基于PSO-BP神经网络的外贸发展状况的评价

以我国对外贸易的实际情况为基础，建立了评价外贸发展状况的一套指标体系.使用主成分分析方法对所有评价指标进行预处理之后，借助粒子群优化算法改进了BP神经网络算法，构建了外贸发展状况的评价模型.评价模型在具体应用中，评价结果较为准确，具有一定的科学性和合理性.     

浅谈给水排水工程节能节水措施

作者针对给排水系统工程特点并依据多年设计实践,总结了几点节能节水措施;阐明了通过减少不必要的浪费,可以达到节约水资源、节约能源的目的。     

智能轨迹控制割草机器人设计——基于FPGA神经网络

为了提高割草机器人自主导航和定位的精确性和智能性,设计了一种新型的基于FPGA神经网络算法的割草机器人。该设计采用FPGA可重构技术,以3层误差反向传播神经网络作为典型的模型来展开;利用成熟的BP算法公式,设计了割草机器人智能控制的模型;利用FPGA技术,设计了割草机器人的硬件系统;最后采用文本输入的设计方法,利用田间试验的方式,对机器人的轨迹规划能力和控制精度进行了验证。试验结果表明:利用FPGA和神经网络模型可以有效地穿越5个障碍物,并可得到满意的轨迹规划结果。将普通的PID控制器和神经网络PID控制器得到的控制结果误差进行了对比,结果表明:神经网络PID控制器得到的割草机器人控制误差明显比传统的PID控制器误差小。该方法为神经网络的硬件实现提供了可靠的理论基础。     

New Approaches to Modeling Methyl Jasmonate Effects on Pomegranate Quality during Postharvest Storage

Adaptive neuro fuzzy inference system (ANFIS) and genetic algorithm–artificial neural network (GA-ANN) models were used to predict the effect of methyl jasmonate (at three levels 0, 0.01, and 0.1 mM) and storage time (0, 14, 28, 42, 56, 70, and 84 days) on quality parameters and physiological changes of pomegranate fruits during storage. Methyl jasmonate reduced chilling injury and improved quality characteristics of pomegranates during postharvest storage. The GA-ANN and ANFIS were fed with two inputs of methyl jasmonate and storage time. The results showed that GA-ANN predictions agreed with experimental data and the GA-ANN with 14 neurons in one hidden layer can predict physiological changes and quality parameters of pomegranate (weight loss, pH, chilling injury index, ion leakage, ethylene, respiration, polyphenols, anthocyanins, and total antioxidant activity) with correlation coefficients equal to 0.87. The ANFIS model was trained by a hybrid method and agreement between experimental data and ANFIS predictions was significant (r = 0.90).     

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。     

Aggregate-related changes in network patterns of nematodes and ammonia oxidizers in an acidic soil

Nitrification plays a central role in global nitrogen cycle, which is affected by biological interaction between soil microfauna and microorganisms. However, the complexity of soil biotic communities made it difficult to reveal organizational principles of the community and the interactions among species. Here, we used the network analysis to decipher the interactions between nematodes and ammonia oxidizers within aggregate fractions under 10-year manure application, and examine their associations with soil variables and potential nitrification activity (PNA). Three aggregate fractions included large macroaggregates (>2000 μm, LA), small macroaggregates (250–2000 μm, SA), and inter-aggregate soil and space (<250 μm, IA). Aggregate factions showed a remarkable effect on association networks of nematodes and ammonia oxidizers. The average connectivity (avgK) and the number of edges in overall networks increased with increasing aggregate sizes, while the average geodesic distance (GD) followed the opposite trend. The LA network could be viewed as a better organized or a better operational soil food web with more functional interrelated members than the SA and IA networks. The modules related to PNA were significantly correlated and clustered together as meta-modules in networks of aggregate fractions. The role-shifts prevailed among the network members such as significant module memberships (MMs) and generalist/specialist operational taxonomic units (OTUs). A half of shared nodes were further identified as shared MMs, dominated by ammonia-oxidizing bacteria (AOB) especially for Nitrosospira cluster 3a and 10. Soil pH could explain partly the shift of module hubs in different networks, while grazing by bacterivores might account for three exclusively connecters related to Nitrososphaera clusters 1.1. The strongly coupled modules correlated positively to pH and total carbon (TC), regardless of aggregate fractions. The network analysis approach provided new insights into potential importance of network interactions between nematodes and ammonia oxidizers in soil nitrogen cycling.     

基于Lasso和BP神经网络的组合预测及其应用——以居民消费支出预测为例

在变量选择的基础上，构建基于Lasso方法和BP神经网络的预测模型，并对我国城乡居民的消费支出进行预测，结果显示：基于Lasso方法和BP神经网络的组合预测精度要明显高于BP神经网络、Lasso方法的预测精度；在2014~2020年，我国农村居民消费增长率有所提升，城镇居民消费增长率减缓，城乡居民消费增长率之间的差距呈下降趋势，但短期内城乡居民消费差距依然难以缓和。     

网络嵌入性、商业模式创新与企业竞争优势关系研究

基于商业模式创新中介效应，依据全国314家企业问卷调查的样本数据，运用多元线性回归方法，考量网络嵌入性、商业模式创新和企业竞争优势之间关系，结果发现：关系嵌入性、结构嵌入性与竞争优势均有显著的正向关系；商业模式创新在关系嵌入性、结构嵌入性与企业竞争优势的关系中起着中介作用。鉴此，企业应注重构建不同形式的网络嵌入，推动商业模式的调整与变革，以提高企业竞争优势。     

农村信息化网络建设方式对比

在市场经济条件下，建立和完善农村信息公共服务网络，促进农业信息工作、新农村建设，已经成为统筹城乡经济社会发展、全面建设小康社会的战略选择。文章首先分析了我国农村信息化网络建设的现状，然后探讨了农村信息化建设面临的主要障碍，最后提出了农村信息化网络建设的实施意见。     

中小旅行社入境旅游与出境旅游网络营销对比分析

通过对中小旅行社入境旅游与出境旅游网络营销的相同处和不同处进行对比分析，把他们常用的营销方法通过举例表现出来，叙述了网络营销对出境旅游和入境旅游的意义，对旅游营销有积极作用。