人工神经网络在电力系统短期负荷预测中的应用

根据电力系统短期负荷变化的特性，提出BP模型在实际负荷预测应用中的方法和步骤．对BP网络结构、样本空间、收敛性等作了有针对性的研究．结果表明：多层神经网络应用于电力系统短期负荷预测是可行和有效的．其预报结果比传统的负荷预测方法更准确、经济、效果更好．     

磷化铝间歇熏蒸防治鱼粉螨类的研究

本研究介绍了饲料鱼粉螨类的有效防治方法．采用11．5g／m2的磷化铝片剂，分两次间歇熏蒸大量孳生螨类和昆虫的棉纱布袋和编织袋包装的鱼粉，达到了有效杀灭鱼粉中大量孳生的粉尘螨、跗蠊螨、齿蠊螨、河野脂螨、食根嗜木螨、马六甲肉食螨、转开肉食螨、特氏肉食螨等8种螨类和烟草甲、白腹皮蠹、拟白腹皮蠹、赤颈郭公虫、赤足郭公虫、黑菌虫的效果。     

哈达门国家森林公园游客量动态预测

根据哈达门国家森林公园的票房数据，应用灰色系统理论建立旅游量灰色动态模型。基此，对哈园游客量进行了中短期预测，其预测检验精度为９３．７２。旨在对该园建设、管理等项决策提供科学依据。     

小型渔船号灯最小间距的研究

我国小型渔船(船长20～35米)捕鱼作业信号灯至今未能达到《1972年国际海上避碰规则(1989年修订本)》的要求。本文根据光学原理,对号灯间距分辨率进行了多次测试和研究,并根据我国渔船客观实际提出了小型渔船号灯设置最佳配置方案。     

Modelling Plant Disease Epidemics

An epidemic is the progress of disease in time and space. Each epidemic has a structure whose temporal dynamics and spatial patterns are jointly determined by the pathosystem characteristics and environmental conditions. One of the important objectives in epidemiology is to understand such spatio-temporal dynamics via mathematical and statistical modelling. In this paper, we outline common methodologies that are used to quantify and model spatio-temporal dynamics of plant diseases, with emphasis on developing temporal forecast models and on quantifying spatial patterns. Several examples of epidemiological models in cereal crops are described, including one for Fusarium head blight.     

Improving cereal yield forecasts in Europe – The impact of weather extremes

The impact of extreme events (such as prolonged droughts, heat waves, cold shocks and frost) is poorly represented by most of the existing yield forecasting systems. Two new model-based approaches that account for the impact of extreme weather events on crop production are presented as a way to improve yield forecasts, both based on the Crop Growth Monitoring System (CGMS) of the European Commission. A first approach includes simple relations – consistent with the degree of complexity of the most generic crop simulators – to explicitly model the impact of these events on leaf development and yield formation. A second approach is a hybrid system which adds selected agro-climatic indicators (accounting for drought and cold/heat stress) to the previous one. The new proposed methods, together with the CGMS-standard approach and a system exclusively based on selected agro-climatic indicators, were evaluated in a comparative fashion for their forecasting reliability. The four systems were assessed for the main micro- and macro-thermal cereal crops grown in highly productive European countries. The workflow included the statistical post-processing of model outputs aggregated at national level with historical series (1995–2013) of official yields, followed by a cross-validation for forecasting events triggered at flowering, maturity and at an intermediate stage. With the system based on agro-climatic indicators, satisfactory performances were limited to microthermal crops grown in Mediterranean environments (i.e. crop production systems mainly driven by rainfall distribution). Compared to CGMS-standard system, the newly proposed approaches increased the forecasting reliability in 94% of the combinations crop × country × forecasting moment. In particular, the explicit simulation of the impact of extreme events explained a large part of the inter-annual variability (up to +44% for spring barley in Poland), while the addition of agro-climatic indicators to the workflow mostly added accuracy to an already satisfactory forecasting system.     

基于LM算法的BP神经网络的电力负荷短期预测

清代书院课艺总集多为连续出版物，或具有连续出版物的刊行初衷。刊期短则一季，多则一年或数年。经费充足与否，会影响刊期。发表周期多为一年至五年，也有十余年的。用稿率以10%~20%居多，偶见“关系稿”。时文的用稿标准是“清真雅正”。题目多为官师所拟。一般全文刊登，也偶有“论点摘编”。多经润色，并附录评点。有的以袖珍本刊行，有的宣称“翻刻必究”，标出定价，附载广告。稿费已在膏火费中预支，优秀作品可被转载。从本质属性和诸多要素来看，书院课艺总集实开今日“大学学报”、“学术集刊”之先河。     

细分外推与模糊预测在近海水质非线性时序处理中的比较分析

近海水质非线性时间序列通常由于采集范围大、时间间隔长带有一定震荡性和模糊性,这使得对其进行分析与预测有一定的难度。本研究中以某近海水质指标磷酸盐(PO3-4-P)、硝酸盐(NO-3-N)、亚硝酸盐(NO-2-N)、铵盐(TNH+4-N)和硅酸盐(Si O2-3-Si)所形成的5种时间序列为例,采用逼近细分模式导出的细分外推法和多参考加权数据的模糊预测法对近海水质时序预测进行了比较分析,并通过图形与误差计算比较了两种方法的异同。结果表明:采用细分外推法预测序列在整体形状上能更好地逼近初始时序,而模糊预测法在整体逼近精度上占有优势。本研究中提出的预测比较方法可为同类问题的预测与模型选取提供参考依据。     

应用Excel软件分析敌敌畏农药对两广二号家蚕的安全间隔期

应用Excel软件中的曲线方程分析判断敌敌畏农药对两广二号家蚕的安全间隔期。结果表明：敌敌畏1000倍液的安全间隔期是6d多，其数学模型为幂函数曲线方：y=88．0653x-1834本方法克服以往家蚕的农药安全期无数学模型可循或使用的BASIC方法陈旧繁杂的缺点，也避免英文统计软件SPSS难以在农村普及的不足，是一种计...     

金融时间序列指标判别框架：以特质波动率为例

基于拐点集合判别的TBUD方法主要思路是分析拐点集合间的关系，并在高维空间进行划分，从而搭建判别模型，并将分析框架应用在特质波动率等若干指标上，利用实证数据得到结论。应用TBUD判别框架可以发现，特质波动率等指标无法对拐点集合进行清晰划分，因而并不具有预测能力。