基于径流分类的日径流量预测神经网络模型

利用聚类分析法将径流序列分解为若干个子径流序列 ,对这些子径流序列分别建立局部神经网络模型 ,而后把这些局部模型合并成一个混合模型。当新的信息进入该模型时 ,首先用分类器判别其类别 ,以确定用混合模型中的何种局部模型加以模拟。通过与不加分类的总体神经网络模型的模拟结果加以对比 ,结果表明这种基于径流分类的降雨 -径流模型表现出了更优良的性能 ,可以较大地提高径流模拟精度。     

铁皮石斛人工繁育技术

以铁皮石斛商品瓶苗和盆栽苗茎段为试材,添加不同浓度6-BA、NAA,诱导茎段腋芽、原球茎和不定根,建立再生体系,快速繁殖铁皮石斛组培苗,以期为秦岭淮河一线以北地区人工繁殖铁皮石斛提供参考依据。结果表明:外植体宜采用70%酒精浸泡20 s,0.1%升汞浸泡8 min消毒;MS+6-BA 3.0~5.0 mg·L^-1+NAA 0.1~1.0 mg·L^-1适合腋芽分化和增殖,分化率92%~100%;1/2MS+6-BA 2.0 mg·L^-1+NAA 0.5 mg·L^-1+土豆泥15%适合原球茎诱导增殖,增殖倍数7.7;1/2MS+NAA 0.3 mg·L^-1生根率为100%;以松针土移栽,成活率83%。     

Neural network prediction of performance parameters of an inclined plate seed metering device and its reverse mapping for the determination of optimum design and operational parameters

Seed planting equipment with inclined plate seed metering devices is the most commonly used equipment for planting of peanut crop in India. For obtaining the high yield, it is very essential to drop the peanut seeds in rows maintaining accurate seed rate and seed spacing with minimum damage to seeds during metering. This mainly depends on forward speed of the planting equipment, rotary speed of the metering plate and area of cells on the plate. The relationship between these factors and the performance parameters viz., seed rate, seed spacing and percent seed damage can be established using regression analysis. But they may not be very accurate and may pose difficulty in the determination of inputs for a set of desired outputs (reverse mapping). Hence, an attempt has been made in this paper to develop the feed forward artificial neural network (ANN) models for the prediction of the performance parameters of an inclined plate seed metering device. The data were generated in the laboratory by conducting experiments on a sticky belt test stand provided with a seed metering device and an opto-electronic seed counter. The generated data was used to develop both statistical and neural network models. The performance of the developed models was compared among themselves for 4 randomly generated test cases. The results show that the ANN model predicted the performance parameters of the seed metering device better than the statistical models. In order to determine the optimum forward speed of the planting equipment, peripheral speed of the metering plate and the area of cells on the plate to obtain the recommended seed rate of 33.33 seeds/m², seed spacing of 100 mm and percent seed damage of 0.2% with 100% fill of the cells, a novel technique of reverse mapping using ANN model was followed. It was observed that the optimum forward speed of the planting equipment and optimum area of cells on the metering plate had good correlation with size of seed. Linear regression equations were developed to predict the optimum forward speed of the planting equipment and optimum area of cells on the metering plate using the size of seeds as independent parameter. The peripheral speed of the metering plate of 0.237 m/s was found to be optimum for the size of seeds in the range of 95.42-123.01 mm². However, the results need to be verified by conducting planting operation under actual field conditions.     

双壳贝类营养需求及人工饵料的研究进展

工厂化养殖是未来贝类产业可持续发展的必然趋势。由于微藻的培养容易受到气温、光照等自然环境条件的影响,而且占用大量水体,因此研发双壳贝类人工饵料已成为贝类工厂化养殖的关键因素。本文简述了蛋白质、脂类和碳水化合物对双壳贝类生长、繁殖及免疫的影响,详细叙述了微藻干粉、大型海藻处理物、酵母、微粒饲料、液态微胶囊饲料和固态微胶囊饲料6种人工饵料的研究进展,以期为研发新型的双壳贝类人工饵料及开展工厂化养殖提供依据。     

人工哺育大熊猫幼仔1月龄内的饲喂及体重增长变化研究

人工圈养大熊猫出生幼仔一般采用自然哺育和人工哺育2种形式。人工哺育大熊猫幼仔1月龄内的饲喂及体重增长变化研究结果表明,3只研究个体均饲喂异母初乳时,其生长发育良好。经方差分析,3只幼仔1月龄内饲喂和体重变化均无显著差异。因圈养大熊猫产双胎的几率较大,所以采取人工哺育可以保证幼仔的成活率。目前人工哺育的方式主要是采集初乳及母乳和配制人工乳来进行人工育幼。     

基于神经网络模型的青岛市城区土壤重金属污染源定位

建立基于遗传算法的BP神经网络系统,该模型可以有效描绘区域中重金属元素的分布情况,并由此通过各元素浓度极大值点求出污染源近似坐标,实现对污染源的定位.将该模型运用于青岛市,根据青岛市不同功能区的土壤重金属含量调查结果,实现了对可能重金属元素污染源位置的预测.     

黄土高原人工草地的土壤水分动态及水土保持效益研究

通过９年观测，黄土高原人工草地土壤水分的季节性变化可划分为三个阶段，在此基础上模拟不同人工草地土壤水分的变化规律；随着牧草生育期的延长至第９年，人工草地土壤水分恢复程度逐渐减弱；沙打旺生存能力极强，能够高效地利用深层土壤贮水；用数学模型可以模拟不同人工草地的水土流失，将植被因子引入水土流失方程，可以定量描述对水土流失的影响；反映植被、土壤等因子与水土流失关系的复合因子Ａ￣１值，基本上代表不同人工草地水土流失状况。     

银纹夜蛾人工饲养技术研究

本文在研究了各种环境因子对银纹夜蛾实验种群影响的基础上，进一步研究了食量，低温保种及饲养管理技术，设计了一种便于收集卵的新型产卵笼，并总结了人工饲养银纹夜蛾的技术要点。     

西安临潼人工林土壤干化与恢复研究

通过野外调查和室内测定,本文研究了西安临潼人工林下0-6m土壤含水量和土壤干层的变化。结果表明,临潼14龄杨树林和16龄梧桐树林下150-350cm之间土层的含水量分别为8.7%和9.0%。按土壤干层划分标准(含水量<10%),这已属于发育弱的土壤干层,说明西安地区人工林下有土壤干层存在。而在丰水年中,杨树林和梧桐树林下原有的土壤干层带水分含量增加到21.6%和21.7%,土壤干层消失,说明在降水量增加的条件下,西安地区发育弱的土壤干层可以得到恢复,人工林能够正常生长。由此推断,西安及其降水量与其类似的其他地区可以种植一些高大乔木或果树经济林。在土壤干层发育严重的黄土高原北部地区不适于广泛造林,可以优先考虑发展疏林和森林草原植被。