Grey-theory based intrusion detection model

To solve the problem that current intrusion detection model needs large-scale data in formulating the model in real-time use, an intrusion detection system model based on grey theory （GTIDS） is presented. Grey theory has merits of fewer requirements on original data scale, less limitation of the distribution pattern and simpler algorithm in modeling. With these merits GTIDS constructs model according to partial time sequence for rapid detect on intrusive act in secure system. In this detection model rate of false drop and false retrieval are effectively reduced through twice modeling and repeated detect on target data. Furthermore, GTIDS framework and specific process of modeling algorithm are presented. The affectivity of GTIDS is proved through emulated experiments comparing snort and next-generation intrusion detection expert system （NIDES） in SRI international.

Establishment of Neural Network Prediction Model for Terminative Temperature Based on Grey Theory in Hot Metal Pretreatment

In order to improve the accuracy of model for terminative temperature in steelmaking, it is necessary to predict and control before decarburization. Thus, an optimization neural network model of terminative temperature in the process of dephosphorization by laying correlative degree weights to all input factors related was used. Then sim- ulation experiment of model newly established is conducted utilizing 210 data from a domestic steel plant. The results show that hit rate arrives at 56.45~~ when error is within plus or minus 5%, and the value is 100% when within ~10%. Comparing to the traditional neural network prediction model, the accuracy almost increases by 6. 839o//oo. Thus, the simulation prediction fits the real perfectly, which accounts for that neural network model for terminative tempera- ture based on grey theory can reflect accurately the practice in dephosphorization. Naturally, this method is effective and nraeticahle.

Optimization of structural parameters for elliptical cross-section spiral equal-channel extrusion dies based on grey theory

The elliptical cross-section spiral equal-channel extrusion （ECSEE） process is simulated by using Deform-3D finite element software. The ratio m of major-axis to minor-axis length for ellipse-cross-section, the torsion angle u, the round-ellipse cross-section transitional channel L1, the elliptical rotation cross-section transitional channel L2 and the ellipse-round cross-section transitional channel L3 are destined for the extrusion process parameters. The average effective strain eave on cross-section of blank, the deformation uniformity coefficient a and the value of maximum damage dmax are chosen to be the optimize indexes, and the virtual orthogonal experiment of L16 （45） is designed. The correlation degree of the process factors affecting eave, a and dmax is analyzed by the numerical simulation results using the weights and grey association model. The process parameters are optimized by introducing the grey situation decision theory and the ECSEE optimal combination of process parameters is obtained： u of 120 , m of 1.55, L1 of 7 mm, L2 of 10 mm, and L3 of 10 mm. Simulation and experimental results show that the material can be refined with the optimized structural parameters of die. Therefore, the optimization results are satisfactory.

Research and Prediction on the Properties of Concrete at Cryogenic Temperature Based on Gray Theory

To solve the cryogenic temperature problems faced by all-concrete liquefied natural gas(ACLNG)storage tanks during servicing,a low temperature resistant and high strength concrete(LHC)was designed from the perspectives of reducing water-binder ratio,removing coarse aggregates,optimizing composite mineral admixture and utilizing steel fibers.The variation laws of compressive and tensile strength,elastic modulus and Poisson’s ratio for C60 concrete and LHC were compared and analyzed under the temperatures from 10 to-165℃through uniaxial compression and tensile tests.The rapid freezing method was adopted to analyze the evolution process of mass and relative dynamic elastic modulus loss rates for C60 and LHC in 0-300 freeze-thaw cycles.The gas permeability test was carried out,and the laws of gas permeability coefficient varied with temperature and cryogenic freeze-thaw cycles were obtained.Then,the grey dynamic model GM(1,1)was used to predict the variation laws of physical and mechanical parameters on the basis of the test data.The test results demonstrate that the compressive strength,elastic modulus and Poisson’s ratio for both C60 and LHC increase significantly from 10 to-165℃,but the specific variation laws are difierent,and there is a phenomenon that some parameters decrease after reaching a critical temperature range for C60.The uniaxial tensile strength increases first and then decreases as temperature decreases,and finally increases slightly at-165℃for both C60 and LHC.The mass and relative dynamic elastic modulus loss rates of LHC are much lower than that of C60 under different freeze-thaw cycles.The gas permeability coefficient of C60 declines gradually with the drop of temperature,and increases gradually with the number of freeze-thaw cycles while the gas permeability coefficient of LHC basically remains stable and is much lower than that of C60.Therefore,such a conclusion can be drawn that LHC has better properties at cryogenic temperature.On the premise of providing consistent functional mode,GM(1,1)can predict the test data with high accuracy,which well reflects the variation laws of relevant parameters.

