遗传算法优化性能评价准则研究

为了克服传统遗传算法优化性能评价准则(如在线性能、离线性能)忽略随机因素对算法的影响,从而不能准确评价算法性能的缺点,提出了一种基于平均偏离距和偏离距标准差的新的遗传算法优化性能评价准则,给出了平均偏离距和偏离距标准差的数学定义,并分析了它们的泛函意义.由于平均偏离距和偏离距标准差采用遗传算法多次运行结果的统计参数来评价算法的性能,因此能够较好地消除随机因素对算法性能的影响.同时,应用所提出的评价准则研究了二进制码和格雷码对遗传算法优化性能的影响.基于F2函数的数值实验结果表明,与二进制码相比,格雷码的平均偏离距和偏离距标准差指标都比较低,因此能够更好地提高遗传算法的优化性能.

竞选算法的参数设计与性能研究

提出采用在线性能评估准则和离线性能评估准则评价竞选算法用于数值优化问题时的性能。通过对标准测试函数的数值优化实验,分析竞选算法的参数对算法在线性能和离线性能的影响,为竞选算法实际应用时的参数选择提供依据。实验结果表明,通过控制参数的改变,可有效改善竞选算法的在线性能和离线性能。

粒子群算法及特性的研究

研究了粒子群优化算法,探讨了算法的在线与离线性能指标,在此基础上,将粒子群算法与罚函数相结合,提出一种求解有约束问题的优化算法,用MATLAB实现了对典型多峰函数优化计算,仿真结果表明验证了它的收敛性、有效性,对典型的优化问题能以较大概率收敛到全局最优.

Effect of linear carboxylic ester on low temperature performance of LiMn_2O_4-graphite cells

To improve the low-temperature performances of Li-ion cells, three types of linear carboxylic ester-based electrolyte, such as EC/EMC/EA（1：1：2, mass ratio）, EC/EMC/EP（1：1：2, mass ratio） and EC/EMC/EB（1：1：2, mass ratio）, were prepared to substitute for industrial electrolyte（EC/EMC/DMC）. Then, 18650-type Li Mn2O4-graphite cells（nominal capacity of 1150 mA ·h） were assembled and studied. Results show that the cells containing three types of electrolyte are able to undertake 5C discharging current with above 93% capacity retention at-20 °C. Electrochemical impedance spectra show that the discharge capacity fading of Li-ion cells at low temperature is mainly ascribed to the charge transfer resistance increasing with temperature decreasing. In comparison, the cells containing electrolyte of 1.0 mol/L LiPF6 in EC/EMC/EA（1：1：2, mass ratio） have the highest capacity retention of 90% at-40 °C and 44.41% at-60 °C, due to its lowest charge-transfer resistance.

Separation method for multi-source blended seismic data

Multi-source seismic technology is an efficient seismic acquisition method that requires a group of blended seismic data to be separated into single-source seismic data for subsequent processing. The separation of blended seismic data is a linear inverse problem. According to the relationship between the shooting number and the simultaneous source number of the acquisition system, this separation of blended seismic data is divided into an easily determined or overdetermined linear inverse problem and an underdetermined linear inverse problem that is difficult to solve. For the latter, this paper presents an optimization method that imposes the sparsity constraint on wavefields to construct the object function of inversion, and the problem is solved by using the iterative thresholding method. For the most extremely underdetermined separation problem with single-shooting and multiple sources, this paper presents a method of pseudo-deblending with random noise filtering. In this method, approximate common shot gathers are received through the pseudo-deblending process, and the random noises that appear when the approximate common shot gathers are sorted into common receiver gathers are eliminated through filtering methods. The separation methods proposed in this paper are applied to three types of numerical simulation data, including pure data without noise, data with random noise, and data with linear regular noise to obtain satisfactory results. The noise suppression effects of these methods are sufficient, particularly with single-shooting blended seismic data, which verifies the effectiveness of the proposed methods.

Optimal Guaranteed Cost Control via Static Output Feedback for Uncertain Discrete Time Systems

Aim To study the optimal guaranteed cost control problem via static output feedback for uncertain linear discrete time systems with norm bounded parameter uncertainty in both the state and the control input matrices of the state space model. Methods\ An upper bound on a quadratic cost index was found for all admissible parameter uncertainties and minimized by using Lagrange multiplier approach. Results and Conclusion\ Sufficient conditions are given for the existence of a controller guaranteeing the closed loop system quadratic stability and providing an optimized bound. A numerical algorithm for solving the output feedback gain is also presented.

