An Availability Evaluation Method of Web Services Using Improved Grey Correlation Analysis with Entropy Difference and Weight

Web services is one of the basic network services, whose availability evaluation is of great significance to the promotion of users’ experience. This paper focuses on the problem of availability evaluation of Web services and proposes a method for availability evaluation of Web services using improved grey correlation analysis with entropy difference and weight (EWGCA).This method is based on grey correlation analysis, and use entropy difference to illustrate the changes of availability, set weight to quantize availability requirements of different operations or transactions in services. Through simulation experiment in high load scenarios for Web services, the experiment result shows that our method can realize hierarchical description and overall evaluation for availability of Web services accurately in the case of smaller test sample volumes or uncertain data even in the field of big data.

A Diagnosis Method of Vibration Fault of a Steam Turbine Based on Information Entropy and Grey Correlation Analysis

The vibration fault, one of the common faults in the steam turbine generator unit, brings great damage to the production and the running process. It is well known that the information entropy is to describe the degree of indeterminacy of the system, so the information entropy can be used to measure Despite its efficiency, one kind of information entropy is just enabled to identify make up for this limitation, based on nalysis was studied for vibration fault the vibration condition of the unit. certain part of the faults. In order to the faulty signals collected from the rotor test platform, the grey correlation adiagnosis of steam turbine shafting in this paper. The reference faulty matrix and the calculation model of grey correlation degree was established based on three kinds of information entropy. The analysis shows that grey correlation analysis is a useful method for fault diagnosis of shafting and can be used as a quantitative index for fault diagnosis.

Response surface method using grey relational analysis for decision making in weapon system selection

A proper weapon system is very important for a na- tional defense system. Generally, it means selecting the optimal weapon system among many alternatives, which is a multiple- attribute decision making （MADM） problem. This paper proposes a new mathematical model based on the response surface method （RSM） and the grey relational analysis （GRA）. RSM is used to obtain the experimental points and analyze the factors that have a significant impact on the selection results. GRA is used to an- alyze the trend relationship between alternatives and reference series. And then an RSM model is obtained, which can be used to calculate all alternatives and obtain ranking results. A real world application is introduced to illustrate the utilization of the model for the weapon selection problem. The results show that this model can be used to help decision-makers to make a quick comparison of alternatives and select a proper weapon system from multiple alternatives, which is an effective and adaptable method for solving the weapon system selection problem.

PHASE EXTENSION AND STRUCTURE ANALYSIS BY THE MAXIMUM ENTROPY METHOD

Excellent results are obtained in structure analysis with jew phases of structure factors by the maximum-entropy method (MEM) for CaGaN PbCO3 and ReBe22 single crystals. The computation time and memory space are minimized by symmetry operations so that structure analysis by the MEM can be carried out with a personal computer.

Analysis of Factors Influencing Comprehensive Productivity of Agriculture in Henan Province on the Basis of Grey Correlation

According to the data from Henan Statistical Yearbook from 2002 to 2008, from production capital, production conditions, labour inputs and financial support, this paper selects 11 variables influencing comprehensive productivity of agriculture in Henan Province. Through calculation and analysis of grey correlation of variables and comprehensive productivity of agriculture, this paper determines the impact of different variables on comprehensive productivity of agriculture. The results show that the agricultural capital has become the most important factor influencing comprehensive productivity of agriculture in Henan Province, while the impact of production conditions, labour inputs and financial support on comprehensive productivity of agriculture in Henan Province diminishes in turn. Corresponding countermeasures and suggestions are put forward to promote the sustainable development of comprehensive productivity of agriculture in Henan Province as follows: strengthen agricultural financial system building, and ensure agricultural production expenditure; scientifically arrange allocation of agricultural resources, and improve agricultural production conditions; carry out training of agricultural skills, and elevate the quality of agricultural labour forces; increase financial expenditure for agricultural production, and optimize financial expenditure structure.

