膨胀颗粒污泥床（EGSB）反应器处理高浓度自配水的试验研究

本文对EGSB反应器处理高浓度自配有机废水进行了较系统地研究，研究表明中温条件下(31～35℃)，进水COD浓度为8200～9000mg     

基于PDM犁的智能CAD设计系统

讨论基于产品数据管理(PDM)犁的智能CAD设计系统基本框架及其3个组成部分：设计专家系统、产品数据管理和犁的计算机辅助设计。研究了各部分的功能和技术实现，设计专家系统用于犁的参数化设计过程中参数的选择和装配图装配合理性的判断，PDM主要管理犁的辅助设计相关的数据和文件以及专家系统知识。在此基础上，介绍了集成专家系统和产品数据管理犁的计算机辅助设计软件开发。     

泵站系统故障诊断智能PETRI网

以往应用系统故障诊断模型行为PETRI网中规则的可信度为固定常数，由于泵站工作状况在改变，因此，应用在泵站系统时，提出了以谓词变迁网（Pr／T－PN）存储知识，智能推理计算重要规则可信度的方法，并给出了明确的定义。以轴流泵出现动力机过载情况为例，说明了泵站系统故障诊断智能PETRI网的构造和诊断方法。     

内燃机排气成分动态检测方法的研究

介绍了采用飞行时间质谱仪动态测量内燃机排气成分的方法。提出了实现动态检测的系统方案，研制开发了高速数据采集系统，给出了性能试验结果。测量并识别了质量数相近的N2和C2H4的谱图，给出了废气成分浓度的动态变化曲线。     

排种器性能检测中种子位置智能检测方法

根据基于计算机视觉的排种器性能检测的特点，提出了基于神经网络的种子位置智能检测方法。采用两个光轴互相垂直的摄像机监测投种规律，并把以矩法求取的质心图像坐标作为输入节点，构造检测种子质心实际坐标的两个神经网络，并行处理左右两幅图像，从而快速求得种子位置。实践表明，此方法不仅能求出种子位置，而且可全面监测种子的运动情况。     

我国植保机械及施药技术现状与发展趋势

阐述了我国植保机械及施药技术的现状,分析了我国施药技术中存在的问题以及与国外植保机械发展水平的差距,并提出了发展趋势。     

固定式喷灌系统喷头经济压力的研究

在能源危机的冲击下，节能已成为广大喷灌工作者共同关心的问题。降低喷灌系统工作压力是节能的主要方法之一，而喷头的工作压力与喷灌系统工作压力紧密相关。本文提出了固定式喷灌系统喷头经济压力的概念及其确定方法，并将此法运用到实例中。在选择经济、合理的喷头及其经济工作压力方面做了有意义的探讨。     

Effect of water deficit in different growth stages on stem sap flux of greenhouse grown pear-jujube tree

The effects of water deficit in different fruit growth stages on the variation of stem sap flux of 6-year old greenhouse-grown pear-jujube trees were investigated. Treatments included sufficient water supply during the whole fruit-growing period (T₁), mild water deficit during the flowering–fruit setting stage (T₂), moderate water deficit during the fruit rapid growth stage (T₃) and severe water deficit during the fruit maturing stage (T₄). Results showed that significant compensation effect on stem sap flux after re-watering was observed in T₂, but not in T₃ and T₄ stages. At the end of rapid growth stage, the diurnal variation of stomatal conductance generally had a similar trend as that of stem sap flux, but with a distinct midday depression from 12:00 to 14:00 p.m. In addition, a linear relationship between the relative available soil water content (RAWC) and the ratio of daily stem sap flux to that of sufficient water treatment was observed (R² = 0.4489).     

棉田膜内与膜间土壤溶液含盐量的变化

用定期取表层土样测定其电导率和在不同深度埋设盐分传感器探头的方法 ,在作物生长季节内 ,监测了棉田膜内和膜间不同深度的土壤溶液含盐量变化。结果为 :1棉田膜内与膜间表层土壤和 1 0 cm、30 cm深土壤溶液含盐量变化较大 ,且规律相同。未灌水时上升 ,灌水后迅速下降。膜间未灌水期间的含盐量上升幅度大于膜内 ,灌水对膜内和膜间表土洗盐、1 0 cm、30 cm深土壤溶液含盐量的降低作用没有差别。降雨可引起膜内和膜间 1 0 cm深土壤溶液电导率的变化 ,这个影响也是膜间大于膜内。 2 60 cm深的土壤溶液不存在明显的盐分累积现象 ,灌水可使这里的土壤溶液含盐量缓慢降低 ,膜间的降低过程快于膜内     

“WaterMan”: an on-farm water management game with heuristic capabilities

A modern computer-based simulation tool (WaterMan) in the form of a game for on-farm water management was developed for application in training events for farmers, students, and irrigators. The WaterMan game utilizes an interactive framework, thereby allowing the user to develop scenarios and test alternatives in a convenient, risk-free environment. It includes a comprehensive soil water and salt balance calculation algorithm. It also employs heuristic capabilities for modeling all of the important aspects of on-farm water management, and to provide quantitative performance evaluations and practical water management advice to the trainees. Random events (both favorable and unfavorable) and different strategic decisions are included in the game for more realism and to provide an appropriate level of challenge according to player performance. Thus, the ability to anticipate the player skill level, and to reply with random events appropriate to the anticipated level, is provided by the heuristic capabilities used in the software. These heuristic features were developed based on a combination of two artificial intelligence approaches: (1) a pattern recognition approach and (2) reinforcement learning based on a Markov decision processes approach, specifically the Q-learning method. These two approaches were combined in a new way to account for the difference in the effect of actions taken by the player and action taken by the system in the game world. The reward function for the Q-learning method was modified to reflect the suggested classification of the WaterMan game as what is referred to as a partially competitive and partially cooperative game.