立轴冲击式水轮发电机组技术供水系统优化

水电站的技术供水系统要根据水电站的基本技术参数及设备要求的技术供水参数进行详细设计和论证,并结合电站所在区域的实际情况,使系统满足机组在各种工况下的正常安全稳定运行。主要阐述米角河一级水电站立轴冲击式水轮发电机组技术供水系统的优化设计,采用一次冷却供水和冷却水二次循环供水相结合的设计方案,避免供水水质变化时停机造成的经济损失,提高了供水系统的运行可靠性,减少了检修维护量,为电站"无人值班,少人值守"创造了必要条件。     

DETECTOR: A knowledge-based system for injection molding diagnostics

A knowledge-based system (KBS) for diagnosis of multiple defects in injection molding is presented. The general scheme for knowledge representation based on fuzzy set theory has been shown useful in representing inexact and incomplete information for developing the KBS. An optimality criterion is created for selecting a simple and best cover to explain the given problem. An efficient search algorithm for finding such cover is also discussed.     

A balanced solution of a fuzzy soft set based decision making problem in medical science

The purpose of this paper is two folded. Firstly, the concept of mean potentiality approach (MPA) has been developed and an algorithm based on this new approach has been proposed to get a balanced solution of a fuzzy soft set based decision making problem. Secondly, a parameter reduction procedure based on relational algebra with the help of the balanced algorithm of mean potentiality approach has been used to reduce the choice parameter set in the parlance of fuzzy soft set theory and it is justified to the problems of diagnosis of a disease from the myriad of symptoms from medical science. Moreover the feasibility of this proposed method is demonstrated by comparing with Analytical Hierarchy Process (AHP), Naive Bayes classification method and Feng's method.     

基于变精度粗糙集的煤与瓦斯突出预测

煤与瓦斯突出是受诸多因素影响的复杂问题,为了提高其预测的准确性,本文以变精度粗糙集理论中的决策表为主要工具,首先将影响煤与瓦斯突出的检测信号作为预测的条件属性集,煤与瓦斯突出量作为对预测的决策属性,建立决策表,然后利用小生境遗传算法适合于进行多峰值函数优化的特点,提出了一种基于小生境遗传算法的粗糙集属性约简方法,用于求解决策表的多个约简,进而进行值约简后抽取出预测规则。算例结果说明了本算法的正确性和可行性。     

Continuous process control using neural networks

We present some adaptive control strategies based on neural networks that can be used for designing controllers for continuous process control problems. Specifically, a learning algorithm has been formulated based on reinforcement learning, a weakly supervised learning technique, to solve set-point control and control scheduling for continuous processes where the process cannot be modeled easily. It is shown how reinforcement learning can be used to learn the control strategy adaptively based on exploration of the control space without making assumptions about the process model. A new learning scheme, handicapped learning, was developed to learn a control schedule that specifies a schedule of set points. Applications studied include the control of a nonisothermal continuously stirred tank reactor at its unstable state and the learning of the daily time-temperature schedule for an environment controller. Experimental results demonstrate good learning performance, indicating that the learning algorithm can be used for solving transient startup and boundary value control problems.     

一种谱分解降维的模糊有监督局部保持投影策略

提出一种谱分解降维的模糊有监督局部保持投影策略。首先针对监督局部保持投影SLPP存在过学习和不能较好地保持图像空间的差异信息等问题,通过最小化局部离散度和最大化差异离散度准则提取投影方向,找到一种线性鉴别分析的等价形式。其次,通过采用模糊k近邻(FKNN)方法得到相应的样本分布隶属度信息,同时考虑到离群样本对整个分类结果的不利影响,提出一种模糊化方法,根据样本的隶属度对样本分布矩阵重定义所做的贡献,将每个样本的隶属度融入到SLPP特征抽取的过程中,从而得到完整有效的模糊样本特征向量集,有效解决了小样本问题的特征抽取问题。第三,提出一种谱分解的矩阵分析方法,在SLPP投影准则下,对散布矩阵实现降维。在ORL和NUST603人脸库上的实验结果验证了该方法的有效性。     

基于最大加权独立集的频谱分配算法

动态频谱接入技术允许认知用户接入未授权的频谱,可以有效地提高频谱资源的利用率。频谱分配算法的时间开销和公平性是算法优劣的主要评价标准。本文从图论着色模型出发,构建了着色算法的评价体系及优化目标。针对用户间的公平性与分配的时间开销问题,在极大独立集的基础上提出了基于加权最大独立集的着色算法,获得了接近于最优的用户公平性,且该算法的时间开销等于信道数,与认知用户的数目无关。仿真分析验证了算法的正确性。     

基于深度学习与不平衡样本集的输电线路故障分类

针对输电线路各类型故障样本间的数量不平衡会造成人工智能算法对故障中的少数类样本识别精度不足的问题,提出了一种基于Borderline-SMOTE（BSMOTE）算法与卷积神经网络（CNN）相结合的输电线路故障分类方法。该方法首先利用BSMOTE算法对位于分类边界上的少数类样本进行过采样合成处理,改善样本间的不平衡度,然后将所提取的一维故障电流信号样本重构成二维灰度图像数据形式,并在Pytorch深度学习框架下搭建了CNN网络模型,利用模型的自主学习能力对灰度图像进行特征自提取与辨识,减少传统人工设计特征提取的工序,完成对输电线路故障类型的分类。实验结果表明该模型能够提高对少数类故障样本的识别能力,准确地判断故障类型,并对噪音具有较强的抗干扰能力。     

基于Rough集的磨削参数决策系统

本文介绍了5层模糊神经网络的优缺点，提出了基于Rough集构造模糊神经网络的方法，并应用于多传感器的磨削参数决策系统，达到控制磨削加工质量的目的。     

不完备信息系统的规则提取研究*

粗糙集理论和D-S证据理论都是重要的不确定性推理方法,两者各有优缺点.现实生活中,不完备信息系统广泛存在.研究了将两种理论结合用于不完备信息系统以进行规则提取,并用实例进行了验证.