基于像素运动的图像模糊机理与恢复技术

从像素运动的角度分析了因运动造成图像模糊的实际过程，根据模糊图像像素间的关系建立了一维和二维匀速直线运动所造成的模糊图像的模糊模型，进而由模糊过程的逆过程给出了恢复模型。最后对匀速直线运动造成的图像模糊进行了模拟和恢复,取得了令人满意的 效果。

南方沿海地区电网标识牌褪色模糊机理分析

南方沿海地区湿度大、盐雾多、太阳光照时间长、紫外线强、雨水多、微生物活跃、工业区分布广,对电网标识牌寿命有较大影响。而现有的电网标识牌褪色模糊研究分析仅停留在现象表面,因此,从电网使用环境和材质本身深入分析电网标识牌褪色模糊机理,并提出褪色模糊防治措施以减缓电网标识牌褪色模糊速率,延长其使用寿命,为电网标识牌防褪色模糊防治提供了新的思路。

采用瞄准式杀伤技术的防空导弹总体问题研究

定向战斗部技术是利用目标方位信息通过导弹弹体变化或战斗部起爆逻辑控制改变爆破方向以取得最大毁伤效果的新型杀伤技术,是未来新一代防空导弹实现能力跨越的关键技术之一。以装备有径向转向式定向战斗部的瞄准杀伤式防空导弹为研究对象,着重研究了相关总体问题。研究了补偿导弹法向过载的脱靶信息预测方法,满足了瞄准式杀伤提前获取脱靶信息的需求;研究了预测着靶点的散布规律和预测模糊问题的形成机理,为解决模糊问题提供了理论支撑;研究了小脱靶量遭遇时的瞄准精确度提升方法;对瞄准杀伤式防空导弹实例进行了仿真。

一种模糊参数自适应控制器在直接转矩控制中的应用

采用一种基于模糊理论的自适应控制器作为三相异步电机直接转矩控制系统的速度调节器。重点介绍了控制器的模糊控制规则和模糊推理机理。试验证明比传统的PI控制器优越。

基于模糊加权最小二乘支持向量回归的非线性系统建模方法

针对非线性系统建模时边界数据会产生较大的建模偏差、数据计算负荷大以及如何从数据集中选取K个近邻点才能保证其性能缺乏统一标准等问题,提出了基于模糊加权最小二乘支持向量回归的非线性系统建模方法。该方法融合了模糊加权机理与最小二乘支持向量回归的优点,通过引入重叠因子,在保证建模精度(均方根误差越小越好)的情况下,去除建模过程中的一些非重要数据,减小建模方法的运算时间,并能将全局与局部建模方法相融合有效解决局部建模方法所产生的边界效应问题。实验验证结果表明,分别对几种方法从训练/测试均方根误差、不同重叠因子、计算时间方面比较都有明显的有效性和优越性。

ESTIMATION METHOD FOR AIRCRAFT SIMILARITY BASED ON FUZZY THEORY AND GREY INCIDENCE ANALYSIS

An estimation method for aircraft similarity based on fuzzy theory and grey incidence analysis is presented. This estimation method is made up of the triangular fuzzy transforming model of linguistic variables and the method of grey incidence analysis. Nine feature attributes of aircraft are selected to estimate the similarity between the new aircraft and the existing aircraft. A new aircraft X and other six existing aircrafts are taken as examples. Analyses show that similarity estimation results obtained from the method are in accordance with practice.

GRADE-LIFE PROGNOSTIC MODEL OF AIRCRAFT ENGINE BEARING

Research on practical and verifiable prediction methods for the service life of bearings plays a critical role in improving the reliability and safety of aircraft engines. The concept of grade-life （GL） is introduced to de- scribe the service life of bearings. A GL prognostic model for aircraft engine bearings is proposed based on sup- port vector machine （SVM） and fuzzy logic inference. Firstly, the mathematical model is discussed to predict the physics-based GL （PGL）. Then, the diagnostic estimation model based on SVM is presented in detail to predict the empirical GL （EPL）. Thirdly, a fuzzy logic inference is adopted to fuse two GL predicted results. Finally, the GL prognostic model is verified by the run-to-failure data acquired from an accelerated life test of an aircraft bearing. The results show that the model provides a more practical and reliable prediction for the service life of bearings.

APPLICATION OF FUZZY INFERENCE IN IDENTIFICATION OF HELICOPTER MODEL

Helicopter mathematical model mainly depends on design helicopter control system, flight simulator, and real time control simulation system. But it is difficult to establish a helicopter flight dynamics mathematical model that has features such as rapidness, reliability and precision, because there is no unique and precise expression to some sophisticated phenomenon of helicopter. In this paper a fuzzy helicopter flight model is constructed based on the flight experimental data. The fuzzy model, which is identified by fuzzy inference, has characteristics of computed rapidness and high precision. In order to guarantee the precision of the identified fuzzy model, a new method is adopted to handle the conflict fuzzy rules. Additionally, using fuzzy clustering technology can effectively reduce the number of rules of fuzzy model, namely, the order of the fuzzy model. The simulation results indicate that the method of this paper is effective and feasible.