Optimization of Tribological Performance of Al-6061T6-15% SiCp-15% Al₂O₃Hybrid Metal Matrix Composites Using Taguchi Method &Grey Relational Analysis

In this investigation, optimization of tribological performance parameters of Al-6061T6 alloy reinforced with SiC (15% by weight) and Al2O3 (15% by weight) particulates having particle size of 37 μm each has been presented. The wear and frictional properties of the hybrid metal matrix composites have been studied by performing dry sliding wear test using pin-on-disc wear tester. A L27 orthogonal array is selected for the analysis of the data. From the test results it is observed that sliding distance has the significant contribution in controlling the friction and wear behaviour of hybrid composites. A confirmation test is also carried out to verify the accuracy of the results obtained through the optimization. In addition an optical micrograph test is also performed on the wear tracks to study the wear mechanism.

Optimizing the Glass Fiber Cutting Process Using the Taguchi Methods and Grey Relational Analysis

This paper mainly describes a new approach to optimizing of the cutting glass fiber with multiple performance characteristics, based on reliability analysis, Taguchi and Grey methods. During the cutting process, the speed, the volume and the cutting load are optimized cutting parameters when the performance characteristics, which include Weibull modulus and blade wear, are taken into consideration. In this paper, optimization with multiple performance characteristics is found to be the highest cutting speed and the smallest cutting volume, and the medium cutting load. An analysis of the variance of the blade wear indicates that the cutting speed (47.21%), the cutting volume (14.62%) and the cutting load (12.20%) are the most significant parameters in the cutting process of glass fibers. In summary, the most optimal cutting parameter should be A3B1C2. The results of experiments have shown that the multiple performance characteristics of cutting glass fiber are improved effectively through this approach.

Multi-Objective Optimization of Fused Deposition Modeling for Mechanical Properties of Biopolymer Parts Using the Grey-Taguchi Method

The urgent need to develop customized functional products only possible by 3D printing had realized when faced with the unavailability of medical devices like surgical instruments during the coronavirus-19 disease and the ondemand necessity to perform surgery during space missions.Biopolymers have recently been the most appropriate option for fabricating surgical instruments via 3D printing in terms of cheaper and faster processing.Among all 3D printing techniques,fused deposition modelling(FDM)is a low-cost and more rapid printing technique.This article proposes the fabrication of surgical instruments,namely,forceps and hemostat using the fused deposition modeling(FDM)process.Excellent mechanical properties are the only indicator to judge the quality of the functional parts.The mechanical properties of FDM-processed parts depend on various process parameters.These parameters are layer height,infill pattern,top/bottom pattern,number of top/bottom layers,infill density,flow,number of shells,printing temperature,build plate temperature,printing speed,and fan speed.Tensile strength and modulus of elasticity are chosen as evaluation indexes to ascertain the mechanical properties of polylactic acid(PLA)parts printed by FDM.The experiments have performed through Taguchi’s L27orthogonal array(OA).Variance analysis(ANOVA)ascertains the significance of the process parameters and their percent contributions to the evaluation indexes.Finally,as a multiobjective optimization technique,grey relational analysis(GRA)obtains an optimal set of FDM process parameters to fabricate the best parts with comprehensive mechanical properties.Scanning electron microscopy(SEM)examines the types of defects and strong bonding between rasters.The proposed research ensures the successful fabrication of functional surgical tools with substantial ultimate tensile strength(42.6 MPa)and modulus of elasticity(3274 MPa).

Reliability Distribution of Numerical Control Lathe Based on Correlation Analysis

Combined Reliability distribution with correlation analysis,a new method has been proposed to make Reliability distribution where considering the elements about structure correlation and failure correlation of subsystems.Firstly,we make a sequence for subsystems by means of TOPSIS which comprehends the considerations of Reliability allocation,and introducing a Copula connecting function to set up a distribution model based on structure correlation,failure correlation and target correlation,and then acquiring reliability target area of all subsystems by Matlab.In this method,not only the traditional distribution considerations are concerned,but also correlation influences are involved,to achieve supplementing information and optimizing distribution.

