有重要意义。本研究以关中地区2020年夏玉米为研究对象,获取试验区无人机多光谱影像,提取植被指数,分析所选植被指数与SPAD的相关性,筛选得到模型的输入变量,利用偏最小二乘法(PLS)、随机森林回归(RF)和分层线性模型(HLM)分别构建拔节期、抽雄期、灌浆期以及全生育期的SPAD估算模型,最终选出最优估算模型,以期为快速获取夏玉米SPAD提供参考。研究发现：除NRI之外,NDVI、OSAVI、GNDVI、RVI、MCARI、MSR、CIre与SPAD均显著相关,其中,OSAVI、NDVI与SPAD呈现出较强且稳定的相关性;各个生育期的最优模型均是RF模型,在拔节期、抽雄期、灌浆期和全生育期,验证集R²分别为0.81、0.81、0.73、0.61,RMSE分别为1.24、2.32、3.13、3.20;对于SPAD估算模型,将降雨量、最高气温这两个气象因子与植被指数耦合的HLM模型可以一定程度提升线性模型的估算精度,但其精度低于RF模型。因此,基于无人机多光谱影像的RF模型可以实现夏玉米SPAD的快速准...     

Surface drainage requirement of crops: Application of a piecewise linear model for evaluating submergence tolerance

Crop tolerance to land submergence is an important criterion for designing a surface drainage system for agricultural lands. This paper collates the available data from various places in India related to the studies on the submergence tolerance of crops. The paper hypothesizes that a piecewise linear model could be used to describe crop response to land submergence. According to this hypothesis, there would be no yield decline for a few initial days of submergence. If submergence continues beyond this period then there would be linear decline in yield. The unknown parameters in the model are: optimum yield, threshold time and the slope which represents the per cent yield reduction per day of additional submergence beyond the threshold.Data in respect of wheat, pigeon peas, cowpeas, pearlmillet, maize and groundnuts indicate that the model describes the data well, although in many cases the threshold is 0.0. The yield reduction varies from 5.3 to 23.2% for each day of submergence beyond the threshold. It appears that to allow for more than 1–2 days of submergence will result in more than 10% reducation in yield of dryfoot crops. For the maize crop, the seedling stage is the most sensitive stage followed by the silking stage. The grain formation stage is the least sensitive, although even at this stage the threshold is 0.0 and yield reduction is 9.3% for each day of submergence beyond the threshold. The data for 9 test crops from Texas and Venezuela were well described by the model. It is concluded that the piecewise linear model is a useful tool for describing submergence tolerance of crops and for working out surface drainage requirements for a given level of yield reduction. Frequency analysis of the daily rainfall data from some selected locations indicates that there is every likelihood of submergence at most of the stations. It is suggested that there is an urgent need for developing wet farming techniques analogous to dry farming techniques.     

Preliminary recovery of coastal sharks in the south‐east United States

Relative abundance of many shark species in the Atlantic is assessed by compiling data from several independently conducted, but somewhat spatially limited surveys. Although these localized surveys annually sample the same populations, resulting trends in yearly indices often conflict with one another, thereby hindering interpretation of abundance patterns at broad spatial scales. We used delta‐lognormal generalized linear models (GLMs) to generate indices of abundance for seven Atlantic coastal shark species from six fishery‐independent surveys along the US east coast and Gulf of Mexico from 1975 to 2014. These indices were further analysed using dynamic factor analysis (DFA) to produce simplified, broad‐scale common trends in relative abundance over the entire sampled distribution. Effects of drivers including the North Atlantic Oscillation index, the Atlantic Multidecadal Oscillation index, annually averaged sea surface temperature and species landings were evaluated within the DFA model. The two decadal oscillations and species landings were shown to affect shark distribution along south‐east US coast. Estimated common trends of relative abundance for all large coastal shark species showed similar decreasing patterns into the early 1990s, periods of sustained low index values thereafter and recent indications of recovery. Small coastal shark species exhibited more regional variability in their estimated common trends, such that two common trends were required to adequately describe patterns in relative abundance throughout the Gulf of Mexico and Atlantic. Overall, all species’ (except the Gulf of Mexico blacknose shark) time series concluded with an increasing trend, suggestive of initial recovery from past exploitation.     

季节性冻融区地下水位预测方法研究

为预测河套灌区冻融区全年地下水位变化过程,采用统计学方法,研究了冻融期地下水位与地表气温间的关系,建立了二者间的线性模型,结合非冻融期水量均衡模型,建立了改进型水量均衡模型,通过优化求解方法确定模型参数。结果表明,模型计算埋深与实测埋深拟合效果较好,提出的改进型水量均衡模型可较好地预测冻融区全年地下水位变化过程,解决了冻融期间地下水模拟难题,方法简单精确,具有很好的实用性。