Data processing of small samples based on grey distance information approach

Data processing of small samples is an important and valuable research problem in the electronic equipment test. Because it is difficult and complex to determine the probability distribution of small samples, it is difficult to use the traditional probability theory to process the samples and assess the degree of uncertainty. Using the grey relational theory and the norm theory, the grey distance information approach, which is based on the grey distance information quantity of a sample and the average grey distance information quantity of the samples, is proposed in this article. The definitions of the grey distance information quantity of a sample and the average grey distance information quantity of the samples, with their characteristics and algorithms, are introduced. The correlative problems, including the algorithm of estimated value, the standard deviation, and the acceptance and rejection criteria of the samples and estimated results, are also proposed. Moreover, the information whitening ratio is introduced to select the weight algorithm and to compare the different samples. Several examples are given to demonstrate the application of the proposed approach. The examples show that the proposed approach, which has no demand for the probability distribution of small samples, is feasible and effective.     

Appraisal on the Regional Technological Innovation Ability Based on Unascertained Measure Method

In market economics, the regional technological innovation ability has become an important factor in the sustainable development of this region and important position in the region＇s competition. In this paper, the application of unascertained measure method in the ability of the regional technological innovation is studied. The appraisal index system is setup and the unascertained measure model is given . At last, an example is given to verify the theory model.     

A rough set approach to feature selection based on scatter search metaheuristic

Rough set theory is an effective method to feature selection, which has recently fascinated many researchers. The essence of rough set approach to feature selection is to find a subset of the original features. It is, however, an NP-hard problem finding a minimal subset of the features, and it is necessary to investigate effective and efficient heuristic algorithms. This paper presents a novel rough set approach to feature selection based on scatter search metaheuristic. The proposed method, called scatter search rough set attribute reduction （SSAR）, is illustrated by 13 well known datasets from UCI machine learning repository. The proposed heuristic strategy is compared with typical attribute reduction methods including genetic algorithm, ant colony, simulated annealing, and Tabu search. Computational results demonstrate that our algorithm can provide efficient solution to find a minimal subset of the features and show promising and competitive performance on the considered datasets.     

PREDICTIVE STUDY ON THE ECONOMIC VALUE OF RADIO SPECTRUM IN CHINA

Increasing popularity of spectrum-based services brings the striking contradictions between the limited spectrum resource and its increasing demands.This paper puts forward an approach to forecast the future spectrum demand and its economic value,so as to offer a scientific basis for spectrum regulators to resolve this contradiction effectively and make a long-term spectrum-use plan.Specifically,this paper analyzes the driving factors of spectrum demand firstly,based on which a forecasting model is constructed to predict the spectrum demand and its deficit/surplus in the next few years.Then,a forecasting model to measure the economic value of spectrum is proposed based on marginal opportunity cost theory,and the indifference curve is introduced to show the economic value generated by additional spectrum.Additionally,an empirical study is conducted to forecast the spectrum demand and its economic value for China in the next 10 years according to the proposed method.The results of this study show that spectrum deficit is a trend in future and releasing additional spectrum will bring China huge economic benefits.     

Study on a Evaluation Method of Vendorst

Based on the background of vendors＇ selection in supply chain management, the theory of entropy is adopted to filter the criteria. With the combination of data envelopment analysis（DEA） model, it can not only to eliminate the exclusive information of criteria, but it can keep the advantages of DEA model as well, which can conveniently conduct to automatic data collection and going on an objective evaluation of the priority of vendors.     

Generalized reliability measures of Kalman filtering for precise point positioning

To deal with the adverse influence of model failures on Kalman filtering (KF) estimation, it is necessary to investigate the generalized reliability theory, including the model failure detection and identification method as well as the separability and reliability theories. Although the generalized reliability theory for the least square has been discussed for many decades, the generalized reliability theory of KF is not widely discussed. Compared with the least square, KF includes not only the measurement model, but also the dynamic model. In KF, the predicted value of the state parameters from the dynamic model is considered as pseudomeasurements and combined with the observed measurements to compose the form of the least square. According to the reliability of the least square, the generalized reliability of KF is derived. Then, the dynamic model failure of precise point positioning is simulated to demonstrate the usage of the generalized reliability theory. The results show that the adverse influence of the dynamic model failure is more severe than that of the measurement model. Moreover, it is recommended that the model failure identification should always be used even if the overall model test passes. It is shown that the derived generalized reliability measures are suitable for the generalized KF estimation.     