Correlations between direct and indirect strength test methods

The difficulties associated with performing direct compression strength tests on rocks lead to the development of indirect test methods for the rock strength assessment. Indirect test methods are simple, more economical, less time-consuming, and easily adaptable to the field. The main aim of this study was to derive correlations between direct and indirect test methods for basalt and rhyolite rock types from Carlin trend deposits in Nevada. In the destructive methods, point load index, block punch index, and splitting tensile strength tests are performed. In the non-destructive methods, Schmidt hammer and ultrasonic pulse velocity tests are performed. Correlations between the direct and indirect compression strength tests are developed using linear and nonlinear regression analysis methods. The results show that the splitting tensile strength has the best correlation with the uniaxial compression strength.Furthermore, the Poisson's ratio has no correlation with any of the direct and indirect test results.

Analysis on decision-making model of plan evaluation based on grey relation projection and combination weight algorithm

In military service joint operations, when there are more operational forces, more multifarious materials are consumed, the support is more complex and fuzzy, the deployment of personnel is more rapid, and the support provided by wartime military material support powers can be more effective. When the principles,requirements, influencing factors and goals of military material support forces are deployed in wartime, an evaluation indicator system is established. Thus, a new combined empowerment method based on an analytic hierarchy process（AHP） is developed to calculate the subjective weights, and the rough entropy method is used to calculate the objective weights. Combination weights can be obtained by calculating the weight preference coefficient error, which is determined by combining the cooperative game method and the minimum deviation into objectives. This approach can determine the grey relation projection coefficient and synthesize the measure scheme superiority to finally optimize the deployment plan using the grey relation projection decision-making method. The results show that the method is feasible and effective;it can provide a more scientific and practical decision-making basis for the military material support power deployment in wartime.

Optimization of back bead geometry in the PMAG-TIG twin arc hybrid root welding process using grey based Taguchi method

This study investigated multi-response optimization of the pulse metal active gas-tungsten inert gas( PMAG-TIG) twin arc hybrid root welding process for an optimal parametric combination to yield favorable back bead geometry of welded joints using grey relational analysis and Taguchi method.Eighteen experimental runs based on an orthogonal array following the Taguchi method were performed to derive objective functions to be optimized within the experimental domain.The objective functions were selected in relation to parameters of PMAG-TIG twin arc root welding back bead geometry: back bead width to root reinforcement ratio and deposited metal height.The Taguchi approach was followed by grey relational analysis to solve the multi-response optimization problem.The significance of factors on overall quality characteristics of the weld joint was also evaluated quantitatively using analysis of variance.Optimal results were verified through additional experiments,and showed to feasibility of applying grey relation analysis in combination with Taguchi technique for continuous improvement of product quality in the manufacturing industry.

Multi-attributed decision making for mining methods based on grey system and interval numbers

In the case of unknown weights, theories of multi-attributed decision making based on interval numbers and grey related analysis were used to optimize mining methods. As the representative of independence for the indicator, the smaller the correlation of indicators is, the greater the weight is. Hence, the weights of interval numbers of indicators were determined by using correlation coefficient. Relative closeness based on positive and negative ideal methods was calculated by introducing distance between interval numbers, which made decision making more rational and comprehensive. A new method of ranking interval numbers based on normal distribution was proposed for the optimization of mining methods, whose basic properties were discussed. Finally, the feasibility and effectiveness of this method were verified by theories and practice.

