A Disturbance Localization Method for Power System Based on Group Sparse Representation and Entropy Weight Method

This paper addresses the problem of complex and challenging disturbance localization in the current power system operation environment by proposing a disturbance localization method for power systems based on group sparse representation and entropy weight method.Three different electrical quantities are selected as observations in the compressed sensing algorithm.The entropy weighting method is employed to calculate the weights of different observations based on their relative disturbance levels.Subsequently,by leveraging the topological information of the power system and pre-designing an overcomplete dictionary of disturbances based on the corresponding system parameter variations caused by disturbances,an improved Joint Generalized Orthogonal Matching Pursuit(J-GOMP)algorithm is utilized for reconstruction.The reconstructed sparse vectors are divided into three parts.If at least two parts have consistent node identifiers,the node is identified as the disturbance node.If the node identifiers in all three parts are inconsistent,further analysis is conducted considering the weights to determine the disturbance node.Simulation results based on the IEEE 39-bus system model demonstrate that the proposed method,utilizing electrical quantity information from only 8 measurement points,effectively locates disturbance positions and is applicable to various disturbance types with strong noise resistance.

Construction of Conservative Numerical Fluxes for the Entropy Split Method

The entropy split method is based on the physical entropies of the thermally perfect gas Euler equations.The Euler flux derivatives are approximated as a sum of a conservative portion and a non-conservative portion in conjunction with summation-by-parts(SBP)difference boundary closure of(Gerritsen and Olsson in J Comput Phys 129:245-262,1996;Olsson and Oliger in RIACS Tech Rep 94.01,1994;Yee et al.in J Comp Phys 162:33-81,2000).Sj?green and Yee(J Sci Comput)recently proved that the entropy split method is entropy conservative and stable.Stand-ard high-order spatial central differencing as well as high order central spatial dispersion relation preserving(DRP)spatial differencing is part of the entropy stable split methodol-ogy framework.The current work is our first attempt to derive a high order conservative numerical flux for the non-conservative portion of the entropy splitting of the Euler flux derivatives.Due to the construction,this conservative numerical flux requires higher oper-ations count and is less stable than the original semi-conservative split method.However,the Tadmor entropy conservative(EC)method(Tadmor in Acta Numerica 12:451-512,2003)of the same order requires more operations count than the new construction.Since the entropy split method is a semi-conservative skew-symmetric splitting of the Euler flux derivative,a modified nonlinear filter approach of(Yee et al.in J Comput Phys 150:199-238,1999,J Comp Phys 162:3381,2000;Yee and Sj?green in J Comput Phys 225:910934,2007,High Order Filter Methods for Wide Range of Compressible flow Speeds.Proceedings of the ICOSAHOM09,June 22-26,Trondheim,Norway,2009)is proposed in conjunction with the entropy split method as the base method for problems containing shock waves.Long-time integration of 2D and 3D test cases is included to show the com-parison of these new approaches.

An Information Entropy-Based Methodology to Construct the Avulsion Threshold in the Tail Reach of the Estuarine Alluvial Plain

Channel avulsion is a natural phenomenon that occurs abruptly on alluvial river deltas,which can affect the channel stability.The causes for avulsion could be generally categorized as topography-and flood-driven factors.However,previous studies on avulsion thresholds usually focused on topography-driven factors due to the centurial or millennial avulsion timescales of the world’s most deltas,but neglected the impacts of flood-driven factors.In the current study,a novel demarcation equation including the two driven factors was proposed,with the decadal timescale of avulsion being considered in the Yellow River Estuary(YRE).In order to quantify the contributions of different factors in each category,an entropy-based methodology was used to calculate the contributing weights of these factors.The factor with the highest weight in each category was then used to construct the demarcation equation,based on avulsion datasets associated with the YRE.An avulsion threshold was deduced according to the demarcation equation.This avulsion threshold was then applied to conduct the risk assessment of avulsion in the YRE.The results show that:two dominant factors cover respectively geomorphic coefficient representing the topography-driven factor and fluvial erosion intensity representing the flood-driven factor,which were thus employed to define a two dimensional mathematical space in which the demarcation equation can be obtained;the avulsion threshold derived from the equation was also applied in the risk assessment of avulsion;and the avulsion threshold proposed in this study is more accurate,as compared with the existing thresholds.