Developmental ecology of the American horseshoe crab Limulus polyphemus

During spawning events, horseshoe crab eggs are released from the female＇s oviducts, and fertilized by one or more males. Eggs are shaped by the female into discrete clutches deposited in nests at depths of 10-20 cm on intertidal estuarine beaches. Distinguishing between fxesh eggs and the early developmental stages is obfuscated by the large amount of dense, opaque yolk. The first unambiguous confirmation of development is the formation of the rudimentary prosomatie appendages at the ＂limb bud＂ stage. Several days thereafter, the outer chorion is shed and the developing embryo expands and undergoes a series of molts within the clear inner egg membrane. The trilobite （first iustar） stage thus attained may remain within the beach sedi- ments for several more weeks, until hatching is facilitated by environmental factors such as hydration, agitation, and osmotic shock that accompany the infiltration of seawater into the nests. Trilobites exhibit endogenous eirgatidal swimming rhythms that are entrained by mechanical agitation, suggesting that peaks in larval swimming are timed to coincide with periods of high water and the inundation of the nests. Larval swimming is limited and does not appear to result in long-distance dispersal. The limited dispersal of the larvae has important implications for the population dynamics of relatively isolated populations. The rate of larval development is highly plastic and is influenced by temperature, salinity, dissolved oxygen, and the presence of pollutants. The broad environmental tolerances of horseshoe crab embryos and larvae are important in understanding their current geographic distribution and their evolutionary persistence

Development of single-chip fuzzy controller based on FFSI in binary

Length and concise structure of fuzzy logic reasoning program and its real-time reasoning characteris-tic have their effect on the performance of a digital single-chip fuzzy controller. The control effect of a digitalfuzzy controller based on looking up fuzzy control responding table is only relative to the table and not relative tothe fuzzy control rules in the practical control process. Aiming at above problem and having combined fuzzy log-ic reasoning with digital operational characteristics of a single-chip microcomputer, functioning-fuzzy-subset in-ference (FFSI) in binary, in which triangle membership functions of error and error-in-change are all represen-ted in binary and singleton membership functions of control variable is binary too, has been introduced. The cir-cuit principle plans of a single-chip fuzzy controller have been introduced for development of its hardware, andthe primary program structure, fuzzy logic reasoning subroutine, serial communication subroutine with PC andreliability design of the fuzzy controller are all discussed in detail. The control of indoor temperature by a fuzzycontroller has been conducted using a testing-room thermodynamic system. Research results show that the FFSIin binary can exercise a concise fuzzy control in a single-chip fuzzy controller, and the fuzzy controller is there-fore reliable and possesses a high performance-price ratio.

Influence of driver’s yielding behavior on pedestrian-vehicle conflicts at a two-lane roundabout using fuzzy cellular automata

The roundabouts are widely used in China,some of which have central islands as scenic spots.The crosswalks connecting to the central islands,normally full of pedestrians,have negative impact on roundabout capability and pedestrian safety.Therefore,this study proposes a fuzzy cellular automata(FCA)model to explore the safety and efficiency impacts of pedestrian-vehicle conflicts at a two-lane roundabout.To reason the decision-making process of individual drivers before crosswalks,membership functions in the fuzzy inference system were calibrated with field data conducted in Changsha,China.Using specific indicators of efficiency and safety performance,it was shown that circulating vehicles can move smoothly in low traffic flow,but the roundabout system is prone to the traffic congestion if traffic flow reaches to a certain level.Also,the high yielding rate of drivers has a negative impact on the traffic efficiency but can improve pedestrian safety.Furthermore,a pedestrian restriction measure was deduced for the roundabout crosswalk from the FCA model and national guideline of setting traffic lights.

Path-tracking Control of a Tractor-aircraft System

An aircraft tractor plays a significant role as a kind of important marine transport and support equipment. It＇s necessary to study its controlling and manoeuvring stability to improve operation efficiency. A virtual prototyping model of the tractor-aircraft system based on Lagrange＇s equation of the first kind with Lagrange mutipliers was established in this paper, According to the towing characteristics, a path-tracking controller using fuzzy logic theory was designed. Direction control herein was carried out through a compensatory tracking approach. Interactive co-simulation was performed to validate the path-tracking behavior in closed-loop, Simulation results indicated that the tractor followed the reference courses precisely on a flat ground.

Fuzzy TOPSIS method to primary crusher selection for Golegohar Iron Mine(Iran)

Selection of the crusher required a great deal of design regarding to the mine planning. Selection of suitable primary crusher from all of available primary crushers is a multi-criterion decision making(MCDM) problem. The present work explores the use of technique for order performance by similarity to ideal solution(TOPSIS) with fuzzy set theory to select best primary crusher for Golegohar Iron Mine in Iran. Gyratory, double toggle jaw, single toggle jaw, high speed roll crusher, low speed sizer, impact crusher, hammer mill and feeder breaker crushers have been considered as alternatives. Also, the capacity, feed size, product size, rock compressive strength, abrasion index and application of primary crusher for mobile plants were considered as criteria for solution of this MCDM problem. To determine the order of the alternatives, closeness coefficient is defined by calculating the distances to the fuzzy positive ideal solution(FPIS) and fuzzy negative ideal solution(FNIS). Results of our work based on fuzzy TOPSIS method show that the gyratory is the best primary crusher for the studied mine.

