Entropy weight coefficient model and its application in evaluation of groundwater vulnerability of the Sanjiang Plain

The research of groundwater vulnerability is the basic work to protect the groundwater. For utilizing groundwater resource continuably, groundwater vulnerability evaluation is necessary. Useful reference to protect, exploit and utilize on groundwater resource are provided rationally. According to the real condition of Sanjiang Plain, the indexes system is established based on the traditional DRASTIC model. The new system includes the following seven indexes： Depth of Water, Net Recharge, Aquifer Media, Soil Media, Conductivity of the Aquifer, Land Utilizing Ratio and Populace Density. The related analysis appears that the system is rather reasonable. Because traditional methods, such as analytic hierarchy process and fuzzy mathematics theory, can＇t be avoided human interference in selection of weights, they could lead to an imprecise result. In order to evaluate the groundwater vulnerability reasonably, entropy weight coefficient method is applied for the first time, which provides a new way to groundwater vulnerability evaluation. The method is a model whose weights are insured by the calculation process, so the artificial disturb can be avoided. It has been used to evaluate the groundwater vulnerability in Sanjiang Plain. The satisfied result is acquired. Comparably, the same result is acquired by the other method named projection pursuit evaluation based on real-coded accelerating genetic algorithm. It shows that entropy weight coefficient method is applicable on groundwater vulnerability evaluation. The evaluation result can provide reference on the decision-making departments.

Study on Entropy Weight Coefficient Method and Application for Water Quality Evaluation

In order to evaluate the quality of water environment, the conception of entropy is applied in information science, and the entropy weight model is built to evaluate comprehensively water quality. The indexes weights of water quality are determined by value of entropy. This kind of method is applied on evaluating water quality in the new water to be built. The result shows that the water quality in it which supply water is between grade Ⅲ and Ⅳ, and the result is similar to that of gray related method.

New computing method of weighted coefficients for tracking a maneuvering target using PDAF in the presence of clutter

To avoid or reduce the influence of unpredictable motion mode on data association, a new computing method of weighted coefficients of measurements for PDAF is presented in which it is assumed that the current turn rate of a maneuvering target changes within a limited range and its turn may be in arbitrary direction during data association. Thus, the predicted center for computing the weighted coefficients is a curved surface in 3-D space, which differs from the predicted center for setting up a validation gate, namely, a point in 3-D space. The distance between a measurement and the curved surface is used to compute its weighted coefficient. To reduce the computational complexity of weighted coefficients, the formulas for computing the maneuvering direction angle and turn rate corresponding to a measurement are presented. Simulation results show the proposed method reduces the percentage of lost tracks and improves the state estimation accuracy in tracking a maneuvering target using PDAF in the presence of clutter.

Parameter Estimation of a Valve-Controlled Cylinder System Model Based on Bench Test and Operating Data Fusion

The accurate estimation of parameters is the premise for establishing a high-fidelity simulation model of a valve-controlled cylinder system.Bench test data are easily obtained,but it is challenging to emulate actual loads in the research on parameter estimation of valve-controlled cylinder system.Despite the actual load information contained in the operating data of the control valve,its acquisition remains challenging.This paper proposes a method that fuses bench test and operating data for parameter estimation to address the aforementioned problems.The proposed method is based on Bayesian theory,and its core is a pool fusion of prior information from bench test and operating data.Firstly,a system model is established,and the parameters in the model are analysed.Secondly,the bench and operating data of the system are collected.Then,the model parameters and weight coefficients are estimated using the data fusion method.Finally,the estimated effects of the data fusion method,Bayesian method,and particle swarm optimisation(PSO)algorithm on system model parameters are compared.The research shows that the weight coefficient represents the contribution of different prior information to the parameter estimation result.The effect of parameter estimation based on the data fusion method is better than that of the Bayesian method and the PSO algorithm.Increasing load complexity leads to a decrease in model accuracy,highlighting the crucial role of the data fusion method in parameter estimation studies.