Research Progress of High Entropy Ceramic Materials

High-entropy materials(HEMs)have better mechanical,thermal,and electrical properties than traditional materials due to their special"high entropy effect".They can also adjust the performance of high entropy ceramics by adjusting the proportion of raw materials,and have broad application prospects in many fields.This article provides a review of the high entropy effect,preparation methods,and main applications of high entropy ceramic materials,especially exploring relevant research on high entropy perovskite ceramics.It is expected to provide reference for the promotion of scientific research and the development of further large-scale applications of high-entropy ceramic materials.

基于FAHP-Entropy赋权法的矿山地质环境影响评价:以武鸣区灰岩矿山为例

矿山地质环境影响评价是一个兼具复杂性和模糊性的系统,是将有限的修复资源如何合理地分配到不同影响程度矿山的科学依据。为了更精准、更高效地评价矿山对周边地质环境的影响状况及程度,本文选择南宁市武鸣区38个灰岩矿山为研究对象,从地质环境背景、资源破坏、地质灾害、矿山开发利用状况4个方面选取了14个评价指标构建矿山地质环境影响评价体系,采用模糊层次分析法和熵值法相结合(FAHP-Entropy组合)赋权法综合评价矿山地质环境影响程度,并基于MATLAB平台开发了矿山地质环境影响评价系统(MGES),对38座灰岩矿山进行评价。评价结果显示,对地质环境影响较轻的矿山仅占比21%,对地质环境影响较严重的矿山占比47%,对地质环境影响严重的矿山占比32%,武鸣区矿山地质环境影响程度整体属较严重~严重级别。研究结果为武鸣区政府有限的治理资金指明了优先治理方向。该系统操作简单,可以弥补传统方法复杂、难操作的不足之处,对于处理大规模数据有极大优势,可为同业技术人员和学者开展矿山地质环境影响评价工作提供借鉴。

Application of Fuzzy Comprehensive Evaluation Method Based on Entropy Weight Theory in Evaluation of Salt Tolerance of Cotton

[Objective] The aim was to propose a new entropy weight fuzzy compre- hensive evaluation method for assessing cotton salt tolerance, realizing the objective, accurate and comprehensive evaluation of salt tolerance of cotton. [Method] A sand culture experiment under salt stress of 150 mmol/L of NaCI was designed. The in- dicator weight was determined with the entropy weight fuzzy comprehensive evalu- ation method, based on the salt injury index of indicators. The salt tolerance of cotton was evaluated comprehensively. [Result] At the germination stage, the entropy and weight of salt injury index of germination energy, vigor index, hypocotyl length and fresh weight were highest, followed by germination rate and germination index, and of root length were lowest. At the seedling stage, the entropy and weight of salt injury index of plasma membrane permeability, root vigor and leaf expansion rate were highest, followed by plant height and net photosynthetic rate, and of shoot dry weight and root dry weight were lowest. The salt tolerance of cotton differed a- mong growth stages and cultivars. Among the 11 cultivars, CCRI-44 and CCRI-75 were steadily salt-tolerant at both germination and seedling stages; CCRI-17, Sumi- an 22, Sumian 15 and Dexiamianl had a stable moderate salt tolerance; while Sumian 12 and Simian 3 were steadily salt-sensitive. [Conclusion] The evaluated result was objective and exact, which indicated that this method could be used in comprehensive evaluation of salt tolerance of cotton.

