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.

Feasibility of similarity coefficient map for improving morphological evaluation of T_2* weighted MRI for renal cancer

The purpose of this paper is to investigate the feasibility of using a similarity coefficient map（SCM） in improving the morphological evaluation of T2＊ weighted（T2＊W） magnatic resonance imaging（MRI） for renal cancer.Simulation studies and in vivo 12-echo T2＊W experiments for renal cancers were performed for this purpose.The results of the first simulation study suggest that an SCM can reveal small structures which are hard to distinguish from the background tissue in T2＊W images and the corresponding T2＊ map.The capability of improving the morphological evaluation is likely due to the improvement in the signal-to-noise ratio（SNR） and the carrier-to-noise ratio（CNR） by using the SCM technique.Compared with T2＊ W images,an SCM can improve the SNR by a factor ranging from 1.87 to 2.47.Compared with T2＊ maps,an SCM can improve the SNR by a factor ranging from 3.85 to 33.31.Compared with T2＊W images,an SCM can improve the CNR by a factor ranging from 2.09 to 2.43.Compared with T2＊ maps,an SCM can improve the CNR by a factor ranging from 1.94 to 8.14.For a given noise level,the improvements of the SNR and the CNR depend mainly on the original SNRs and CNRs in T2＊W images,respectively.In vivo experiments confirmed the results of the first simulation study.The results of the second simulation study suggest that more echoes are used to generate the SCM,and higher SNRs and CNRs can be achieved in SCMs.In conclusion,an SCM can provide improved morphological evaluation of T2＊W MR images for renal cancer by unveiling fine structures which are ambiguous or invisible in the corresponding T2＊W MR images and T2＊ maps.Furthermore,in practical applications,for a fixed total sampling time,one should increase the number of echoes as much as possible to achieve SCMs with better SNRs and CNRs.

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.

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.

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.

Program evaluation and its application to equipment based on super-efficiency DEA and gray relation projection method

For the gray attributes of the equipment program and its difficulty to carry out the quantitative assessment of the equipment program information, the gray relation projection method is simply reviewed. Combining the super-data envelopment analysis（DEA） model and the gray system theory, a new super-DEA for measuring the weight is proposed, and a gray relation projection model is established to rank the equipment programs. Finally, this approach is used to evaluate the equipment program. The results are verified valid and can provide a new way for evaluating the equipment program.

Convergence analysis and performance optimization of parallel concatenated systematic polar code

Similar to the analysis of Turbo codes, the parallel concatenated systematic polar code （PCSPC） can also be analyzed by the extrinsic information transfer （EXIT） chart. The convergence of the iterative decoding based on soft cancellation （SCAN） and belief propagation （BP） of PCSPC are analyzed by the EXIT chart. Analysis shows that SCAN decoder is more appropriate than BP decoder for this iterative decoding structure in terms of complexity. In addition, the weight coefficients of the iterative decoding structure are optimized by the simulated-EXIT （S- EXIT） chart, which improves the performance of PCSPC.

Optimizing channel cross section in irrigation area using improved cat swarm optimization algorithm

This research aimed to design the channel cross section with low water loss in irrigation areas.The traditional methods and models are based on explicit equations which neglect seepage and evaporation losses with low accuracy.To rectify this problem,in this research,an improved cat swarm optimization(ICSO)was obtained by adding exponential inertia weight coefficient and mutation to enhance the efficiency of conventional cat swarm optimization(CSO).Finally,the Fifth main channel of Jiangdong Irrigation area in Heilongjiang Province was taken as a study area to test the ability of ICSO.Comparing to the original design,the reduction of water loss was 20%with low flow errors.Furthermore,the ICSO was compared with genetic algorithm(GA),the particle swarm optimization(PSO)and cat swarm algorithm(CSO)to verify the effectiveness in the channel section optimization.The results are satisfactory and the method can be used for reliable design of artificial open channels.