Grey Clustering Theory to Assess the Effect of Mineral Admixtures on the Cyclic Sulfate Resistance of Concrete

Concrete specimens made with ordinary portland cement or ordinary portland cement incorporating fly ash with the replacement of 10% or 20%, ground blast furnace slag with the replacement of 15% or 30%, or 15% fly ash and 15% ground blast furnace slag were made and exposed to a cyclic sulfate environment. Concrete properties including relative dynamic elastic modulus, chloride ion diffusion coefficient, compressive strength and flexural strength were measured. Effect of mineral admixtures on the cyclic sulfate resistance of concrete was assessed based on the grey clustering theory. The experimental results indicate that the cyclic sulfate resistance of concrete incorporating ground blast furnace slag belongs to the higher grey grade, which exhibits that it possesses excellent cyclic sulfate resistance. With increasing addition of fly ash, the cyclic sulfate resistance of concrete changes from the medium grey grade to the lower grey grade, which shows that incorporation of fly ash is disadvantageous for the cyclic sulfate resistance of concrete.

Predicting changes in Bitcoin price using grey system theory

Bitcoin is currently the leading global provider of cryptocurrency.Cryptocurrency allows users to safely and anonymously use the Internet to perform digital currency transfers and storage.In recent years,the Bitcoin network has attracted investors,businesses,and corporations while facilitating services and product deals.Moreover,Bitcoin has made itself the dominant source of decentralized cryptocurrency.While considerable research has been done concerning Bitcoin network analysis,limited research has been conducted on predicting the Bitcoin price.The purpose of this study is to predict the price of Bitcoin and changes therein using the grey system theory.The first order grey model(GM(1,1))is used for this purpose.It uses a firstorder differential equation to model the trend of time series.The results show that the GM(1,1)model predicts Bitcoin’s price accurately and that one can earn a maximum profit confidence level of approximately 98%by choosing the appropriate time frame and by managing investment assets.

Optimization approach hydroforming car beam billets based grey system theory

Perfect combination of structural size parameters of the hydroforming billets is essential to obtain even wall thicknesses of the car beam. Finite element （ FE ） analysis on hydroforming car beam was carried out, and the results were optimized according to multiple quality objectives by the grey system theory. With bending angle, bending radius and hight difference along the axis direction as variables, orthogonal FE analyses were conducted and the minimum and maximum wall thicknes ses of the billets with different sizes were obtained. Taking the minimum and maximum wall thick nesses as two references, the correlation coefficient between the data for reference and those for comparison by the grey system theory reduced multi objectives to a single quality objective, and the average correlation level of every billet facilitated the optimization of size parameters for hydroform ing car beam. The trial production showed that the optimization approach satisfied the need of hy droforming car beams.

Probability estimation based on grey system theory for simulation evaluation

In the evaluation of some simulation systems, only small samples data are gotten due to the limited conditions. In allusion to the evaluation problem of small sample data, an interval estimation approach with the improved grey confidence degree is proposed.On the basis of the definition of grey distance, three kinds of definition of the grey weight for every sample element in grey estimated value are put forward, and then the improved grey confidence degree is designed. In accordance with the new concept, the grey interval estimation for small sample data is deduced. Furthermore,the bootstrap method is applied for more accurate grey confidence interval. Through resampling of the bootstrap, numerous small samples with the corresponding confidence intervals can be obtained. Then the final confidence interval is calculated from the union of these grey confidence intervals. In the end, the simulation system evaluation using the proposed method is conducted. The simulation results show that the reasonable confidence interval is acquired, which demonstrates the feasibility and effectiveness of the proposed method.