Two-Dimensional Entropy Method Based on Genetic Algorithm

Two dimensional(2 D) entropy method has to pay the price of time when applied to image segmentation. So the genetic algorithm is introduced to improve the computational efficiency of the 2 D entropy method. The proposed method uses both the gray value of a pixel and the local average gray value of an image. At the same time, the simple genetic algorithm is improved by using better reproduction and crossover operators. Thus the proposed method makes up the 2 D entropy method’s drawback of being time consuming, and yields satisfactory segmentation results. Experimental results show that the proposed method can save computational time when it provides good quality segmentation.

AUTOMATIC MULTILEVEL THRESHOLDING METHOD BASED ON MAXIMUM ENTROPY

In the multilevel thresholding segmentation of the image, the classification number is always given by the supervisor. To solve this problem, a fast multilevel thresholding algorithm considering both the threshold value and the classification number is proposed based on the maximum entropy, and the self-adaptive criterion of the classification number is given. The algorithm can obtain thresholds and automatically decide the classification number. Experimental results show that the algorithm is effective.

Application of Fuzzy Comprehensive Evaluation Method Based on Entropy Weight to Evaluate Pond Water Quality

[Objective] This study was to provide references for the evaluation of water quality in aquaculture ponds by evaluating the pond water quality using fuzzy comprehensive evaluation method based on entropy weight. [Method] The fuzzy compre- hensive evaluation method based on entropy weight was used to evaluate the water quality in the ponds with Ukraine scale carp （Cyprinus carpio） as the main cultivated fish. The average size of the fish was 71.4 g/ind, and totally three groups of pond were set with the population density of 6 000, 9 000, 12 000 ind/hm2. [Result] According to the GB3838-2002 Environmental Quality Standards for Surface Water of China, the water quality of 6 000 ind/hm2 group was Grade I, and the water quality of 9 000 and 12 000 ind/hm2 were Grade V. [Conclusion] With the increasing of feeding density, the pond water quality would worsen, however, there is no difference on water quality between 9 000 and 12 000 ind/hm2 groups.

Risk Assessment of Diary Cattle Brucellosis Based on Systematic Multilevel Grey Relation Entropy Method

[Objective] The study was to explore the major factors affecting diary cattle brucellosis risk assessment,as well as their strong-to-weak sequence,so as to provide theoretical basis for assessing diary cattle brucellosis risk level in different regions.[Method] From 4 dimensions of feeding and importing,breeding,housing and polyculture situation,an evaluation index system was set up,and diary cattle brucellosis risk survey was conducted in 3 typical regions.Finally,systematic multilevel grey relation entropy method was applied to perform data analysis.[Result] The strong-to-weak sequence of Level 1 impact factor of diary cattle brucellosis was as follows：feeding and importinghousingpolyculture situationbreeding;the sequence of Level 2 impact factor was U32〉U12〉U11〉U31〉U21〉U42〉U43〉U23〉U22〉U41;the risk level sequence of 3 typical regions was Province A（County A1,A2,A3）Province B（County B1,B2,B3）Province C（County C1,C2,C3）.[Conclusion] According to the weight of Level 1 index strata,administrative departments at all levels and dairy cattle farmers should lay emphasis on the aspects of feeding,importing and housing;viewed from the perspective of Level 2 index strata,dairy cattle farmers should value the siting of cattle field,the brucellosis surveillance before importing and milking modes most.According to the diary cattle brucellosis risk level of 3 typical regions,if administrative departments at all levels strengthen peoples＇ awareness of their personal health and increase investment in this area,with new healthy cultured atmosphere built,the risk level of diary cattle brucellosis will surly decline.

Entropy method for determination of weight of evaluating indicators in fuzzy synthetic evaluation for water quality assessment

Considering the difficulty of fuzzy synthetic evaluation method in calculation of the multiple factors and ignorance of the relationship among evaluating objects, a new weight evaluation process using entropy method was introduced. This improved method for determination of weight of the evaluating indicators was applied in water quality assessment of the Three Gorges reservoir area. The results showed that this method was favorable for fuzzy synthetic evaluation when there were more than one evaluating objects. One calculation was enough for calculating every monitoring point. Compared with the original evaluation method, the method predigested the fuzzy synthetic evaluation process greatly and the evaluation results are more reasonable.

