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.

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.

Differentiation degree combination weighting method for investment decision-making risk assessment in power grid construction projects

Power grid construction projects are distinguished by their wide variety,high investment,long payback period,and close relation to national development and human welfare.To improve the investment accuracy in such projects and effectively prevent investment risks,this paper proposes an investment optimization decision-making method for multiple power grid construction projects under a certain investment scale.Firstly,an in-depth analysis of the characteristics and development requirements of China’s power grid projects was performed.Thereafter,the time sequence and holographic method was adopted to conduct multi-dimensional,multi-perspective risk assessment of different parts of power grid projects,and a holographic risk assessment index system was developed.Moreover,an investment decision model considering the comprehensive risk based on combination weighting was developed according to the output and input of power grid construction projects.A new combination weighting optimization method that takes into account the investment willingness of enterprises was designed to improve the current weighting evaluation methods.Finally,the validity and applicability of the proposed evaluation method were verified by case examples.

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.

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.

Optimizing selection of bridge raft based on fuzzy matter-element model and combination weighting

It＇ s a necessary selection to support the maneuver across Yangtze River by floating bridge constructed by portable steel bridge and civilian ships. It is a comprehensive index for the scheme of bridge raft, containing a variety of technical factors and uncertainties. The optimization is the selection in the constructing time, quantity of equipments and man power. Based on the calculation result of bridge rafts, an evaluating system is established, consisting of index of spacing between interior bays, raft length, truss numbers, operation difficulty and maximal bending stress. A fuzzy matter element model of optimizing selection of bridge rafts was built up by combining quantitative analysis with qualitative analysis. The method of combination weighting was used to calculate the value of weights index to reduce the subjective randomness. The sequence of schemes and the optimization resuh were gained finally based on euclid approach degree. The application result shows that it is simple and practical.

Using GIS-Based Weighted Linear Combination Analysis and Remote Sensing Techniques to Select Optimum Solid Waste Disposal Sites within Mafraq City, Jordan

Landfill siting was determined within Mafraq City, Jordan, through the integration of geographic information system (GIS), weighted linear combination (WLC) analysis, and remote sensing techniques. Several parameters were collected from various sources in vector and raster GIS formats, and then, used within the GIS-based WLC analysis to select optimum solid waste disposal sites. Namely, urban areas, agricultural lands, access roads, surface aquifers, groundwater table, fault system, water wells, streams, and land slope were considered in this research. Also, the trend of urban expansion within the study area was monitored using the Landsat data of 1989, 1999, and 2009 to support the selection process of disposal sites. It is found that about 84% of the study area was within “most suitable” to “moderately suitable” classes for landfill sites, while the rest of the study area was within “poorly suitable” and “unsuitable” classes. Based on the analysis of Landsat satellite data the urban area was expanded of more than 240% during the last three decades, mainly toward south, and southwest, except the villages near the existing disposal site, where the trend was toward east and northeast. Finally, three sites were suggested as alternatives to the existing disposal site taking into the consideration the environmental, biophysical, and economical variables applied in the GIS-based WLC analysis.

The Optimal Weighted Combinational Forecasting with Constant Terms

We propose a model based on the optimal weighted combinational forecasting with constant terms, give formulae of the weights and the average errors as well as a relation of the model and the corresponding model without constant terms, and compare these models. Finally an example was given, which showed that the fitting precision has been enhanced.

Potential Hazard Map for Snow Disaster Prevention Using GIS-Based Weighted Linear Combination Analysis and Remote Sensing Techniques: A Case Study in Northern Xinjiang, China

Snow disaster is one of the top ten natural disasters worldwide. Almost every year, there will be snow disasters in north Xinjiang, northwestern China. Since the accumulated heavy snow in winter season will seriously threaten people’s lives, the main object of this study is to produce a potential hazard map for snow avalanche prevention. Taking three snow seasons from November to March of year 2008 to 2010, potential hazard areas were estimated, based on snow volume products and terrain features. Remote sensing (RS) techniques and geographical information system (GIS) based weighted linear combination (WLC) approach were applied, taking into consideration multiple criteria. Snow avalanche risks were analyzed using physical exposure and vulnerability indexes. The analysis indicates that: the areas at high-risk of avalanches are located in the north and south part of the counties of Altay, Bortala and Ili prefectures;the areas at medium-risk of avalanches are found in the certain part of Altay prefecture and Urumqi, Changji, Tacheng prefectures;the avalanche risk is generally low throughout the large area to the certain part of the study area and the region on the border of the eastern north Xinjiang. Overall, the risks of snow avalanche in Altay and Ili prefectures are higher than that other regions;those areas should be allocated correspondingly more salvage materials.