Continuous Weight Attack on Complex Network

We introduce a continuous weight attack strategy and numerically investigate the effect of continuous weight attack strategy on the Barabasi-Albert （BA） scale-free network and the Erdos-Rdnyi （ER） random network. We use a weight coefficient ω to define the attack intensity. The weight coefficient ω increases continuously from 1 to infinity, where 1 represents no attack and infinity represents complete destructive attack. Our results show that the continuous weight attack on two selected nodes with small ω （ω≈ 3） could achieve the same damage of complete elimination of a single selected node on both BA and ER networks. It is found that the continuous weight attack on a single selected edge with small ω （ω≈ 2） can reach the same effect of complete elimination of a single edge on BA network, but on ER network the damage of the continuous weight attack on a single edge is c/ose to but always smaller than that of complete elimination of edge even if ω is very large.

Reliability analysis method for slope stability based on sample weight

The single safety factor criteria for slope stability evaluation, derived from the rigid limit equilibrium method or finite element method （FEM）, may not include some important information, especially for steep slopes with complex geological conditions. This paper presents a new reliability method that uses sample weight analysis. Based on the distribution characteristics of random variables, the minimal sample size of every random variable is extracted according to a small sample t-distribution under a certain expected value, and the weight coefficient of each extracted sample is considered to be its contribution to the random variables. Then, the weight coefficients of the random sample combinations are determined using the Bayes formula, and different sample combinations are taken as the input for slope stability analysis. According to one-to-one mapping between the input sample combination and the output safety coefficient, the reliability index of slope stability can be obtained with the multiplication principle. Slope stability analysis of the left bank of the Baihetan Project is used as an example, and the analysis results show that the present method is reasonable and practicable for the reliability analysis of steep slopes with complex geological conditions.

Adaptive weighting impact angle optimal guidance law considering seeker's FOV angle constraints

In this paper, a new adaptive optimal guidance law with impact angle and seeker’s field-of-view(FOV) angle constraints is proposed. To this end, the generalized optimal guidance law is derived first. A changeable impact angle weighting(IAW) coefficient is introduced and used to modify the guidance law to make it adaptive for all guidance constraints. After integrating the closed-form solution of the guidance command with linearized engagement kinematics, the analytic predictive models of impact angle and FOV angle are built, and the available range of IAW corresponding to constraints is certain. Next, a calculation scheme is presented to acquire the real-time value of IAW during the entire guidance process. When applying the proposed guidance law, the IAW will keep small to avoid a trajectory climbing up to limit FOV angle at an initial time but will increase with the closing target to improve impact position and angle accuracy, thereby ensuring that the guidance law can juggle orders of guidance accuracy and constraints control.

Improvement of Similarity Measure： Pearson Product-Moment Correlation Coefficient

Aim To study the reason of the insensitiveness of Pearson product-momentcorrelation coefficient as a similarity measure and the method to improve its sensitivity. MethodsExperimental and simulated data sets were used. Results The distribution range of the data setsinfluences the sensitivity of Pearson product-moment correlation coefficient. Weighted Pearsonproduct-moment correlation coefficient is more sensitive when the range of the data set is large.Conclusion Weighted Pearson product-moment correlation coefficient is necessary when the range ofthe data set is large.

A Mixed Mechanism of Weighted-Driven and Inner Selection in Networks

For most networks, the weight of connection is changing with their attachment and inner affinity. By introducing a mixed mechanism of weighted-driven and inner selection, the model exhibits wide range power-law distributions of node strength and edge weight, and the exponent can be adjusted by not only the parameter δ but also the probability q. Furthermore, we investigate the weighted average shortest distance, clustering coefficient, and the correlation of our network. In addition, the weighted assortativity coefficient which characterizes important information of weighted topological networks has been discussed, but the variation of coefficients is much smaller than the former researches.

APPLICATION OF WEIGHTED NONOSCILLATORY AND NON-FREE-PARAMETER DISSIPATION DIFFERENCE SCHEME IN CALCULATING THE FLOW OF VIBRATING FLAT CASCADE

A dual-time method is introduced to calculate the unsteady flow in a certain vibrating flat cascade. An implicit lower-upper symmetric-gauss-seidel scheme（LU-SGS） is applied for time stepping in pseudo time domains, and the convection items are discretized with the spatial three-order weighted non-oscillatory and non-free-parameter dissipation difference （WNND） scheme. The turbulence model adopts q-co low-Reynolds-number model. The frequency specmuns of lift coefficients and the unsteady pressure-difference coefficients at different spanwise heights as well as the entropy contours at blade tips on different vibrating instants, are obtained. By the analysis of frequency specmuns of lift coefficients at three spanwise heights, it is considered that there exist obvious non-linear perturbations in the flow induced by the vibrating, and the perturbation frequencies are higher than the basic frequency. The entropy contours at blade tips at different times display an intensively unsteady attribute of the flow under large amplitudes.