Operational Patterns of Industrial Symbiosis Network in Industrial Cluster District Based on Circular Economy Theory

Industrial symbiosis network （ISN） is an efficient organizational form for improving resource recycling and efficiency in industrial cluster district. Because of the variety of industrial cluster district formation model, the industrial symbiosis network is different with each other. Based on the circular economy theory, combing with international tendency of cluster district, the paper puts forward the relying-on-oriented industrial symbiosis network. Meanwhile, it also analyzes its organizational mechanism, operating pattern and environmental performance. Through the above efforts, we hope it could be helpful for industry cluster district sustainable development in China.     

Modeling mechanism and extension of GM （1, 1）

Firstly,the research progress of grey model GM(1,1) is summarized,which is divided into three development stages: assimilation,alienation and melting stages.Then,the matrix analysis theory is used to study the modeling mechanism of GM(1,1),which decomposes the modeling data matrix into raw data transformation matrix,accumulated generating operation matrix and background value selection matrix.The changes of these three matrices are the essential reasons affecting the modeling and the accuracy of GM(1,1).Finally,the paper proposes a generalization grey model GGM(1,1),which is a extended form of GM(1,1) and also a unified form of model GM(1,1),model GM(1,1,α),stage grey model,hopping grey model,generalized accumulated model,strengthening operator model,weakening operator model and unequal interval model.And the theory and practical significance of the extended model is analyzed.     

Congestion control scheme in ATM networks based on fast tracing-queue

One of the more challenging and unresolved issues in ATM networks is the congestion control of available bit rate （ABR）. The dynamic controller is designed based on the control theory and the feedback mechanism of explicit rates With the given method of a chosen parameter, it can guarantee the stability of the controller and closed loop system with propagation delay and bandwidth oscillation. It needs less parameters（only one） to be designed. The queue length can converge to the given value in the least steps. The fairness of different connections is considered further. The simulations show better performance and good quality of service（QoS） is achieved.     

Weapon system portfolio selection based on structural robustness

The system portfolio selection is a fundamental frontier issue in the development planning and demonstration of weapon equipment. The scientific and reasonable development of the weapon system portfolio is of great significance for optimizing the design of equipment architecture, realizing effective resource allocation, and increasing the campaign effectiveness of integrated joint operations. From the perspective of system-ofsystems, this paper proposes a unified framework called structure-orien...     

Empirical Analysis on Chinese Urban Residents＇ Behavior＇s Differences in Different income -a SAM Multiplier Analysis

Based on SAM Multiplier theory, this paper discloses the structural characteristics of Chinese Urban Residents＇ Consumption. The main conclusions are as follows. Firstly, economic development in different sectors is unbalanced and especially consumption insufficiency is emerging; secondly, the effects of households by income group on the commodities are different; thirdly, consumption capability of Chinese urban residents is in the stage of durable consumable, but the highest income group is swifting to the higher stage and households with low income are entering the stage; finally, Chinese clothing, service and information industries have huge potential to develop while the latent demands are scarcity for that of the food, resident and education, cultural and entertainment industries.     

A GENERAL APPROACH BASED ON AUTOCORRELATION TO DETERMINE INPUT VARIABLES OF NEURAL NETWORKS FOR TIME SERIES FORECASTING

Input selection is probably one of the most critical decision issues in neural network designing, because it has a great impact on forecasting performance. Among the many applications of artificial neural networks to finance, time series forecasting is perhaps one of the most challenging issues. Considering the features of neural networks, we propose a general approach called Autocorrelation Criterion (AC) to determine the inputs variables for a neural network. The purpose is to seek optimal lag periods, which are more predictive and less correlated. AC is a data-driven approach in that there is no prior assumption about the models for time series under study. So it has extensive applications and avoids a lengthy experimentation and tinkering in input selection. We apply the approach to the determination of input variables for foreign exchange rate forecasting and conduct comparisons between AC and information-based in-sample model selection criterion. The experiment results show that AC outperforms inf     

System portfolio selection based on GRA method under hesitant fuzzy environment

The hesitant fuzzy set(HFS) is an important tool to deal with uncertain and vague information.In equipment system portfolio selection, the index attribute of the equipment system may not be expressed by precise data;it is usually described by qualitative information and expressed as multiple possible values.We propose a method of equipment system portfolio selection under hesitant fuzzy environment.The hesitant fuzzy element(HFE) is used to describe the index and attribute values of the equipment system.The hesitation degree of HFEs measures the uncertainty of the criterion data of the equipment system.The hesitant fuzzy grey relational analysis(GRA) method is used to evaluate the score of the equipment system, and the improved HFE distance measure is used to fully consider the influence of hesitation degree on the grey correlation degree.Based on the score and hesitation degree of the equipment system,two portfolio selection models of the equipment system and an equipment system portfolio selection case is given to illustrate the application process and effectiveness of the method.     