AXIAL HEAT CONDUCTION MODEL TO PREDICT MAXIMUM HEAT REMOVE OF MINIATURE HEAT PIPE BASED ON GREY MODEL THEORY

Computer chip is always accompanied by the increase of heat dissipation and miniaturization. The miniature heat pipes are widely used in notebook computer to resolve the heat dissipation problems. Maximum heat removed model of miniature heat pipes building by grey model is presented. In order to know the foundation for modeling, the smooth grade of error examination is inquired and the accuracy of grey relational grade is verified. The model can be used to select a suitable heat pipes to solve electric heat problems in the future. Final results show that the grey model only needs four experiment data and its error value is less than 10%, further, it is better than computational fluid dynamics （CFD） model.

Using Grey Target Theory for Power Quality Evaluation Based on Power Quality Monitoring Data

Smart grid puts forward higher requirements for power quality.Power quality evaluation can provide a decision-making basis for quality improvement.Based on power quality monitoring data,a grey target method is proposed for power quality evaluation.The grey target is composed of power quality evaluation standard and power quality monitoring data to be evaluated.Combining with the characteristics of each power quality evaluation index,the target center of the whole grey target system is found.Then,the power quality monitoring data to be evaluated and the power quality standard mode are compared and analyzed to construct the power quality grey correlation difference information space.Finally,the target center coefficient and target degree of power quality are calculated to realize the comprehensive evaluation of power quality,and the evaluation grade of power quality monitoring data to be evaluated is obtained.Compared with the evaluation results of the existing literature,the effectiveness of the proposed method is verified,which shows that grey target theory is reasonable in the comprehensive evaluation of power quality.

Construction of a Comprehensive Soundscape Evaluation System in Forest Parks Based on Grey Statistical Theory

Based on collection and arrangement of evaluation indicators of soundscape in a forest park,24 primary evaluation indicators are chosen by grey statistical theory.The results show that there are 5 main factors influencing soundscape in a forest park,including water soundscape,wind soundscape,animal soundscape,recreation soundscape,and artificial soundscape,which contain 13 evaluation indicators.Among these factors,natural sound elements account for 84.6%.Thus a comprehensive evaluation indicator system of soundscape(including natural and unnatural soundscape) in a forest park is constructed by the selected evaluation indicators,and it is expected to provide a reference for scientific and systematic construction and development of forest parks in future.

Application of Grey System Theory in Design For Cost (DFC)

Design For Cost (DFC) is a branch of Design For X (DFX). In this paper, wedefined DFC as a design method that analyzed and evaluated the product's life cycle cost (LCC), thenmodified the design to reduce the LCC. Nowadays it is a very difficult thing to obtain LCC data inChina or in developing countries. Statistical methods can not be used because available LCC data arefew. In order to solve this problem, we used grey system theory. Then relations of cost factorswere analyzed in LCC using grey relevant methods, and a GM(1,1) model between design parameters andLCC was established. Using this model, we can estimate and control LCC by changing design parametersat the beginning of the design stage.

Map Building for a Mobile Robot Based on Grey System Theory

In this paper, a new method for mobile robot map building based on grey system theory is presented, by which interpretation and integration of sonar readings can be solved robustly and efficiently. The conception of 'grey number is introduced to model and handle the uncertainty of sonar reading. A new data fusion approach based on grey system theory is proposed to construct environment model. Map building experiments are performed both on a platform of simulation and a real mobile robot. Experimental results show that our method is robust and accurate.

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.

STUDY ON GREY FORECASTING MODEL OF COPPER EXTRACTION RATE WITH BIOLEACHING OF PRIMARY SULFIDE ORE

A model GM （grey model） （1,1） for forecasting the rate of copper extraction during the bioleaching of primary sulphide ore was established on the basis of the mathematical theory and the modeling process of grey system theory. It was used for forecasting the rate of copper extraction from the primary sulfide ore during a laboratory microbial column leaching experiment. The precision of the forecasted results were examined and modified via ＂posterior variance examination＂. The results show that the forecasted values coincide with the experimental values. GM （1,1） model has high forecast accuracy; and it is suitable for simulation control and prediction analysis of the original data series of the processes that have grey characteristics, such as mining, metallurgical and mineral processing, etc. The leaching rate of such copper sulphide ore is low. The grey forecasting result indicates that the rate of copper extraction is approximately 20% even after leaching for six months.

