改进Elman神经网络在短期热负荷预测中的应用

热电厂的短期热负荷预测在城市集中供暖中起着至关重要的作用,直接影响热电厂的经济效益和热能利用率。电厂的短期热负荷一般采用神经网络预测模型进行预测,而BP神经网络应用最为广泛。Elman神经网络算法在BP神经网络基础上加入了承接层,作为一步延时算子,实现记忆能力,使系统具备适应时变能力,增强系统全局稳定性。但Elman神经网络算法模型的构造依然需要大量样本的支撑,而且输入层的变量多,导致预测时间依然很长,收敛速度慢。该文在Elman神经网络预测前,进行了相关系数预处理和对样本中异常值的平均化预处理,通过数据归一化运算,使Elman神经网络输入层变量大幅减少。仿真实验表明,改进的Elman神经网络算法使预测模型快速寻优,减少预测时间的同时明显提高预测精度。     

Belief-Propagation-Approximated Decoding of Low-Density Parity-Check Codes

In this paper, we propose a new reduced-complexity decoding algorithm of Low-Density Parity-Check (LDPC) codes, called Belief-Propagation-Approximated (BPA) algorithm, which utilizes the idea of normalization and translates approximately the intricate nonlinear operation in the check nodes of the original BP algorithm to only one operation of looking up the table. The normalization factors can be obtained by simulation, or theoretically. Simulation results demonstrate that BPA algorithm exhibits fairly satisfactory bit error performance on the Additive White Gaussian Noise (AWGN) channel.     

多测井曲线的综合处理合成

测井曲线是地质分层的基础，但在利用单一测井曲线解决复杂地质问题时也存在多解性和局限性。为克服多解性，人们采用多种测井曲线进行地质分层，提高了分层的精度。本文在此基础上提出把多条曲线分别赋予不同的加权因子，然后进行归一化处理，形成一条标准综合参数测井曲线。此综合参数曲线突出了所选的多条测井曲线的公共信息，减少或削弱了单一测井曲线中的偶然误差，提高了综合后测井资料的可信度。该方法可应用于地质分层、岩性分析、含油气预测等诸多领域。应用时要注意，并非所选择的测井曲线种类越多越好，而是要选择那些最能反映地层单元特征信息的测井曲线。     

On the Consistency of the Normalized Eight-Point Algorithm

A recently proposed argument to explain the improved performance of the eight-point algorithm that results from using normalized data (Chojnacki, W., et al. in IEEE Trans. Pattern Anal. Mach. Intell. 25(9):1172–1177, 2003) relies upon adoption of a certain model for statistical data distribution. Under this model, the cost function that underlies the algorithm operating on the normalized data is statistically more advantageous than the cost function that underpins the algorithm using unnormalized data. Here we extend this explanation by introducing a more refined, structured model for data distribution. Under the extended model, the normalized eight-point algorithm turns out to be approximately consistent in a statistical sense. The proposed extension provides a link between the existing statistical rationalization of the normalized eight-point algorithm and the approach of Mühlich and Mester for enhancing total least squares estimation methods via equilibration. The paper forms part of a wider effort to rationalize and interrelate foundational methods in vision parameter estimation.     

A Multi-View Face Recognition System

In many automatic face recognition systems,posture constraining is a key factor preventing them from application.In this paper a series of strategies will be described to achieve a system which enables face recognition under varying pose.These approaches include the multi-view face modeling,the threschold image based face feature detection,the affine transformation based face posture normalization and the template matching based face identification.Combining all of these strategies,a face recognition system with the pose invariance is designed successfully,Using a 75MHZ Pentium PC and with a database of 75 individuals,15 images for each person,and 225 test images with various postures,a very good recognition rate of 96.89% is obtained.     

逻辑型多变量鲁棒自校正解耦间接算法

本文提出了一种多变量鲁棒自校正解耦间接算法。它采用一种新的正则化和相对死区实现了鲁棒自校正解耦控制。这种方法可以使系统跟踪特性不受死区界和正则化因子的影响。本文还给出了算法的鲁棒性分析和仿真结果。     

误差反向传播神经网络模型的改进及其应用

针对误差反向传播神经网络模型(BP模型)学习收敛速度慢、容易陷入局部极小点等缺点，提出原始数据的非线性规格化函数、记忆式初始权值、阈值和参数自动优选等方法，对BP模型进行改进。结合陆浑水库大坝沉降实测资料的分析，编制了改进后的BP网络算法程序。分析结果表明，改进后的BP模型对于提高网络运行收敛速度、防止陷入局部极小点、克服手工调试参数的盲目性、提高模型精度等都有较大的改善作用。     

水利水电施工企业项目管理浅析

阐述了水利水电施工企业项目管理的特点,就本施工企业实行项目管理的实践情况作了介绍,对施工企业如何进行规范化项目管理提出了建议。