Consensus Control With a Constant Gain for Discrete-time Binary-valued Multi-agent Systems Based on a Projected Empirical Measure Method

This paper studies the consensus control of multiagent systems with binary-valued observations.An algorithm alternating estimation and control is proposed.Each agent estimates the states of its neighbors based on a projected empirical measure method for a holding time.Based on the estimates,each agent designs the consensus control with a constant gain at some skipping time.The states of the system are updated by the designed control,and the estimation and control design will be repeated.For the estimation,the projected empirical measure method is proposed for the binary-valued observations.The algorithm can ensure the uniform boundedness of the estimates and the mean square error of the estimation is proved to be at the order of the reciprocal of the holding time(the same order as that in the case of accurate outputs).For the consensus control,a constant gain is designed instead of the stochastic approximation based gain in the existing literature for binary-valued observations.And,there is no need to make modification for control since the uniform boundedness of the estimates ensures the uniform boundedness of the agents’states.Finally,the systems updated by the designed control are proved to achieve consensus and the consensus speed is faster than that in the existing literature.Simulations are given to demonstrate the theoretical results.

Fully implicational methods for approximate reasoning based on interval-valued fuzzy sets

The aim of this paper is to discuss the approximate rea- soning problems with interval-valued fuzzy environments based on the fully implicational idea. First, this paper constructs a class of interval-valued fuzzy implications by means of a type of impli- cations and a parameter on the unit interval, then uses them to establish fully implicational reasoning methods for interval-valued fuzzy modus ponens （IFMP） and interval-valued fuzzy modus tel- lens （IFMT） problems. At the same time the reversibility properties of these methods are analyzed and the reversible conditions are given. It is shown that the existing unified forms of α-triple I （the abbreviation of triple implications） methods for FMP and FMT can be seen as the particular cases of our methods for IFMP and IFMT.

Compact implicit integration factor methods for some complex-valued nonlinear equations

The compact implicit integration factor （cIIF） method is an efficient time discretization scheme for stiff nonlinear diffusion equations in two and three spatial dimensions. In the current work, we apply the cIIF method to some complex-valued nonlinear evolutionary equations such as the nonlinear SchrSdinger （NLS） equation and the complex Ginzburg-Landau （GL） equation. Detailed algorithm formulation and practical implementation of cIIF method are performed. The numerical results indicate that this method is very accurate and efficient.

Approximation Maintenance When Adding a Conditional Value in Set-Valued Ordered Decision Systems

The integration of set-valued ordered rough set models and incremental learning signify a progressive advancement of conventional rough set theory, with the objective of tackling the heterogeneity and ongoing transformations in information systems. In set-valued ordered decision systems, when changes occur in the attribute value domain, such as adding conditional values, it may result in changes in the preference relation between objects, indirectly leading to changes in approximations. In this paper, we effectively addressed the issue of updating approximations that arose from adding conditional values in set-valued ordered decision systems. Firstly, we classified the research objects into two categories: objects with changes in conditional values and objects without changes, and then conducted theoretical studies on updating approximations for these two categories, presenting approximation update theories for adding conditional values. Subsequently, we presented incremental algorithms corresponding to approximation update theories. We demonstrated the feasibility of the proposed incremental update method with numerical examples and showed that our incremental algorithm outperformed the static algorithm. Ultimately, by comparing experimental results on different datasets, it is evident that the incremental algorithm efficiently reduced processing time. In conclusion, this study offered a promising strategy to address the challenges of set-valued ordered decision systems in dynamic environments.

THE QUALOCATION METHOD FOR LINEAR SECOND-ORDER TWO-POINT BOUNDARY-VALUE PROBLEMS

A qualocation method for linear second-order two-point boundary-value problems is developed. The results are extended those in [2]. On the other hand i this method can also be regarded as a discrete, version of the H1-Galerkin method. From this point, our results show that the effect of numerical integration does not decrease the order of convergence.

Projected subgradient method for non-Lipschitz set-valued mixed variational inequalities

A projected subgradient method for solving a class of set-valued mixed variational inequalities （SMVIs） is proposed when the mapping is not necessarily Lipschitz. Under some suitable conditions, it can be proven that the sequence generated by the method can strongly converge to the unique solution to the problem in the Hilbert spaces.

An integrated method for matching forest machinery and a weight-value adjustment

Proper matching of forestry machinery is important when raising mechanization levels for forestry production. In the matching process, forestry machinery needs not only expertise, but also improved methods for solving problems. I propose combination of case-based reasoning （CBR） and rule-based reasoning （RBR） by calculating the similarity of quantitative parameters of various forestry machines in an analytical and hierarchical process. I calculated the similarity of machin-ery used in forest industries to enable better selection and matching of equipment. I propose a weight-value adjusting method based on sums of squares of deviations in which the individual parameter weights were modified in the process of application. During the process of system design, I put forward a design method knowledge base and generated a dynamic web reasoning framework to integrate the processes of forest industry machinery selection and weight-value adjustment. This enables expansion of the scope of the complete system and enhancement of the reasoning efficiency. I demonstrate the validity and practicability of this method using a practical example.

