某蛋禽公司投入产出分析Ⅱ．价值型回归投入产出预测模型

以某蛋禽公司１９８９～１９９３年的总产值为时间响应数列，建立数学模型Ｙ＝１２７４．７＋１４７．４６ｔ（ｒ＝０．９１５２，Ｐ＜０．０１），用其预报１９９５、１９９８、２０００年该公司总产值分别为２３０６．９、２７４９．３、３０４４．２万元，并根据预测值及基年（１９９３）的投入产出模型，采用比例分摊，编制了１９９５、１９９８、２０００年该公司的价值型投入产出预测模型。据此，预测了三个阶段各部门应增加的劳动力人数及在劳动力不增加的情况下，年人均劳动报酬量。经分析，该公司没有维持简单再生产的能力，要维持简单再生产，在消费增长速度不变的情况下，生产资料的生产应扩大０．０９２倍或在生产资料生产保持不变的情况下，消费缩小０．１０１倍。     

我国蔬菜市场预测预警研究浅析

在探讨蔬菜预测、预警理论发展情况的基础上,介绍了蔬菜市场预测预警的核心内容即蔬菜价格监测和蔬菜价格预警理论体系的概况,着重从蔬菜价格监测的概念、蔬菜价格监测的品种及范围、蔬菜价格监测体系3个方面介绍了蔬菜价格监测的主要内容;并分别从数量供应、需求、贮藏库、市场价格4个角度总结蔬菜预测预警现状,最后进行了展望。     

水土流失定量遥感方法新进展及其在太湖流域的应用

本文介绍了水土流失定量遥感方法研究所取得的新进展及其在太湖流域的应用结果。显示出该法具有快速、准确、省钱和实用的特点。建成了可供长期使用的太湖流域苏皖区水土流失定量遥感监测系统 ,还有 1 996、1 997、1 999年的全区、分县市统计的土壤年流失量、侵蚀模数、流失强度等级面积、防治强度类型面积和相应最终成果图等。依据太湖流域苏皖区的监测结果 ,讨论了水土流失的空间和时间变化、应用领域等。土壤年流失量及流失面积的增减 ,与监测年的降雨侵蚀力R密切相关。凡土壤年流失量大的年份 ,次年很可能出现水质恶化和蓝藻爆发 ,表明监测结果将在太湖水质面源污染增量监测与治理中发挥应用价值。     

利用内部信息的农用自动引导行走车的研究(第4报)——适应农业环境的控制系统

研究的行走控制系统由软、硬两部分组成，通过建立系统的控制模型，开发了利用非线性理论进行线性变换的直线行走控制方法和利用预测控制进行曲线行走控制的方法，通过实验确定了控制系统的参数；改造设计了行走车的行走与操向部分。实现了计算机的行走控制。     

煤-粮复合区耕地破坏预测系统的初步设计

论述了煤-粮复合区概念的提出、研究背景和现状,对现有的采煤沉陷预测系统的预测方法和功能进行了描述,并分析了它的不足,指出现有的采煤沉陷预测系统不能满足煤-粮复合区耕地破坏预测的需要。在现有系统分析的基础上对煤-粮复合区耕地破坏预测系统进行了构建,提出了系统设计的目标和需求,对系统的总体结构和功能以及系统解决的关键问题进行了论述。通过建立煤-粮复合区的耕地破坏预测系统,满足县级国土资源管理部门对煤矿区耕地管理的需要,为解决煤炭资源开采和耕地保护的矛盾提供技术支撑,从而达到国家煤粮兼得的目标。     

Farm-related Factors Influencing the Adoption of Short-rotation Willow Coppice Production Among Swedish Farmers

The area of short-rotation willow coppice energy plantations on Swedish farmland increased quickly in the early 1990s because of subsidies for energy crop production, an increased CO₂ tax on fossil fuel and an already existing biofuel market in the country. In this study farm-related determinants for the adoption of short-rotation willow coppice production among Swedish farmers are identified and estimated. A Tobit model is applied to cross-sectional data on Swedish farmers in 1995. The results show that the decision to plant willow and the areas planted depend positively on arable land area, forest land area, the area of other land types, leasing out of arable land and tractor ownership. Negative factors are pasture area, tenancy and animal production. Differences in willow growing between ownership types, age groups and geographical regions are also important. The policy implications of the results are discussed.     

伊宁市冬小麦产量预报模型研究

基于1976—2019年伊宁市冬小麦单产数据和气象资料,分析伊宁市近43 a冬小麦单产的变化情况,得到伊宁市冬小麦趋势产量的计算方程;计算出小麦气象产量,选取冬小麦生长期间的气温、降水和日照时数等的旬月值,分析气象产量与气象因子之间的关系,找出影响小麦产量的关键发育时段和主要影响因子,结合小麦生长发育状况,挑选出冬小麦气象产量预报因子,建立小麦气象产量预报方程,最后得出伊宁市冬小麦产量预报方程。经近4 a实际单产数据验证,预测效果较好,可以在业务中使用。研究结果可用于指导生产,指导农民改进冬小麦种植及田间管理方式,还可为政府部门制定保障粮食安全的决策提供科学依据。     

Neural networks in fisheries research

Piscimetrics deals with software implementation of experimental design, second-generation artificial intelligence tools, viz. Neural Nets (NNs), genetic algorithms, Fuzzy Logic, Expert Systems, Wavelets and Image analysis in the field of fisheries. A brief sketch of NNs is followed by a review of their applications in forecasting, classification, distribution and fisheries management since 1978. Forecasting in fisheries covers distribution of eggs, recruitment, fish growth/age, biomass and fish catch. Other major areas are identification, abundance and food products, environmental factors and collapse of fishery industry. The data structures are given in tensorial notation. The need for the paradigm shift from classical to multi-level hybrid NNs is emphasized.     

Forecasting daily potential evapotranspiration using machine learning and limited climatic data

Anticipating, or forecasting near-term irrigation demands is a requirement for improved management of conveyance and delivery systems. The most important component of a forecasting regime for irrigation is a simple, yet reliable, approach for forecasting crop water demands, which in this paper is represented by the reference or potential evapotranspiration (ET_o). In most cases, weather data in the area is limited to a reduced number of variables measured, therefore current or future ET_o estimation is restricted. This paper summarizes the results of testing of two proposed forecasting ET_o schemes under the mentioned conditions. The first or “direct” approach involved forecasting ET_o using historically computed ET_o values. The second or “indirect” approach involved forecasting the required weather parameters for the ET_o calculation based on historical data and then computing ET_o. An statistical machine learning algorithm, the Multivariate Relevance Vector Machine (MVRVM) is applied to both of the forecastings schemes. The general ET_o model used is the 1985 Hargreaves Equation which requires only minimum and maximum daily air temperatures and is thus well suited to regions lacking more comprehensive climatic data. The utility and practicality of the forecasting methodology is demonstrated with an application to an irrigation project in Central Utah. To determine the advantage and suitability of the applied algorithm, another learning machine, the Multilayer Perceptron (MLP), is used for comparison purposes. The robustness and stability of the proposed schemes are tested by the application of the bootstrap analysis.     

黔西南东南部一次低空急流暴雨分析与预报

利用望谟县区域自动站资料、Micaps常规资料、望谟县国家基本气象站资料,应用天气学原理和方法对2011年5月10日20：00—11日20：00发生在望谟县境内的暴雨过程进行综合分析。结果表明,西南低空急流、低层切变辐合是形成此次暴雨的直接影响系统;低空急流向县境内暴雨区提供了大量的水汽、能量和垂直上升运动,是此次暴雨过程的重要影响系统。