双纵模热稳频激光源的模糊PID控制研究

为了满足激光拍频干涉仪所需要的高的频率稳定性的激光光源,研究了双纵模热稳频的机理。以控制激光管放电电流为主要热控制方式及自创的对激光管进行感应加热作为微量控制的先进方法为控制手段,采用模糊控制理论与专家系统相结合的控制策略,建立模糊PID控制器,对双纵模激光源进行稳频。无须建立被控对象数学模型,对时滞、非线形和时变性具有一定的适应能力。实验结果显示,稳频精度无明显变化,但预热时间明显缩短,抗干扰性明显增强,强干扰后也能迅速稳频。     

Intelligent optimal control for lead-zinc sintering process state

The intelligent integrated predictive model of synthetical permeability was established using the fuzzy classifier to combine the time sequence predictive model with the craftwork parameter predictive model. Then, the estimation model of bum-through point（BTP） based on pipe stress point（PSP） method and the predictive model of BTP were proposed. The optimal control of permeability and heat states was implemented by using the fuzzy expert controller with self-studying mechanism. The application of the intelligent control technique suppresses 17% of the fluctuation of synthetical permeability and 12% of the fluctuation of BTP, stabilizes the output and quality of sinter and settles the basis for the optimization of output and quality of sintering process.     

数据融合在电梯群控系统中的应用

将数据融合技术引入电梯群控系统中,建立了基于数据融合技术的模糊联结聚合神经网络模型,对影响电梯调度的各因素进行充分有效的数据处理后,得到的电梯控制参数作为电梯调度单元的输入.应用实例表明了该方法是方便且有效的.     

组合冲模CAD系统中的模具库管理及模糊查询

在组合冲模CAD系统中,模具装配图的数据库管理方法,对于能够按照特征信息正确保存和准确找出所需要的模具装配图是至关重要的.为能按照用户提出的在任意范围内进行检索,因而又提出了模糊查询的方法.     

耐磨白口铸铁的综合性能与价格比

采用模糊数学对耐磨白口铸铁性能进行综合分析,通过大量计算得出了耐磨白口铸铁的综合性能价格比,计算结果表明,在这些材料中,Cr27的综合性能价格比最好,Ni1最差,而Cr24,15-3和Ni4依次介于两者之间。本方法对于工程技术方案评价将具有实用价值。     

基于电容层析成像和模糊模式识别的油气两相流流型辨识新方法的研究

基于电容层析成像和模糊模式识别技术别提出了一种油气两相流流型辨识的新方法。建立了12电极电容层析成像流型自动识别系统，该系统利用Tikhonov正则化原理并结合SIRT(Simultaneous Reconstruction Techniques)算法进行图像重建。Tikhonov正则化原理用于克服图像重建过程中的不适定问题，SIRT算法用于提高最终重建图像的质量。根据流型的随机和模糊特性，提出了一种根据管截面重建图像进行流型辨识的模糊流型判别方法。研究结果表明，提出的流型辨识新方法是有效的。对于层状流、核心流、环状流、均相流等流型，流型辨识的准确率高于95％，辨识一个流型所用的时间小于0.3秒。对于塞状流，流型辨识的准确率高于90％。     

Interactive fuzzy stochastic multi-level 0–1 programming using tabu search and probability maximization

In this paper, we consider interactive fuzzy programming for multi-level 0–1 programming problems involving random variable coefficients both in objective functions and constraints. Following the probability maximization model together with the concept of chance constraints, the formulated stochastic multi-level 0–1 programming problems are transformed into deterministic ones. Taking into account vagueness of judgments of the decision makers, we present interactive fuzzy programming. In the proposed interactive method, after determining the fuzzy goals of the decision makers at all levels, a satisfactory solution is derived efficiently by updating satisfactory levels of the decision makers with considerations of overall satisfactory balance among all levels. For solving the transformed deterministic problems efficiently, we also introduce novel tabu search for general 0–1 programming problems. A numerical example for a three-level 0–1 programming problem is provided to illustrate the proposed method.     

Stabilization of Rössler chaotic dynamical system using fuzzy logic control algorithm

This paper proposes a fuzzy logic control algorithm (FLCA) to stabilize the Rössler chaotic dynamical system. The fuzzy logic control system is based on a Takagi-Sugeno-Kang inference engine and the stability analysis in the sense of Lyapunov is carried out using Lyapunov’s direct method. The new FLCA is formulated to offer sufficient inequality stability conditions. The asymptotic complexity of our algorithm is analyzed and proved to be lower in comparison with that of linear matrix inequality-based FLCAs. A set of simulation results illustrates the effectiveness of the proposed FLCA.     

Computer aided detection system for micro calcifications in digital mammograms

Breast cancer continues to be a significant public health problem in the world. Early detection is the key for improving breast cancer prognosis. Mammogram breast X-ray is considered the most reliable method in early detection of breast cancer. However, it is difficult for radiologists to provide both accurate and uniform evaluation for the enormous mammograms generated in widespread screening. Micro calcification clusters (MCCs) and masses are the two most important signs for the breast cancer, and their automated detection is very valuable for early breast cancer diagnosis. The main objective is to discuss the computer-aided detection system that has been proposed to assist the radiologists in detecting the specific abnormalities and improving the diagnostic accuracy in making the diagnostic decisions by applying techniques splits into three-steps procedure beginning with enhancement by using Histogram equalization (HE) and Morphological Enhancement, followed by segmentation based on Otsu's threshold the region of interest for the identification of micro calcifications and mass lesions, and at last classification stage, which classify between normal and micro calcifications ‘patterns and then classify between benign and malignant micro calcifications. In classification stage; three methods were used, the voting K-Nearest Neighbor classifier (K-NN) with prediction accuracy of 73%, Support Vector Machine classifier (SVM) with prediction accuracy of 83%, and Artificial Neural Network classifier (ANN) with prediction accuracy of 77%.