Removing Random-Valued Impulse Noises by a Two-Staged Nonlinear Filtering Method

Digital images are frequently contaminated by impulse noise(IN)during acquisition and transmission.The removal of this noise from images is essential for their further processing.In this paper,a two-staged nonlinear filtering algorithm is proposed for removing random-valued impulse noise(RVIN)from digital images.Noisy pixels are identified and corrected in two cascaded stages.The statistics of two subsets of nearest neighbors are employed as the criterion for detecting noisy pixels in the first stage,while directional differences are adopted as the detector criterion in the second stage.The respective adaptive median values are taken as the replacement values for noisy pixels in each stage.The performance of the proposed method was compared with that of several existing methods.The experimental results show that the performance of the suggested algorithm is superior to those of the compared methods in terms of noise removal,edge preservation,and processing time.

Soft-Resolution Method of Six-Element Linguistic Truth-Valued Intuitionistic Fuzzy Propositional Logic

＂In this paper, we construct a six-element intuitionistic linguistic truth-valued fuzzy propositional logic （6LTV-IP） based on the framework of linguistic truth-valued propoitional logic, which can express bath the comparable and incomparable truth values. Truth degree and falsity degree of intuitionistic fuzzy proposition are two truth values with linguistic hedge. With the concrete logic operation of 6LTV-IP, some special properties are obtained. Then based on （α, β）-complementary literals and （a, β）-similar literals, we propose a soft-resolution method of 6LTV-IP.

A Spectral Method in Time for Initial-Value Problems

A time-spectral method for solution of initial value partial differential equations is outlined. Multivariate Chebyshev series are used to represent all temporal, spatial and physical parameter domains in this generalized weighted residual method (GWRM). The approximate solutions obtained are thus analytical, finite order multivariate polynomials. The method avoids time step limitations. To determine the spectral coefficients, a system of algebraic equations is solved iteratively. A root solver, with excellent global convergence properties, has been developed. Accuracy and efficiency are controlled by the number of included Chebyshev modes and by use of temporal and spatial subdomains. As examples of advanced application, stability problems within ideal and resistive magnetohydrodynamics (MHD) are solved. To introduce the method, solutions to a stiff ordinary differential equation are demonstrated and discussed. Subsequently, the GWRM is applied to the Burger and forced wave equations. Comparisons with the explicit Lax-Wendroff and implicit Crank-Nicolson finite difference methods show that the method is accurate and efficient. Thus the method shows potential for advanced initial value problems in fluid mechanics and MHD.

Fabrication of monolithic bulk Ti_3AlC_2 and impurity measurement by K-value method

Polycrystalline bulk Ti3AlC2 material with high purity and density was fabricated by hot pressing from the powder mixture with the starting stoichiometric mole ratios of 2.0TiC/ 1.0Ti/ 1.1A1/ 0.1Si at 1 300-1 500℃. X-ray diffraction patterns and scanning electron microscopy photographs of the fully dense samples indicate that the proper addition of silicon is favorable to the formation of Ti3AlC2, consequently results in high purity of the prepared samples. The Ti3AlC2 hot pressed at 1 300℃and 1 400℃is in plane-shape with sizes of 6-8μm and 15-20μm in the elongated dimension, respectively. The purities of samples are measured by the K-value method, and the contents of TiC are given by a linear equation.

基于E^3-Value的服务供应链运作管理流程和方法

目前尽管存在较多以产品为中心的供应链运作管理流程和方法,但在服务供应链领域,由于服务不同于产品的诸多特性局限了其进一步的应用。因此,采用结构化分析思想和方法,提出了基于E3-value的服务供应链运作管理逻辑流程和方法,该方法以价值为导向,不但可以解决现有供应链运作管理模式的一些适应性问题,而且能够解决"供应链运作管理模式为什么是这样,潜在盈利性如何量化"问题。

基于e^3-value的移动商务商业模式仿真分析

本文运用e3-value结构化仿真分析方法构建基于价值链的移动商务商业模式的价值模型。通过相关参数输入模型,对其进行模拟试算,得到该商业模式的盈利性和合理性评价。通过e3-value模型创新关键因素价值活动、价值界面及价值端口的解构,调整价值模型及其变量,得到移动商务价值网商业模式价值模型。通过模型试算结果对比,分析讨论移动商务价值网商业模式的合理性及模型创新发展策略。