Evaluation model of the grey fuzzy on eco-environment vulnerability

The basic theory and evaluation index system of eco-environment vulnerability were reviewed. Based on the grey theory and fuzzy mathematics, a new comprehensive evaluation method from qualitative to quantitative, called grey-fuzzy evaluation, was proposed for evaluating eco-environment vulnerability. It was integrated of Association for Healthcare Philanthropy （AHP）, grey correlation analysis, grey statistics and fuzzy judgment. The constitutional principle and method of the new evaluation method were given and its feasibility and effectiveness were proved by the practical example.

Prediction of leaching rate in heap leaching process by grey dynamic model GDM(1,1)

The method of developing GM（1,1） model is extended on the basis of grey system theory. Conditions for the transfer function that improve smoothness of original data sequence and decrease the revert error are given. The grey dynamic model is first combined with the transfer function to predict the leaching rate in heap leaching process. The results show that high prediction accuracy can be expected by using the proposed method. This provides a new approach to realize prediction and control of the future behavior of leaching kinetics.

A Grey Decision Model Used in Bidding for Equipment Purchase

Bidding has long been used as a method for allocating and procuring goods and services. An acurrate and comprehensive evaluation of bidders is the key to make the bidding a successful one for tenderee. However, evaluation of bidders is a tough work and the result of evaluation is always affected by the evaluator's understanding of the standards set for evaluation, and the evaluator's expertise, experience and preferrence. We make an effort to find a method for selecting bidders as accurately as possible. A grey decision model is presented, and an example is illustrated to make the practioners know how to use the model.

A Hybrid Grey DEMATEL and PLS-SEM Model to Investigate COVID-19 Vaccination Intention

The main objective of this study is to comprehensively investigate individuals’vaccination intention against COVID-19 during the second wave of COVID-19 spread in Vietnam using a novel hybrid approach.First,the Decision-Making Trial and Evaluation Laboratory based on Grey Theory(DEMATEL-G)was employed to explore the critical factors of vaccination intention among individuals.Second,Partial Least Squares-Structural Equation Modeling(PLS-SEM)was applied to test the hypotheses of individual behavioral intention to get the vaccine to prevent the outbreak of COVID-19.A panel of 661 valid respondents was collected from June 2021 to July 2021,and confidentiality was maintained for all data obtained.The results identified that perception of COVID-19 vaccination and trust in vaccination strategy directly associated with individuals’COVID-19 immunization.Hence,the perceived severity of COVID-19 has an indirect impact on COVID-19 vaccination intentions via the perception of the COVID-19 vaccine.These findings indicated that the government’s information about vaccines is necessary for the new phase of vaccination intervention strategies in Vietnam.Therefore,the study suggests that the government needs to give complete information about the role of vaccines prioritizes transparency in official information about COVID-19 vaccines to allay concerns about side effects,allowing for the most appropriate policy formulation and implementation to encourage public vaccination.Future studies can apply PLS-SEM and other MCDM models with the fuzzy,hesitant numbers to re-evaluate the feasibility,validity and reliability of this research’s proposed model.

CALCULATION FOR KERNEL OF INTERVAL GREY NUMBER BASED ON BARYCENTER APPROACH

The kernel of interval grey number is most likely the real number,which can be used to represent whitenization value of interval grey number.A novel method for calculating kernel of interval grey number is constructed based on the geometric barycenter of whitenization weight function in the two-dimensional coordinate plane,and the calculation of kernel is converted to the calculation of barycenter in geometric figures.The method fully considers the effect of all information contained in whitenization weight function on the calculation result of kernel,and is the extension and perfection of the existing methods in the scope of application.