Coagulation and analgesic effects of aqueous extract of peanut shells on mice

Background:Peanut shells are a commonly discarded byproduct of peanut processing.However,recent studies have shown that they contain bioactive compounds that have potential health benefits.Specifically,water extract from peanut shells has been identified as a promising source of these compounds.Therefore,investigating the effects of water extract from peanut shells on coagulation and analgesia in mice could have significant implications for human health.Methods:(1)Analgesic experiments:The analgesic effect of the aqueous extract of peanut shells was observed by the hot plate method in mice.The aspirin group was used as a positive control group for analgesic experiments.(2)Coagulation experiment:the coagulation effect of the aqueous extract of peanut shells was observed by the capillary method and slide method.Yunnan Baiyao group was the positive control group of the coagulation test.Results:(1)The analgesic effect of peanut shell water extract on mice was prolonged with the increase in dose.The low,medium,and high dose groups of peanut shell could improve the pain domain of mice induced by the hot plate method in a certain period(P<0.05);with the increase of peanut shell water extract dose,liver weight coefficient increased(P<0.05).(2)Peanut shell water extract coagulated mice,and the high-dose group of peanut shells was the most significant.Within the scope of this study,the higher the concentration,the better the coagulation effect(P<0.05).Compared with distilled water group,the liver weight coefficients of the Yunnan Baiyao group,low,middle,and high dose groups of peanut shells were significantly increased(P<0.05).Conclusion:(1)The aqueous extract of peanut shells has a specific analgesic effect on mice.(2)The aqueous extract of peanut shells promotes coagulation,and the pro-coagulant effect is more significant with increasing dose and the liver weight coefficient increases.

Emergency Energy Management of Microgrid in Industrial Park Basedon Robust Optimization

Reducing the impact of power outages and maintaining the power supply duration must be considered in implementing emergency energy dispatching in micro-networks.This paper studies a new emergency energy treatment method based on the robust optimal method and the industrial park micro-network with the optical energy storage system.After controlling the load input,a control strategy of adjusting and removing is proposed.Rolling optimal theory is applied to emergency energy scheduling based on a robust optimal mathematical model.A weighting factor is introduced into the optimal model to balance the importance of reducing and retaining the power supply.Uncertainty is designed to adjust the effect of uncertainty on the problem.The example shows that this method can flexibly set the weight coefficient and uncertainty value according to the actual situation so that the input of the control load can be optimized.

APPLICATION OF GEOGRAPHICAL PARAMETER DATABASE TO ESTABLISHMENT OF UNIT POPULATION DATABASE

Now GIS is turning into a good tool in handling geographical, economical, and population data, so we can obtain more and more information from these data. On the other hand, in some cases, for a calamity, such as hurricane, earthquake, flood, drought etc., or a decision-making, such as setting up a broadcasting transmitter, building a chemical plant etc., we have to evaluate the total population in the region influenced by a calamity or a project. In this paper, a method is put forward to evaluate the population in such special region. Through exploring the correlation of geographical parameters and the distribution of people in the same region by means of quantitative analysis and qualitative analysis, unit population database (1km× 1km) is established. In this way, estimating the number of people in a special region is capable by adding up the population in every grid involved in this region boundary. The geographical parameters are obtained from topographic database and DEM database on the scale of 1: 250 000. The fundamental geographical parameter database covering county administrative boundaries and 1km × 1km grid is set up and the population database at county level is set up as well. Both geographical parameter database and unit population database are able to oiler sufficient conditions for quantitative analysis. They will have important role in the research fields of data mining (DM), Decision-making Support Systems (DSS), and regional sustainable development.

On an Extension and a Refinement of Van der Corput's Inequality

By introducing a parameter α, we give an extension of Van der Corput＇s inequality. Also a new strengthened version of it is considered.