RELIABILITY ASSESSMENT OF ENTROPY METHOD FOR SYSTEM CONSISTED OF IDENTICAL EXPONENTIAL UNITS

The reliability assessment of unit-system near two levels is the mostimportant content in the reliability multi-level synthesis of complex systems. Introducing theinformation theory into system reliability assessment, using the addible characteristic ofinformation quantity and the principle of equivalence of information quantity, an entropy method ofdata information conversion is presented for the system consisted of identical exponential units.The basic conversion formulae of entropy method of unit test data are derived based on the principleof information quantity equivalence. The general models of entropy method synthesis assessment forsystem reliability approximate lower limits are established according to the fundamental principleof the unit reliability assessment. The applications of the entropy method are discussed by way ofpractical examples. Compared with the traditional methods, the entropy method is found to be validand practicable and the assessment results are very satisfactory.

Identifying influential spreaders in complex networks based on entropy weight method and gravity law

In complex networks,identifying influential spreader is of great significance for improving the reliability of networks and ensuring the safe and effective operation of networks.Nowadays,it is widely used in power networks,aviation networks,computer networks,and social networks,and so on.Traditional centrality methods mainly include degree centrality,closeness centrality,betweenness centrality,eigenvector centrality,k-shell,etc.However,single centrality method is onesided and inaccurate,and sometimes many nodes have the same centrality value,namely the same ranking result,which makes it difficult to distinguish between nodes.According to several classical methods of identifying influential nodes,in this paper we propose a novel method that is more full-scaled and universally applicable.Taken into account in this method are several aspects of node’s properties,including local topological characteristics,central location of nodes,propagation characteristics,and properties of neighbor nodes.In view of the idea of the multi-attribute decision-making,we regard the basic centrality method as node’s attribute and use the entropy weight method to weigh different attributes,and obtain node’s combined centrality.Then,the combined centrality is applied to the gravity law to comprehensively identify influential nodes in networks.Finally,the classical susceptible-infected-recovered(SIR)model is used to simulate the epidemic spreading in six real-society networks.Our proposed method not only considers the four topological properties of nodes,but also emphasizes the influence of neighbor nodes from the aspect of gravity.It is proved that the new method can effectively overcome the disadvantages of single centrality method and increase the accuracy of identifying influential nodes,which is of great significance for monitoring and controlling the complex networks.

Weight Determining of Factors Influencing Grain Output Based on Entropy Weight Method

This article selects 8 main factors(the number of rural employees,total power of agricultural machinery,effective irrigation area of crops,growing area of grain crops,fertilizer consumption,electricity consumption in rural areas,area affected and area covered) as the factors influencing grain output,and offers the method of determining weight of factors influencing grain output using entropy weight method.According to the relevant data in the period 1985-2005,we analyze the weight of factors influencing grain output in China by example.The results show that the electricity consumption in rural areas has the greatest impact on grain output,followed by total power of agricultural machinery,fertilizer consumption and area covered.To increase grain output,we must enhance the degree of mechanization,free people from the former process of direct cultivation,strengthen water conservancy construction,and do a good job in disaster prevention and mitigation.

Entropy Method Based Evaluation for Plant Landscape in Tourist Scenic Spots

Taking five scenic spots in southeast region of Tibet as research objects,this paper calculated the weight of plant landscape evaluation system by entropy weight method,and compared the plant landscape in scenic spots from aesthetic effect,ecological harmony and service functions. The results show that the rank of the comprehensive attributes from high to low is as follows: Nanyigou,Lulang Forest,Kading Mountain Waterfall,Yarlung Zangbo Grand Canyon,and Basomtso Lake.

