Evaluation of soil erosion vulnerability in Hubei Province of China using RUSLE model and combination weighting method

Soil erosion has been recognized as a critical environmental issue worldwide.While previous studies have primarily focused on watershed-scale soil erosion vulnerability from a natural factor perspective,there is a notable gap in understanding the intricate interplay between natural and socio-economic factors,especially in the context of spatial heterogeneity and nonlinear impacts of human-land interactions.To address this,our study evaluates the soil erosion vulnerability at a provincial scale,taking Hubei Province as a case study to explore the combined effects of natural and socio-economic factors.We developed an evaluation index system based on 15 indicators of soil erosion vulnerability:exposure,sensitivity,and adaptability.In addition,the combination weighting method was applied to determine index weights,and the spatial interaction was analyzed using spatial autocorrelation,geographical temporally weighted regression and geographical detector.The results showed an overall decreasing soil erosion intensity in Hubei Province during 2000 and 2020.The soil erosion vulnerability increased before 2000 and then.The areas with high soil erosion vulnerability were mainly confined in the central and southern regions of Hubei Province(Xiantao,Tianmen,Qianjiang and Ezhou)with obvious spatial aggregation that intensified over time.Natural factors(habitat quality index)had negative impacts on soil erosion vulnerability,whereas socio-economic factors(population density)showed substantial spatial variability in their influences.There was a positive correlation between soil erosion vulnerability and erosion intensity,with the correlation coefficients ranging from-0.41 and 0.93.The increase of slope was found to enhance the positive correlation between soil erosion vulnerability and intensity.

A redundant subspace weighting procedure for clock ensemble

A redundant-subspace-weighting(RSW)-based approach is proposed to enhance the frequency stability on a time scale of a clock ensemble.In this method,multiple overlapping subspaces are constructed in the clock ensemble,and the weight of each clock in this ensemble is defined by using the spatial covariance matrix.The superimposition average of covariances in different subspaces reduces the correlations between clocks in the same laboratory to some extent.After optimizing the parameters of this weighting procedure,the frequency stabilities of virtual clock ensembles are significantly improved in most cases.

Numerical Simulation of Oil-Water Two-Phase Flow in Low Permeability Tight Reservoirs Based on Weighted Least Squares Meshless Method

In response to the complex characteristics of actual low-permeability tight reservoirs,this study develops a meshless-based numerical simulation method for oil-water two-phase flow in these reservoirs,considering complex boundary shapes.Utilizing radial basis function point interpolation,the method approximates shape functions for unknown functions within the nodal influence domain.The shape functions constructed by the aforementioned meshless interpolation method haveδ-function properties,which facilitate the handling of essential aspects like the controlled bottom-hole flow pressure in horizontal wells.Moreover,the meshless method offers greater flexibility and freedom compared to grid cell discretization,making it simpler to discretize complex geometries.A variational principle for the flow control equation group is introduced using a weighted least squares meshless method,and the pressure distribution is solved implicitly.Example results demonstrate that the computational outcomes of the meshless point cloud model,which has a relatively small degree of freedom,are in close agreement with those of the Discrete Fracture Model(DFM)employing refined grid partitioning,with pressure calculation accuracy exceeding 98.2%.Compared to high-resolution grid-based computational methods,the meshless method can achieve a better balance between computational efficiency and accuracy.Additionally,the impact of fracture half-length on the productivity of horizontal wells is discussed.The results indicate that increasing the fracture half-length is an effective strategy for enhancing production from the perspective of cumulative oil production.

Legendre-Weighted Residual Methods for System of Fractional Order Differential Equations

The numerical approach for finding the solution of fractional order systems of boundary value problems (BPVs) is derived in this paper. The implementation of the weighted residuals such as Galerkin, Least Square, and Collocation methods are included for solving fractional order differential equations, which is broadened to acquire the approximate solutions of fractional order systems with differentiable polynomials, namely Legendre polynomials, as basis functions. The algorithm of the residual formulations of matrix form can be coded efficiently. The interpretation of Caputo fractional derivatives is employed here. We have demonstrated these methods numerically through a few examples of linear and nonlinear BVPs. The results in absolute errors show that the present method efficiently finds the numerical solutions of fractional order systems of differential equations.