Study on S-shaped region of pump turbine based on Omega vortex analysis method and entropy production theory

In order to comprehensively analyze the operation instability of the pump turbine S-shaped region,this paper uses DDES turbulence model to calculate the model pump turbine from the perspective of the evolution law of runner vortex and draft tube vortex rope and entropy production rate,combined with experiments.The results show that the numerical simulation is in good agreement with the experiment.Omega vortex analysis method is more accurate than other vortex recognition methods because it is not affected by the threshold value.The vortices at the runner region under the runaway condition and the turbine brake condition develop towards the vaneless space and the blade pressure surface respectively,which will cause the flow obstruction and blade separation.The overall vorticity of the reverse pump condition is the largest.The vortex rope of the draft tube under runaway and turbine brake conditions is columnar in shape and has very high rotational strength.The vortex rope under reverse pump conditions is prone to fracture and form scattered vortices,impeding the normal movement of the fluid.The entropy production rate of the spanwise surface near the upper ring and the lower crown is greater than the middle spanwise surface due to the boundary layer effect.And the energy dissipation in the runner under reverse pump conditions is characterized by high at both ends of the runner and low in the middle.The energy dissipation near the wall of the straight cone section of the draft tube is large due to the squeezing effect of the vortex rope on the flow.

A precise tidal prediction mechanism based on the combination of harmonic analysis and adaptive network-based fuzzy inference system model

An efficient and accurate prediction of a precise tidal level in estuaries and coastal areas is indispensable for the management and decision-making of human activity in the field wok of marine engineering. The variation of the tidal level is a time-varying process. The time-varying factors including interference from the external environment that cause the change of tides are fairly complicated. Furthermore, tidal variations are affected not only by periodic movement of celestial bodies but also by time-varying interference from the external environment. Consequently, for the efficient and precise tidal level prediction, a neuro-fuzzy hybrid technology based on the combination of harmonic analysis and adaptive network-based fuzzy inference system（ANFIS）model is utilized to construct a precise tidal level prediction system, which takes both advantages of the harmonic analysis method and the ANFIS network. The proposed prediction model is composed of two modules： the astronomical tide module caused by celestial bodies’ movement and the non-astronomical tide module caused by various meteorological and other environmental factors. To generate a fuzzy inference system（FIS） structure,three approaches which include grid partition（GP）, fuzzy c-means（FCM） and sub-clustering（SC） are used in the ANFIS network constructing process. Furthermore, to obtain the optimal ANFIS based prediction model, large numbers of simulation experiments are implemented for each FIS generating approach. In this tidal prediction study, the optimal ANFIS model is used to predict the non-astronomical tide module, while the conventional harmonic analysis model is used to predict the astronomical tide module. The final prediction result is performed by combining the estimation outputs of the harmonious analysis model and the optimal ANFIS model. To demonstrate the applicability and capability of the proposed novel prediction model, measured tidal level samples of Fort Pulaski tidal station are selected as the testing database. Simulation and experimental results confirm that the proposed prediction approach can achieve precise predictions for the tidal level with high accuracy, satisfactory convergence and stability.

Investigation of feature contribution to shield tunneling-induced settlement using Shapley additive explanations method

Accurate prediction of shield tunneling-induced settlement is a complex problem that requires consideration of many influential parameters.Recent studies reveal that machine learning(ML)algorithms can predict the settlement caused by tunneling.However,well-performing ML models are usually less interpretable.Irrelevant input features decrease the performance and interpretability of an ML model.Nonetheless,feature selection,a critical step in the ML pipeline,is usually ignored in most studies that focused on predicting tunneling-induced settlement.This study applies four techniques,i.e.Pearson correlation method,sequential forward selection(SFS),sequential backward selection(SBS)and Boruta algorithm,to investigate the effect of feature selection on the model’s performance when predicting the tunneling-induced maximum surface settlement(S_(max)).The data set used in this study was compiled from two metro tunnel projects excavated in Hangzhou,China using earth pressure balance(EPB)shields and consists of 14 input features and a single output(i.e.S_(max)).The ML model that is trained on features selected from the Boruta algorithm demonstrates the best performance in both the training and testing phases.The relevant features chosen from the Boruta algorithm further indicate that tunneling-induced settlement is affected by parameters related to tunnel geometry,geological conditions and shield operation.The recently proposed Shapley additive explanations(SHAP)method explores how the input features contribute to the output of a complex ML model.It is observed that the larger settlements are induced during shield tunneling in silty clay.Moreover,the SHAP analysis reveals that the low magnitudes of face pressure at the top of the shield increase the model’s output。