Status Evaluation of Loose of Jig Bed Based on Fuzzy Inference System

This paper mainly describes that loose of jig bed affects jig's separation effect, and the corresponding fuzzy rules were built. Using the evaluating index of jig's separation effect--imperfection (I) and total misplaced material (Cz), it evaluates status of loose of jig bed by fuzzy inference system. Experimental simulation and applications in practice prove the method's feasibility.

Fuzzy Comprehensive Assessment Method to Determine Tectonic Stress Patterns

The tectonic stress patterns were determined by a fuzzy comprehensive assessment method. Data of in-situ survey and fault information were utilized in the method. First, by making pressure and tension in the directions of along-river, cross-river, shear clockwise, and shear counterclockwise , 26 types of tectonic stress patterns were presented. And the stress vector of each pattern was obtained with FE software by taking unit displacement as boundary load. Then, by taking the 26 types of tectonic stress patterns as index set and 3 main stresses as factor set and choosing various operators, comparison of directions of computational stress vector and survey stress vector was made and the most possible tectonic stress pattern was obtained. Taking the 26 types of tectonic stress patterns as index set and strike angle as factor set, comparison of relationships between formation of fault and tectonic stress was made,and the tectonic stress patterns were assessed with known fault information. By summarizing the above assessment results, the most impossible tectonic stress pattern was obtained . Finally an engineering case was quoted to validate that the method is more feasible and reliable than traditional empirical method.

Generating Fuzzy Rule-based Systems from Examples Based on Robust Support Vector Machine

This paper firstly proposes a new support vector machine regression (SVR) with a robust loss function, and designs a gradient based algorithm for implementation of the SVR, then uses the SVR to extract fuzzy rules and designs fuzzy rule-based system. Simulations show that fuzzy rule-based system technique based on robust SVR achieves superior performance to the conventional fuzzy inference method, the proposed method provides satisfactory performance with excellent approximation and generalization property than the existing algorithm.

Probabilistic Fuzzy Hypermodules

We introduce the concept of T-fuzzy subhypermodules of hypermodules with respect to triangular norms and obtain some results. In particular, we define a probabilistic version of hypermodules using random sets and show that fuzzy hypermodules defined in triangular norms are consequences of probabilistic hypermodules under certain conditions.

Objective function of cost in optimal tolerance allocation

An objective function model is proposed for cost in optimizing and allocating tolerance with consideration of manufacturing conditions. With the fuzzy comprehensive evaluation method,a manufacturing difficulty coefficient is derived,which takes into account of several factors affecting the manufacturing cost,including the forming means of the blank,size,machining surface features,operator’s skills and machinability of materials. The coefficient is then converted into a weight factor used in the inversed square model representing the relationship between the cost and tolerance,and,hence,an objective function for cost is established in optimizing and allocating tolerance. The higher is the manufacturing difficulty coefficient,the higher is the relative manufacturing cost and the higher is the weight factor of the tolerance allocation,which indicates the increase of the tolerance’s effects on the total manufacturing cost and,therefore,a larger tolerance should be allocated. The computer-aided tolerance allocation utilizing this model makes it more convenient,accurate and practicable.

Application of Fuzzy Automata Theory and Knowledge Based Neural Networks for Development of Basic Learning Model

The paper focuses on amalgamation of automata theory and fuzzy language. It uses adaptive knowledge based abstract framework which uses dynamic neural network framework along with fuzzy automata as Models of Learning, combining the two methodologies the authors develop a new framework termed as Fuzzy Automata based Neural Network （FANN）. It highlights conversion of knowledge rule to fuzzy automata thereby generating a framework FANN. FANN consists of composite fuzzy automation divided into ＂Performance Evaluator＂ and ＂Feature Extraction＂ which takes the help of previously stored samples of similar situations. The authors have extended FANN for Urban Traffic Modeling.

Modeling Multisource-heterogeneous Information Based on Random Set and Fuzzy Set Theory

This paper presents a new idea, named as modeling multisensor-heterogeneous information, to incorporate the fuzzy logic methodologies with mulitsensor-multitarget system under the framework of random set theory. Firstly, based on strong random set and weak random set, the unified form to describe both data (unambiguous information) and fuzzy evidence (uncertain information) is introduced. Secondly, according to signatures of fuzzy evidence, two Bayesian-markov nonlinear measurement models are proposed to fuse effectively data and fuzzy evidence. Thirdly, by use of "the models-based signature-matching scheme", the operation of the statistics of fuzzy evidence defined as random set can be translated into that of the membership functions of relative point state variables. These works are the basis to construct qualitative measurement models and to fuse data and fuzzy evidence.