The deconvolution of lunar brightness temperature based on the maximum entropy method using Chang'e-2 microwave data

A passive and multi-channel microwave sounder onboard the Chang＇e-2 orbiter has successfully acquired microwave observations of the lunar surface and subsurface structure. Compared with the Chang＇e-1 orbiter, the Chang＇e-2 orbiter obtained more accurate and comprehensive microwave brightness temperature data, which are helpful for further research. Since there is a close relationship between mi- crowave brightness temperature data and some related properties of the lunar regolith, such as the thickness, temperature and dielectric constant, precise and high resolution brightness temperature data are necessary for such research. However, through the detection mechanism of the microwave sounder, the brightness temperature data ac- quired from the microwave sounder are weighted by the antenna radiation pattern, so the data are the convolution of the antenna radiation pattern with the lunar brightness temperature. In order to obtain the real lunar brightness temperature, a deconvolution method is needed. The aim of this paper is to solve the problem associated with per- forming deconvolution of the lunar brightness temperature. In this study, we introduce the maximum entropy method （MEM） to process the brightness temperature data and achieve excellent results. The paper mainly includes the following aspects： first, we introduce the principle of the MEM; second, through a series of simulations, the MEM has been verified as an efficient deconvolution method; and third, the MEM is used to process the Chang＇e-2 microwave data and the results are significant.

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.

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.

Dynamic Analysis of Coupling Relationship between Economic Development and Ecological Environment Based on Entropy Method——A Case Study of Xi'an City

[Objective] The aim was to study the coupling relationship between economic development and ecological environment. [Method] Firstly, the evaluation index system for the coupling system of economic development and ecological environment in Xi’an City was established, then the dynamic variation of coupling relationship between economic development and ecological environment in Xi’an City from 2001 to 2010 was analyzed by using entropy method, finally some corresponding suggestions were put forward according to the problems in the current development model. [Result] The economic development and ecological environment of Xi’an have made a significant upgrading and improvement from 2001 to 2010, namely showing a stable upward trend on the whole, and were in a well-coordinated development state in 2010. However, the development level of ecological environment obviously lagged behind economic development level. In addition, there were obvious differences in the development rate of sub-systems, that is, economic efficiency and economic level developed rapidly, while the carrying capacity of ecological environment and economic vitality grew slowly and unstably. [Conclusion] The research could provide theoretical bases for the establishment of strategies for the coordinated development economy and environment in Xi’an City.

Entropy generation analysis of tangent hyperbolic fluid in quadratic Boussinesq approximation using spectral quasi-linearization method

In many industrial applications,heat transfer and tangent hyperbolic fluid flow processes have been garnering increasing attention,owing to their immense importance in technology,engineering,and science.These processes are relevant for polymer solutions,porous industrial materials,ceramic processing,oil recovery,and fluid beds.The present tangent hyperbolic fluid flow and heat transfer model accurately predicts the shear-thinning phenomenon and describes the blood flow characteristics.Therefore,the entropy production analysis of a non-Newtonian tangent hyperbolic material flow through a vertical microchannel with a quadratic density temperature fluctuation(quadratic/nonlinear Boussinesq approximation)is performed in the present study.The impacts of the hydrodynamic flow and Newton’s thermal conditions on the flow,heat transfer,and entropy generation are analyzed.The governing nonlinear equations are solved with the spectral quasi-linearization method(SQLM).The obtained results are compared with those calculated with a finite element method and the bvp4c routine.In addition,the effects of key parameters on the velocity of the hyperbolic tangent material,the entropy generation,the temperature,and the Nusselt number are discussed.The entropy generation increases with the buoyancy force,the pressure gradient factor,the non-linear convection,and the Eckert number.The non-Newtonian fluid factor improves the magnitude of the velocity field.The power-law index of the hyperbolic fluid and the Weissenberg number are found to be favorable for increasing the temperature field.The buoyancy force caused by the nonlinear change in the fluid density versus temperature improves the thermal energy of the system.