Secure Communication via Chaotic Masking *

A novel secure communication approach via chaotic masking is proposed. At the transmitter, a message sequence is added to a chaotic masking sequence and is,at the same time, also involved in the generation of the masking sequence. At the receiver, a non dynamical system which adopts the same nonlinear functions as what is adopted at transmitter is used to retrieve the masking sequence from the received signal and then the message sequence is recovered through subtraction. The results of the theoretical analysis and computer simulation show that the chaotic digital secure communication system presented in this paper has the fine security, high reliability and can be implemented easily.

DESIGN OF A NOVEL NONLINEAR DISORETE-TIME CONTROLMETHOD FOR SWITOHING OONVERTERS

Based on the high frequency and large signal discrete-time model for switching converters,a nonlinear discrete-time control method is designed on the principle of dynamic programming. In one switch period the optimal duty ratio is got in accordance with a minimum error of the output voltage,then the duty ratio is checked and regulated with the energy function in order to make the global performance best. In thisway the complete objective function is obtained. Based on the objective function,the fast and accurate control effect is accomplished.

A Block-Adaptive Blind Separation Algorithm for Post-Nonlinear Mixture of Sub- and Super-Gaussian Signals

The problem of blind separation of signals in post nonlinear mixture is addressed in this paper. The post nonlinear mixture is formed by a component wise nonlinear distortion after the linear mixture. Hence a nonlinear adjusting part placed in front of the linear separation structure is needed to compensate for the distortion in separating such signals. The learning rules for the post nonlinear separation structure are derived by a maximum likelihood approach. An algorithm for blind separation of post nonlinearly mixed sub and super Gaussian signals is proposed based on some previous work. Multilayer perceptrons are used in this algorithm to model the nonlinear part of the separation structure. The algorithm switches between sub and super Gaussian probability models during learning according to a stability condition and operates in a block adaptive manner. The effectiveness of the algorithm is verified by experiments on simulated and real world signals.

Assessment of different genetic distances in constructing cotton core subset by genotypic values

One hundred and sixty-eight genotypes of cotton from the same growing region were used as a germplasm group to study the validity of different genetic distances in constructing cotton core subset. Mixed linear model approach was employed to unbiasedly predict genotypic values of 20 traits for eliminating the environmental effect. Six commonly used genetic distances(Euclidean,standardized Euclidean,Mahalanobis,city block,cosine and correlation distances) combining four commonly used hierarchical cluster methods(single distance,complete distance,unweighted pair-group average and Ward's methods) were used in the least distance stepwise sampling(LDSS) method for constructing different core subsets. The analyses of variance(ANOVA) of different evaluating parameters showed that the validities of cosine and correlation distances were inferior to those of Euclidean,standardized Euclidean,Mahalanobis and city block distances. Standardized Euclidean distance was slightly more effective than Euclidean,Mahalanobis and city block distances. The principal analysis validated standardized Euclidean distance in the course of constructing practical core subsets. The covariance matrix of accessions might be ill-conditioned when Mahalanobis distance was used to calculate genetic distance at low sampling percentages,which led to bias in small-sized core subset construction. The standardized Euclidean distance is recommended in core subset construction with LDSS method.

A Non-linear Non-ideal Model of Simulated Moving Bed Chromatography for Chiral Separations

A non-linear non-ideal model, taking into account non-linear competitive isotherms, axial dispersion, film mass transfer, intraparticle diffusion, and port periodic switching, was developed to simulate the dynamics of simulated moving bed chromatography (SMBC). The model equations were solved by a new efficient numerical technique of orthogonal collocation on finite elements with periodical movement of concentration vector. The simulated SMBC performance is in accordance with the experimental results reported in the literature for separation of l,1'-bi-2-naphthol enantiomers using SMBC. This model is useful for design, operation, optimization and scale-up of non-linear SMBC for chiral separations with significant non-ideal effects, especially for high solute concentration and small intraparticle diffusion coefficient or large chiral stationary phase particle.

Mixed Gl2／GH2 multi-channel multi-objective control synthesis for discrete time systems

This paper proposes a new approach for multi-objective robust control. The approach extends the standard generalized l2 (Gl2) and generalized H2 (GH2) conditions to a set of new linear matrix inequality (LMI) constraints based on a new stability condition. A technique for variable parameterization is introduced to the multi-objective control problem to preserve the linearity of the synthesis variables. Consequently, the multi-channel multi-objective mixed Gl2/GH2 control problem can be solved less conservatively using computationally tractable algorithms developed in the paper.