Application of combination weighting method in contract risk's evaluation of third party logistics

First,the analytical hierarchy process(AHP),which stands for the subjective weighting method,and the entropy method,which stands for the objective weighting method,are chosen to calculate the index weights of the contract risks of third party logistics(TPL),respectively.Then,they can determine the combination weights using the combination weighting method.Second,using the combination weights,the contract risks of TPL are evaluated through the fuzzy comprehensive evaluation method.According to the combination weights,the most important risk factor of the contract risks of TPL is choosing sub-contractors.The results are basically consistent with the facts and show that the weights determined by the combination weighting method can avoid the man-made deviations of the subjective weighting method on the one hand,and prevent results opposite to the reality brought about by the objective weighting method on the other hand.Meanwhile,the results of the fuzzy comprehensive evaluation are that the contract risks of TPL are at a high risk level.Roughly this matches real situations,and it indicates that the combination weighting method can generate the comprehensive assessment more scientifically and more reasonably as well.

Comprehensive evaluation of the transformer oil-paper insulation state based on RF-combination weighting and an improved TOPSIS method

The accurate identification of the oil-paper insulation state of a transformer is crucial for most maintenance strategies.This paper presents a multi-feature comprehensive evaluation model based on combination weighting and an improved technique for order of preference by similarity to ideal solution(TOPSIS)method to perform an objective and scientific evaluation of the transformer oil-paper insulation state.Firstly,multiple aging features are extracted from the recovery voltage polarization spectrum and the extended Debye equivalent circuit owing to the limitations of using a single feature for evaluation.A standard evaluation index system is then established by using the collected time-domain dielectric spectrum data.Secondly,this study implements the per-unit value concept to integrate the dimension of the index matrix and calculates the objective weight by using the random forest algorithm.Furthermore,it combines the weighting model to overcome the drawbacks of the single weighting method by using the indicators and considering the subjective experience of experts and the random forest algorithm.Lastly,the enhanced TOPSIS approach is used to determine the insulation quality of an oil-paper transformer.A verification example demonstrates that the evaluation model developed in this study can efficiently and accurately diagnose the insulation status of transformers.Essentially,this study presents a novel approach for the assessment of transformer oil-paper insulation.

AModel for the Optimization of the Shale Gas HorizontalWell Section Based on the Combination of Different Weighting Methods in the Frame of the Game Theory

Existing“evaluation indicators”are selected and combined to build a model to support the optimization of shale gas horizontal wells.Towards this end,different“weighting methods”,including AHP and the so-called entropy method,are combined in the frame of the game theory.Using a relevant test case for the implementation of the model,it is shown that the horizontal section of the considered well is in the middle sweet spot area with good physical properties and fracturing ability.In comparison with the FSI(flow scanner Image)gas production profile,the new model seems to display better abilities for the optimization of horizontal wells.

Benefit allocation model of distributed photovoltaic power generation vehicle shed and energy storage charging pile based on integrated weighting-Shapley method

In this study,to develop a benefit-allocation model,in-depth analysis of a distributed photovoltaic-powergeneration carport and energy-storage charging-pile project was performed;the model was developed using Shapley integrated-empowerment benefit-distribution method.First,through literature survey and expert interview to identify the risk factors at various stages of the project,a dynamic risk-factor indicator system is developed.Second,to obtain a more meaningful risk-calculation result,the subjective and objective weights are combined,the weights of the risk factors at each stage are determined by the expert scoring method and entropy weight method,and the interest distribution model based on multi-dimensional risk factors is established.Finally,an example is used to verify the rationality of the method for the benefit distribution of the charging-pile project.The results of the example indicate that the limitations of the Shapley method can be reasonably avoided,and the applicability of the model for the benefit distribution of the charging-pile project is verified.

Engineering Geological Zoning of Soft-Soil Foundation Based on Combination Weighting and Extension Methods

Different criteria and factors are used in different methods of soft soil foundation settlement calculation and engineering geological zoning.The methods used are not universally suitable for complex geological environments.The post-construction settlement of soft soil foundations are especially large and difficult to calculate.In addition,there are many deficiencies in the current methods used for engineering geological zoning.Focusing on the need of establishing engineering geological zoning for areas with soft soil foundations in the Tianjin Marine Economic Area,combination weighting and extension methods were introduced.An evaluation model for the settlement of soft soil foundations was established using multiple factors and large amounts of data.This evaluation model is accurate and objective for delineating engineering geological zoning.These methods eliminate deficiencies by considering both objective and subjective factors,and help obtain an objective and accurate result.

