A neurofuzzy system based on rough set theory and genetic algorithm

This paper presents a hybrid soft computing modeling approach for a neurofuzzy system based on rough set theory and the genetic algorithms ( NFRSGA ). The fundamental problem of a neurofuzzy system is that when the input dimension increases, the fuzzy rule base increases exponentially. This leads to a huge infrastructure network which results in slow convergence. To solve this problem, rough set theory is used to obtain the reductive rules, which are used as fuzzy rules of the fuzzy system. The number of rules decrease, and each rule does not need all the conditional attribute values. This results in a reduced, or not fully connected, neural network. The structure of the neural network is relatively small and thus the weights to be trained decrease. The genetic algorithm is used to search the optimal discretization of the continuous attributes. The NFRSGA approach has been applied in the practical application of building a soft sensor model for estimating the freezing point of the light diesel fuel in a Fluid Catalytic Cracking Unit (FCCU) , and satisfying results are obtained.     

Fundamental algorithm and computational codes for the light beam propagation in high power laser system

The fundamental algorithm of light beam propagation in high power laser system is investigated and the corresponding computational codes are given. It is shown that the number of modulation ring due to the diffraction is related to the size of the pinhole in spatial filter (in terms of the times of diffraction limitation, i. e. TDL) and the Fresnel number of the laser system; for the complex laser system with multi-spatial filters and free space, the system can be investigated by the reciprocal rule of operators.     

Design of systolic BN circuits in Galois fields based on quaternary logic

The BNoperation is known as an efficient basic operation in Galois fields GF(2k),and various algorithms and implementations using binary logic signals have already been proposed.In order to reduce the circuit complexity and long latency of BNoperations,a novel algorithm and its systolic architecture are proposed based on multiple-value logic(MVL).In the very large scale integration(VLSI)realization,a kind of multiple-valued current-mode(MVCM)circuit structure is presented and in which the combination of dynamic source-coupled logic(SCL)and different-pair circuits(DPCs)is employed to improve the switching speed and reduce the power dissipation.The performance is evaluated by HSPICE simulation with 0.18μm CMOS technology.The transistor numbers and the delay are superior to corresponding binary CMOS implementation.The combination of MVCM circuits and relevant algorithms based on MVL seems to be potential solution for high performance arithmetic operationsin Galois fields GF(2k).     

FUZZY REASONING IN CYCLES

By the similarity between the syllogism in logic and a path proposition in graph theory,a new concept,fuzzy reasoning graph G has been given in this paper. Transitive closure has been studied and used to do reasoning related to self-loop in G,and an algorithm has been designed to cope with reasoning in other cycles in G. Both approaches are applicable and efficient.     

Adaptive ANFIS-based filter for active control of sinusoidal primary noise in nonlinear path

Linear active noise control (ANC) system is promising in suppressing broadband and narrowband noise in a linear acoustic site.However,in some situations,the acoustic systems are nonlinear which make the primary noise being nonlinear distortion at the canceling point,and the linear ANC system maybe can not work well for these cases.This paper presents an adaptive network-based fuzzy inference system (ANFIS)-based nonlinear filter for active noise control,which is expected to be successfully applied to situations with nonlinear distortion.In the proposed adaptive control algorithm,the parameters are updated by gradient descent method.In the simulations,the secondary-path FIR model coefficients are estimated in advance by off-line system identification method,and one case for sinusoidal primary noise with nonlinear distortion is presented,which verifies the effectiveness of the proposed system in suppressing sinusoidal noise generated by rotating machines,e.g.,engines in vehicles.     

Discrete logistics network design model under interval hierarchical OD demand based on interval genetic algorithm

Aimed at the uncertain characteristics of discrete logistics network design,an interval hierarchical triangular uncertain OD demand model based on interval demand and network flow is presented.Under consideration of the system profit,the uncertain demand of logistics network is measured by interval variables and interval parameters,and an interval planning model of discrete logistics network is established.The risk coefficient and maximum constrained deviation are defined to realize the certain transformation of the model.By integrating interval algorithm and genetic algorithm,an interval hierarchical optimal genetic algorithm is proposed to solve the model.It is shown by a tested example that in the same scenario condition an interval solution [3 275.3,3 603.7] can be obtained by the model and algorithm which is obviously better than the single precise optimal solution by stochastic or fuzzy algorithm,so it can be reflected that the model and algorithm have more stronger operability and the solution result has superiority to scenario decision.     