Improved particle swarm optimization algorithm for multi-reservoir system operation

In this paper, a hybrid improved particle swarm optimization （IPSO） algorithm is proposed for the optimization of hydroelectric power scheduling in multi-reservoir systems. The conventional particle swarm optimization （PSO） algorithm is improved in two ways： （1） The linearly decreasing inertia weight coefficient （LDIWC） is replaced by a self-adaptive exponential inertia weight coefficient （SEIWC）, which could make the PSO algorithm more balanceable and more effective in both global and local searches. （2） The crossover and mutation idea inspired by the genetic algorithm （GA） is imported into the particle updating method to enhance the diversity of populations. The potential ability of IPSO in nonlinear numerical function optimization was first tested with three classical benchmark functions. Then, a long-term multi-reservoir system operation model based on IPSO was designed and a case study was carried out in the Minjiang Basin in China, where there is a power system consisting of 26 hydroelectric power plants. The scheduling results of the IPSO algorithm were found to outperform PSO and to be comparable with the results of the dynamic programming successive approximation （DPSA） algorithm.

On a Refinement of Hardy-Hilbert's Inequality and Its Applications

In this paper, by introducting a weight coefficient of the form: π/sin(π/r)-1/10(2n+1)1+1/r (r＞1, n∈N0), Hardy-Hilbert's inequality is refined. As its applications, an equivalent Hard y-Hilbert's type inequality and its strengthened form are given, and Hardy-Li ttlewood's inequality is generalized and improved.

Automated Dimensioning Method of Engineering Drawings for Mechanical Products Based on Curve Chain

An automated method based on the curve chain was proposed for dimensioning of engineering drawings for the mechanical products.According to the internal relation between the features of 3D model feature and elements of 2D drawing,the curve chain was established to reflect the geometric topological structure between the elements.It divides the dimensions into the absolute dimensions within the cure chain and the relative dimensions between the curve chains.The parallel and lengthy relationship between the drawing elements of the constructed X and Y parallel matrix was solved to remove redundant elements in the curve chain and labeled the absolute dimensions of the remaining valid elements.The average minimum weight coefficient was introduced to judge the dependence on the relative dimensions between curve chains.Through the analysis of the overlap between the circular rectangular areas,including all the absolute dimensions of the curve chains,overlapping curve chains were merged,and their dimensions were rearranged to avoid the cross interference between them.The method was seamlessly integrated into the drafting module of product design software NX,and it developed an automated dimensioning system.The examples show that the system has excellent interactivity and robustness in the dimensioning of product engineering drawings.The dimension information is complete,accurate and reliable.

On an Extension of Hibert's Inequality and Applications

This paper gives a new generalization of Hilbert＇s inequality with a best constant factor involving the β function. An applications, we consider the equivalent form and some particular results.

Model predictive flux control of permanent magnet synchronous motor driven by three-level inverter based on fine-division strategy

Aiming at the difficulty of setting the weight coefficient in the value function of model predictive torque control(MPTC)for permanent magnet synchronous motor(PMSM)driven by three-level inverter,a fine-division model predictive flux control(MPFC)method is proposed.First,establish a mathematical model between the motor torque and the stator flux linkage according to the mathematical equations of PMSM.Thus,the control of the motor torque and stator flux linkage in the MPTC is transformed into the control of a single stator flux linkage vector,omitting the cumbersome weight setting process in the traditional MPTC.The midpoint potential control strategy is proposed,which uses the characteristics of redundant small vectors to balance the midpoint potential.After that,a fine-division strategy is proposed,which effectively reduces the number of candidate vectors and the computational burden of the system.Finally,the proposed MPFC is compared with MPTC by simulation.The results show that the proposed fine-division MPFC effectively reduces the system calculation,and has the advantages of simple principle and better dynamic and steady-state control performance.The feasibility of the control strategy is verified.

Design of nuclear radiation level gauge based on normalized LMS filtering correction

In the measurement of liquid level in industrial site environment,noise interference can affect the measurement accuracy.In order to improve the measurement accuracy of liquid level in the viscous state,a nuclear radiation level measurement system based on the least mean square(LMS)filtering correction method is designed.The system uses STM32F103 as the control core and adopts HART bus HT1200M chip for remote signal transmission and reception.The adaptive LMS algorithm can be used for more accurate filtering,calculating iterative weight vector,updating weighted coefficient,effectively removing system measurement noise and improving the measurement accuracy.The results show that the nuclear radiation level gauge based on normalized LMS can correct the measurement system accuracy in adaptive rules,improve the measurement accuracy to meet the requirements of industrial field environment for liquid level measurement and enhance the industrial automation control degree.