Prolongation Structure of Semi-discrete Nonlinear Evolution Equations

Based on noncommutative differential calculus, we present a theory of prolongation structure for semidiscrete non/inear evolution equations. As an illustrative example, a semi-discrete model of the non/inear SchrSdinger equation is discussed in terms of this theory and the corresponding Lax pairs are also given.

Performance of the geometric approach to fault detection and isolation in SISO,MISO,SIMO and MIMO systems

In this paper, a geometric approach to fault detection and isolation （FDI） is applied to a Multiple-Input Multipie-Output （MIMO） model of a frame and the FDI results are compared to the ones obtained in the Single-Input Single-Output （SISO）, Multiple-Input Single-Output （MISO）, and Single-Input Multiple-Output （SIMO） cases. A proper distance function based on parameters obtained from parametric system identification method is used in the geometric approach. ARX （Auto Regressive with exogenous input） and VARX （Vector ARX） models with 12 parameters are used in all of the above-mentioned models. The obtained results reveal that by increasing the number of inputs, the classification errors reduce, even in the case of applying only one of the inputs in the computations. Furthermore, increasing the number of measured outputs in the FDI scheme results in decreasing classification errors. Also, it is shown that by using probabilistic space in the distance function, fault diagnosis scheme has better performance in comparison with the deterministic one.

Interaction Between Line Soliton and Algebraic Soliton for Asymmetric Nizhnik-Novikov-Veselov Equation

Starting from the variable separation approach, the algebraic soliton solution and the solution describing the interaction between line soliton and algebraic soliton are obtained by selecting appropriate seed solution for （2＋1）-dimensional ANNV equation. The behaviors of interactions are discussed in detail both analytically and graphically. It is shown that there are two kinds of singular interactions between line soliton and algebraic soliton： 1） the resonant interaction where the algebraic soliton propagates together with the line soliton and persists infinitely; 2） the extremely repulsive interaction where the algebraic soliton affects the motion of the line soliton infinitely apart.

Toxicity of Selected Imidazolium-based Ionic Liquids on Caenorhabditis elegans： a Quantitative Structure-Activity Relationship Study

Due to the large number of ionic liquids （ILs） and their potential environmental risk, assessing the toxicity of ILs by ecotoxicological experiment only is insufficient. Quantitative structure- activity relationship （QSAR） has been proven to be a quick and effective method to estimate the viscosity, melting points, and even toxicity of ILs. In this work, the LC50 values of 30 imidazolium-based ILs were determined with Caenorhabditis elegans as a model animal. Four suitable molecular descriptors were selected on the basis of genetic function approximation algorithm to construct a QSAR model with an R^2 value of 0.938. The predicted lgLC50 in this work are in agreement with the experimental values, indicating that the model has good stability and predictive ability. Our study provides a valuable model to predict the potential toxicity of ILs with different sub-structures to the environment and human health.

Periodic Waves of a Discrete Higher Order Nonlinear SchrSdinger Equation

The Hirota equation is a higher order extension of the nonlinear Schr6dinger equation by incorporating third order dispersion and one form of self steepening effect, New periodic waves for the discrete Hirota equation are given in terms of elliptic functions. The continuum limit converges to the analogous result for the continuous Hirota equation, while the long wave limit of these discrete periodic patterns reproduces the known resulr of the integrable Ablowitz-Ladik system.

New Exact Travelling Wave and Periodic Solutions of Discrete Nonlinear Schroedinger Equation

Some new exact travelling wave and period solutions of discrete nonlinearSchroedinger equation are found by using a hyperbolic tangent function approach, which was usuallypresented to find exact travelling wave solutions of certain nonlinear partial differential models.Now we can further extend the new algorithm to other nonlinear differential-different models.

LINEAR-DISPERSION DIVISION MULTIPLE-ACCESS FOR MIMO SYSTEMS

Comprehensive study on novel Linear-Dispersion Division Multiple-Access(LDDMA) for multi-user uplink Multiple-Input Multiple-Output(MIMO)systems is proposed.In the new multi-plexing scheme,each user’s information symbol is dispersed by a User-Specific Matrix(USM)both inspace and time domain and linearly combined at base-station side.And a simple random search al-gorithm,based on capacity maximization criteria,is developed to generate a bank of USMs.Simulationresults are presented to demonstrate the advantages of LDDMA.When the Bit Error Rate(BER)reaches 10–3,the performance gains are 3dB and 5dB,compared with Time-Division Linear DispersionCodes(TD-LDC)and BLAST,respectively.