SVD Approach for Actuator and Sensor Placement in Active Vibration Control of Large Cable Net Structures

The actuator and sensor placement problem for active vibration control of large cable net structures is investigated in this paper. Since the structures exhibit closely spaced modes in the range of low frequencies, the number of modes to be considered is quite large after modal truncation, while only a limited number of actuators and sensors are to be placed. This makes it hard to determine the actuator and sensor locations with the existing placement methods in the literature such as the methods based on the controllability/observability grammian. To deal with this issue, an actuator and sensor placement method based on singular value decompositions (SVD) of the input and output matrices is proposed, which guarantees the modal controllability and observability of the system. The effectiveness of the SVD based method is verified through numerical simulations in which comparisons are conducted between randomly-chosen locations and the optimal ones obtained by a genetic algorithm.     

A fuzzy neural network evolved by particle swarm optimization

A cooperative system of a fuzzy logic model and a fuzzy neural network(CSFLMFNN)is proposed,in which a fuzzy logic model is acquired from domain experts and a fuzzy neural network is generated and prewired according to the model.Then PSO-CSFLMFNN is constructed by introducing particle swarm optimization(PSO)into the cooperative system instead of the commonly used evolutionary algorithms to evolve the prewired fuzzy neural network.The evolutionary fuzzy neural network implements accuracy fuzzy inference without rule matching.PSO-CSFLMFNN is applied to the intelligent fault diagnosis for a petrochemical engineering equipment,in which the cooperative system is proved to be effective.It is shown by the applied results that the performance of the evolutionary fuzzy neural network outperforms remarkably that of the one evolved by genetic algorithm in the convergence rate and the generalization precision.     

Simulation and optimization of SOFC-BCHP system

As the prime motor of dispersed energy system, the high-temperature solid oxide fuel cells (SOFC) are high efficient with large heat recovery. This study presents a simulation of SOFC building-based cooling, heat and power (BCHP) system, which can meet basic requirements in power and heating (cooling) of the designated customers. The peak power load can be met by power grid, while the peak heating (cooling) load requirement can be met by backup equipments. In order to solve the economic dispatch problem of the energy system, a restricted nonlinear optimization model has been developed. The production costs can be minimized via both the equality constraints of customer’s heat and power demands, and other inequality constrains of equipments’ capacities. The sequential quadratic programming method has been used to search the solution. The study indicates that the model can be used to optimize the system’s capacities and run strategy. An office building case has been computed, and it is indicated that the model can be served in design and optimization of SOFC-BCHP system.     

The even device fabricated by the deep etched binary optics technology for the exposure system of the quasi-molecule laser

By applying the specific properties and the fabricating technology of the deep etched elements presented by us, the even device of deep etched binary optics has been designed and fabricated which can be used in quasi-molecule laser exposure system. This even device is light in weight, easy to adjust and has a high utilization rate of energy and is able to project well-distributed light beams. So it is better than the conventional one which was an array made up of quartz sticks. The properties and designed parameters were studied and simulated. The fabricated even was precisely tested by high precision Alpha-Steper. The testing result of the surface relief structures of the even has been profoundly analyzed by introducing "boundary errors". The theory agrees well with the results of the experiment. This is the first successful application of the deep etched theory and technology of binary optics to the exposure system of microfabrication.     

Theory of Ω-(α-tautologies) in revised Kleene systems

That there are only three different kinds of α-tautologies in revised Kleene systems is proved first; then in finite case the diversity theorem of α-tautologies with α's larger than the mid-value is established. Lastly, also in finite case, a representation theorem of α-tautologies by means of tautologies is given. Project supported by the National Natural Science Foundation of China (Grant No. 19331030).     