Reliability analysis of retaining walls with multiple failure modes

In order to reduce the errors of the reliability of the retaining wall structure in the establishment of function, in the estimation of parameter and algorithm, firstly, two new reliability and stability models of anti-slipping and anti-overturning based on the upper-bound theory of limit analysis were established, and two kinds of failure modes were regarded as a series of systems with multiple correlated failure modes. Then, statistical characteristics of parameters of the retaining wall structure were inferred by maximal entropy principle. At last, the structural reliabilities of single failure mode and multiple failure modes were calculated by Monte Carlo method in MATLAB and the results were compared and analyzed on the sensitivity. It indicates that this method, with a high precision, is not only easy to program and quick in calculation, but also without the limit of nonlinear functions and non-normal random variables. And the results calculated by this method which applies both the limit analysis theory, maximal entropy principle and Monte Carlo method into analyzing the reliability of the retaining wall structures is more scientific, accurate and reliable, in comparison with those calculated by traditional method.

Multi-dimensional and complicated electromagnetic interference hardware-in-the-loop simulation method

A typical electronic communication system, such as GPS receiver, unmanned aerial vehicle＇s （UAV＇s） data link, and radar, faces multi-dimensional and complicated electromagnetic interference in operating environment. To measure the anti- interference performance of the electronic communication system in the complicated electromagnetic interference environment, a method of multi-dimensional and complicated electromagnetic interference hardware-in-the-loop simulation in an anechoic room is proposed. It takes into account the characteristics of interference signals and the positional relationship among interference, the receiver and the transmitter of the electronic communication system. It uses the grey relational method and the angular domain mapping error correction method to control the relevant parameters, the microwave switch and so on, thus achieving the approximately actual mapping of the outdoor multi-dimensional and complicated electromagnetic interference in the anechoic room. To verify the effectiveness of this method, the multi-dimensional and complicated electromagnetic interference of the UAV＇s data link is simulated as an example. The results show that the degree of correlation between the calculated signal to interference ratio of the data link receiver in the actual scene and the measured signal to interference ratio of the data link receiver simulated with this method in the anechoic room is 0.968 1, proving that the method is effective for simulating the complicated electromagnetic interference.

Analysis of the Influence Factors of Grain Supply-Demand Gap in China

Based on the analysis of the grain supply and demand gap’s current situation in China, this paper establishes an indicator system for the influence factors of grain supply and demand gap. Then this paper calculates the correlation degree between the main grain varieties’ supply and demand gap and its influence factors. The results show that sown area and unit yield have the greatest impact on wheat supply and demand gap;per capita disposable income and unit yield have the greatest impact on corn supply and demand gap;per capita disposable income and agricultural mechanization level have the greatest impact on the supply and demand gap of soybean and rice. From the analysis results, we can obtain the difference between the factors affecting the grain supply and demand gap, and provide a certain theoretical basis and new ideas for the balance of grain supply and demand in China.

Evaluation of Farmland Drainage Water Quality by Fuzzy–Gray Combination Method

The complex relationships between indicators and water conditions cause fuzzy and gray uncertainties in evaluation of water quality. Compared to conventional single-factor evaluation methods, the combination evaluation method can consider these two uncertainties to produce more objective and reasonable evaluation results. In this paper, we propose a combination evaluation method with two main parts:(1) the use of fuzzy comprehensive evaluation and gray correlation analysis as submodels with which to consider the fuzzy and gray uncertainties and(2) the establishment of a combination model based on minimum bias squares. In addition, using this method, we evaluate the water quality of a ditch in a typical rice–wheat system of Yixing city in the Taihu Lake Basin during three rainfall events. The results show that the ditch water quality is not good and we found the chemical oxygen demand to be the key indicator that affects water quality most significantly. The proposed combination evaluation method is more accurate and practical than single-factor evaluation methods in that it considers the uncertainties of fuzziness and grayness.