Synoptic review on existing and potential sources for bias in dental research methodology with methods on their prevention and remedies

The results of years of dental study serve as the foundation for the practise of medicine and,for that matter,dentistry.Doctors may have their own preferences for techniques and materials,but whether directly or indirectly,their decisions are influenced by systematic reviews and meta-analyses.However,due to poorly conducted or presented research,this very basic foundation may not be reliable.Bias in research is one of several factors that might make study results or research itself unreliable.Bias can be introduced into research at many stages,deliberately or unknowingly.Bias can appear at any point during the research process,even before the study itself begins.There are many biases in research,but some of them are more relevant to dentistry research than others.Because it is said that“eyes see what the mind knows”,it is essential to have a complete understanding of the different types of bias,how and when they get entrenched,and what steps may be taken to prevent or lessen them if they do occur.This comprehensive summary of bias in dentistry research is provided by this synoptic review.The goal is to identify gaps and measures that have been taken-or that should have been taken-by providing both descriptive and evaluative summaries,as well as examples from the literature,when needed.

A robust triaxial localization method of AE source using refraction path

Acoustic emission(AE)localization algorithms based on homogeneous media or single-velocity are less accurate when applied to the triaxial localization experiments.To the end,a robust triaxial localization method of AE source using refraction path is proposed.Firstly,the control equation of the refraction path is established according to the sensor coordinates and arrival times.Secondly,considering the influence of time-difference-of-arrival(TDOA)errors,the residual of the governing equation is calculated to estimate the equation weight.Thirdly,the refraction points in different directions are solved using Snell’s law and orthogonal constraints.Finally,the source coordinates are iteratively solved by weighted correction terms.The feasibility and accuracy of the proposed method are verified by pencil-lead breaking experiments.The simulation results show that the new method is almost unaffected by the refraction ratio,and always holds more stable and accurate positioning performance than the traditional method under different ratios and scales of TDOA outliers.

A Simple Additive Weighting Method for Time-SeriesMultiindices Decision Making and Its Applications

This paper takes the evaluation of overall economic benefit by an example and proposes a simple additive weighting method for time-series multiindices decision making. The method can automatically determine the weight coefficients among the multiindices and the years respectively and it also can obtain the objective evaluation results and conclusions.

Evaluation of Growth of Agricultural Listed Companies Based on AHP Weighting Method

Agriculture is the foundation of national economy,and agricultural development is related to the rapid development of long-term stability of the society and economy. Agriculture includes farming,forestry,animal husbandry,and fisheries. Agricultural listed company as an agricultural enterprise " leader",which directly affects the development of the entire growth of the agricultural industry development and policy,so the study of agricultural listed company's growth is particularly important. This paper uses AHP weighting method to evaluate 2012 financial data on the growth of agricultural listed companies.

Existence of a Sigh-Changing Solution Result for Logarithmic Schrödinger Equations with Weight Function

This paper is devoted to studying the existence of solutions for the following logarithmic Schrödinger problem: −div(a(x)∇u)+V(x)u=ulogu2+k(x)| u |q1−2u+h(x)| u |q2−2u, x∈ℝN.(1)We first prove that the corresponding functional I belongs to C1(HV1(ℝN),ℝ). Furthermore, by using the variational method, we prove the existence of a sigh-changing solution to problem (1).

Biasing transition rate method based on direct MC simulation for probabilistic safety assessment

Direct Monte Carlo(MC) simulation is a powerful probabilistic safety assessment method for accounting dynamics of the system.But it is not efficient at simulating rare events.A biasing transition rate method based on direct MC simulation is proposed to solve the problem in this paper.This method biases transition rates of the components by adding virtual components to them in series to increase the occurrence probability of the rare event,hence the decrease in the variance of MC estimator.Several cases are used to benchmark this method.The results show that the method is effective at modeling system failure and is more efficient at collecting evidence of rare events than the direct MC simulation.The performance is greatly improved by the biasing transition rate method.

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.

WEIGHTED LEAST SQUARE METHOD FOR S-N CURVE FITTING

An S-N curve fitting approach is proposed based on the weighted least square method, and the weights are inversely proportional to the length of mean confidence intervals of experimental data sets. The assumption coincides with the physical characteristics of the fatigue life scatter. Two examples demonstrate the method. It is shown that the method has better accuracy and reasonableness compared with the usual least square method.

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.

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.

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.