广义系统的状态估计方法

讨论了广义离散随机线系统的状态估计问题，在基本假设条件下，得到了系统状态的最优递推估计算法，算法同时给出了系统动态噪声的估计。     

关于部分Bent函数

首先从广义部分Bent函数的定义出发,利用线性变换的若干理论,证明Galois域上广义部分Bent函数等价于广义Bent函数与仿射函数之和.该结论覆盖了文献[1]的主要结果.然后给出关于部分Bent函数的类似结论,改进了Claud Carlet的关于部分Bent函数的结论.作为新结论的具体应用,最后修正了参考文献中的两个结论.     

Banach空间上广义p-正常算子的注记

广义p-共轭算子和广义p-正常算子的概念在文献和中分别引入。本文中,我们得出拟相似广义p-正常算子的一个谱性质以及广义p-正常算子亦有(Ac)性质;我们证明了广义p-自伴算子是纯量型谱算子。从而回答了D.K.Scn提出的一个问题[5,Note2.26].     

地形跟随系统中的自校正阵风减缓控制

本文对隐式多维极点配置广义最小方差自校正控制在地形跟随系统中的应用进行了研究。所采用的算法结构，可以满足飞机跟踪精度的要求，克服了选取加权因子的困难。并且，选取独立于加权因子的参数来实现在线调整加权因子，使闭环极点能够迅速地处于期望的位置上。仿真结果表明，系统的动态性能符合要求，跟踪误差也在允许的范围之内。     

基于广义分布式天线阵的MIMO检测

针对超3代（B3G）系统中广义分布式天线阵的架构，提出了适用于多个多天线阵中多输入多输出（MIMO）结构的交叉迭代检测译码算法. 该算法通过在多天线阵之间交叉传递信息的方式，将传统的贝尔实验室分层空时码（BLAST）译码算法与干扰删除操作结合起来，实现交叉迭代译码，有效地解决了广义分布式天线阵系统中相邻天线阵覆盖范围内使用相同资源用户之间的干扰问题，改善了系统性能.     

系数矩阵为块三对角的线性方程组的并行算法

给出了一种求解系数矩阵为块三对角的线性方程组的适合于ＭＩＭＤ型机的并行算法。从理论上证明了他与ＢＳＯＲ方法有相同的收敛速度，且与块Ｊａｃｏｂｉ方法有相同的并行性，并用一个算例在Ｍｕｌｔｉ－ＴｒａｎｓｐｕｔｅｒＳｙｓｔｅｍ模型机上作了计算，证明了他的有效性与可行性。     

数控加工仿真中刀具扫描体算法研究

运用包络理论推导出一种刀具扫描体算法，并用Ｃ语言实现。该算法通过求解刀具运动所形成的包络面方程计算刀具扫描体，计算量小，运算速度快。     

亏损阻尼系统的模态灵敏度分析算法

提出了亏损振动系统的模态灵敏度分析的算法。首先将N维向量空间中描述的亏损振动系统转入2N维广义状态空间中，再利用广义状态向量及其伴随向量系的解耦性能，解耦广义状态空间中的灵敏度控制方程，并利用移频技术求解广义状态向量的灵敏度；其次建立了2N维广义状态向量与N维亏损系统模态向量之间的联系；最后将广义状态向量灵敏度算法平移至模态向量，从而建立了亏损振动系统模态向量灵敏度分析的移频算法。该算法可用于拥有各种类型Jordan块的亏损系统，结构紧凑，应用灵活，具有较强的工程应用性。数值算例的结果说明了该算法是可行且有效的。     

非线性序集逻辑系统L4^2中命题真度值在[0，1]上的分布

利用势为4的均匀概率空间的无穷乘积在四值逻辑系统中引入公式的真度概念，给出了真度推理规则，证明了真值集为非线性序集四值逻辑系统L4^2中全体公式的真度值之集在[0，1]上是稠密的，为进一步建立四值非线性序集逻辑系统的近似推理理论奠定了基础．