Reliability analysis of torpedo loading based on fractional-order optimization model

A fractional-order cumulative optimization GM(1,2)model based on grey theory is proposed to study the relationship between torpedo loading and working reliabilities. In this model, the average relative error function related to order and background value is established. Taking the average relative error function as the objective function, the optimal value of the two parameters is obtained through the optimization method,and the minimum value of the average relative error is determined. The calc...     

The Technology Selection and Critical Successful Factors in the Information Technology （IT） Growth of Manufacturing Corporations in China

With the rapid development of the information technology （IT） and the more competitive environment of the corporations, IT is not only important for the enterprises tactically but also strategically, We extend the concept of the critical success factors （CSF） and Nolan＇s stages theory to identify the IT issues and measure their CSF of the manufacturers in China. We put forward the IT selection matrix based on Nolan＇s stages theory to analyze the IT application in manufacturers in Beijing based on our survey. We analyze the development of IT, IT selection strategy and the CSF influencing the IT growth of manufacturers in China.     

Opportunistic spectrum sharing in software defined wireless network

Over the past few decades, the world has witnessed a rapid growth in mobile and wireless networks（MWNs） which significantly change human life. However, proliferating mobile demands lead to several intractable challenges that MWN has to face. Software-defined network is expected as a promising way for future network and has captured growing attention. Network virtualization is an essential feature in software-defined wireless network（SDWN）, and it brings two new entities, physical networks and virtual networks. Accordingly, efficiently assigning spectrum resource to virtual networks is one of the fundamental problems in SDWN. Directly orienting towards the spectrum resource allocation problem, firstly, the fluctuation features of virtual network requirements in SDWN are researched, and the opportunistic spectrum sharing method is introduced to SDWN. Then, the problem is proved as NP-hardness. After that, a dynamic programming and graph theory based spectrum sharing algorithm is proposed.Simulations demonstrate that the opportunistic spectrum sharing method conspicuously improves the system performance up to around 20%–30% in SDWN, and the proposed algorithm achieves more efficient performance.     

Improved genetic algorithm for nonlinear programming problems

An improved genetic algorithm(IGA) based on a novel selection strategy to handle nonlinear programming problems is proposed.Each individual in selection process is represented as a three-dimensional feature vector which is composed of objective function value,the degree of constraints violations and the number of constraints violations.It is easy to distinguish excellent individuals from general individuals by using an individuals’ feature vector.Additionally,a local search(LS) process is incorporated into selection operation so as to find feasible solutions located in the neighboring areas of some infeasible solutions.The combination of IGA and LS should offer the advantage of both the quality of solutions and diversity of solutions.Experimental results over a set of benchmark problems demonstrate that IGA has better performance than other algorithms.     

系族化经营与企业创新——来自集团附属上市公司的经验证据

Although familized-affiliated enterprises are common in the capital market, there is a lack of evidence on whether their innovation performance is better than that of only-child group-affiliated enterprises. This paper divided the listed companies affiliated to the Chinese group into familized group-affiliated enterprises and only-child group-affiliated enterprises, and examined the differences in innovation performance between the two types of organizations. It is found that the innovation performance of familized group-affiliated enterprises is significantly higher than that of only-child group-affiliated enterprises, and the innovation performance advantage of the familized group affiliation is more obvious in private than in state-owned enterprises. Moreover, the more the business of a familized group-affiliated firm is related to that of its parent company, the better the innovation performance of the affiliated firm will be. Conversely, the higher the diversification of a familized group, the lower the innovation performance of its affiliated firms will be. This paper shows that the familized group affiliation promotes the innovation of the affiliated enterprise. The findings enrich the understanding of the impact of the familized group on the innovation of affiliated firms, and have important practical implications for the innovation management of the group enterprise.     

MODEL SELECTION FOR LOG-LINEAR MODELS OF CONTINGENCY TABLES

In this paper, we propose an information-theoretic-criterion-based model selection procedure for log-linear model of contingency tables under multinomial sampling, and establish the strong consistency of the method under some mild conditions. An exponential bound of miss detection probability is also obtained. The .selection procedure is modified so that it can be used in practice. Simulation shows that the modified method is valid. To avoid selecting the penalty coefficient in the information criteria, an alteruative selection procedure is given.