基于e^3-value的电子商务模式的结构化分析——以数据库服务提供商为例

在对电子商务模式的描述方法研究进行综述的基础上,介绍了e3-value的主要概念及分析步骤,并以数据库服务提供商的电子商务模式为例,说明了利用e3-value进行结构化分析的基本过程,最后对该分析方法进行了评价。

Assessment of Direct Eco-value of Liangzi Lake

[Obective] This study amied to evaluate the direct usage value of Liangzi Lake, like plants and animal resources and water storage value. [Method] It was measured through the market value method. The physical environment was introduced and the productivity of the lake was investigated both through the literature materials and the investigations. The market value method was clarified in this paper as well as its operation process and the application fields. [Result] Based on the introduction of the current situation in Liangzi Lake, the direct usage value was estimated as 1.32 billion Yuan/year. Plant resources value was 318 million Yuan/year; animal resources value was 675 million Yuan/year; and water storage value was 325 million Yuan/year for the three parts. [Conclusion] This paper will attract more attention to the emphasis of the reasonable development of nature sources.

基于e3-value模型的iPhone APP Store价值网络分析

文章以i Phone APP Store为例,在运用VNA模型分析价值网络结构的基础上,建立i Phone APP Store的e3-value模型,根据参与者盈利能力表和财务敏感性分析获得战略制定的相关依据因素。

Microbiological Quality of Chicken Sold in Accra and Determination of D₁₀-Value of <i>E. coli</i>

Chicken is an excellent source of good quality protein, but it is highly susceptible to microbial contamination and often implicated in food borne disease. The microbiological quality of chicken at different retail outlets (supermarkets, local markets and farms) in Accra was investigated, and D10-values of E. coli in refrigerated and frozen retailed chicken was determined. The microbiological quality of chicken was studied by analyzing 27 chicken thigh samples collected from the retail outlets. D10-value of Escherichia coli was determined by using a linear regression model after gamma irradiation of inoculated chicken samples with doses of 0, 150, 300, 450, 600, 750 and 900 Gy. Mean total viable counts for the supermarkets, local markets and farms were 6.46, 6.91 and 6.57 log10 cfu/g respectively. Mean total coliform counts for the supermarkets, local markets and farms were 3.80, 3.46 and 3.14 log10 cfu/g respectively and the mean S. aureus counts were also 2.32, 2.28 and 2.70 log10 cfu/g respectively. There were no significant differences (p > 0.05) between the mean total viable count, total coliform counts and S. aureus count for the supermarkets, local markets and the farms. Mean counts of E. coli detected at the supermarket, local markets and farms were 1.27, 2.59 and 2.74 log10 cfu/g respectively. Salmonella spp. was detected in 2 out of the 27 samples. Fifty-two percent and 70% of samples respec-tively had total viable counts and total coliform counts within the microbial safety standards. Mean D10E. coli were 0.22 and 0.32 kGy in refrigerated and frozen chicken respectively. Presence of pathogenic bacteria in fresh chicken sold in some retail outlets in Accra was confirmed. Low D10-values of E. coli especially under refrigerated conditions suggest susceptibility to low dose irradiation and possibility of controlling spoilage and pathogenic microflora of fresh poultry.

Condensed Galerkin element of degree m for first-order initial-value problem with O(h^(2m+2))super-convergent nodal solutions

A new type of Galerkin finite element for first-order initial-value problems(IVPs)is proposed.Both the trial and test functions employ the same m-degreed polynomials.The adjoint equation is used to eliminate one degree of freedom(DOF)from the test function,and then the so-called condensed test function and its consequent condensed Galerkin element are constructed.It is mathematically proved and numerically verified that the condensed element produces the super-convergent nodal solutions of O(h^(2m+2)),which is equivalent to the order of accuracy by the conventional element of degree m+1.Some related properties are addressed,and typical numerical examples of both linear and nonlinear IVPs of both a single equation and a system of equations are presented to show the validity and effectiveness of the proposed element.

Multi-Valued Associative Memory Neural Network

A novel learning method for multi-valued associative memory network is introduced, which is based on Hebb rule, but utilizes more information. According to the current probe vector, the connection weights matrix could be chosen dynamically. Double-valued and multi-valued associative memory are all realized in our simulation experiment. The experimental results show that the method could enhance the associative success rate.

Problem and Improvement of R-values Applied to Assessment of Earthquake Forecast

The researches on the assessment of earthquake forecast are reviewed, then the R-value assessment is further developed theoretically in the paper. The results include the arithmetic of the R-values of earthquake occurrence under the condition that 'anomaly' occurred or no 'anomaly' occurred respectively, and the relation between the values. The distribution of Rvalue of a forecast method, corresponding to multi-status anomalies being independent each other, is also developed in the paper. The appropriate methods to estimate the R-values and extrapolate the occurrence probability of future earthquakes are also given in the paper.