Sustainability Intelligent Evaluation of Regional Microgrid Interconnection System Based on Combination Entropy Weight Rank Order-TOPSIS and NILA-KELM

Sustainability evaluation of regional microgrid interconnection system is conducive to a profound and comprehensive understanding of the impact of interconnection system projects.In order to realize the comprehensive and scientific intelligent evaluation of the system,this paper proposes an evaluation model based on combination entropy weight rank order-technique for order preference by similarity to an ideal solution(TOPSIS)and Niche Immune Lion Algorithm-Extreme Learning Machine with Kernel(NILAKELM).Firstly,the sustainability evaluation indicator system of the regional microgrid interconnection system is constructed fromfour aspects of economic,environmental,social,and technical characteristics,and the evaluation indicators are explained.Then,the classical evaluationmodel based on TOPSIS is constructed,and the entropy weight method and rank order method(RO)are coupled to obtain the indicator weight.The niche immune algorithm is used to improve the lion algorithm,and the improved lion algorithm is used to optimize the parameters of KELM,and the intelligent evaluation model based on NILA-KELM is obtained to realize fast real-time calculation.Finally,the scientificity and accuracy of themodel proposed in this paper are verified.The model proposed in this paper has the lowest RMSE,MAE and RE values,indicating that its intelligent evaluation results are the most accurate.This study is conducive to the horizontal comparison of the overall performance of regional microgrid interconnection system projects,helps investors to choose the most promising project scheme,and helps the government to find feasible project.

A Weighted Combination Forecasting Model for Power Load Based on Forecasting Model Selection and Fuzzy Scale Joint Evaluation

To solve the medium and long term power load forecasting problem,the combination forecasting method is further expanded and a weighted combination forecasting model for power load is put forward.This model is divided into two stages which are forecasting model selection and weighted combination forecasting.Based on Markov chain conversion and cloud model,the forecasting model selection is implanted and several outstanding models are selected for the combination forecasting.For the weighted combination forecasting,a fuzzy scale joint evaluation method is proposed to determine the weight of selected forecasting model.The percentage error and mean absolute percentage error of weighted combination forecasting result of the power consumption in a certain area of China are 0.7439%and 0.3198%,respectively,while the maximum values of these two indexes of single forecasting models are 5.2278%and 1.9497%.It shows that the forecasting indexes of proposed model are improved significantly compared with the single forecasting models.

Evaluation model of venture investment based on fuzzy matter-element method of combined weight

An evaluation model of an international venture investment project on the basis of fuzzy matter-element and combined weight methods is introduced. First, the compound fuzzy matter-element of optimal subordinate degree is constructed on the principle of the bigger-more-optimal or the less-more-optimal depending on the actual evaluation indicators, and combined with standard fuzzy matter-element to form a difference-square fuzzy matter-element. Secondly, a combined weight is calculated by both information entropy and the expert grading method. Finally, the compound fuzzy matter-element of Euclidian approach degree by M(·,+)method is constituted and used to classify venture investment projects. Based on the model above, six venture investment projects in a company are evaluated, and the results show that the projects are all good, which is demonstrated by the good income of the projects. Therefore, the coincidence of evaluation results and actual operation status indicates that the model is of great value in practical application.

New weighting factors assignment of evidence theorybased one vidence distance

Evidence theory has been widely used in the information fusion for its effectiveness of the uncertainty reasoning. However, the classical DS evidence theory involves counter-intuitive behaviors when the high conflict information exists. Based on the analysis of some modified methods, Assigning the weighting factors according to the intrinsic characteristics of the existing evidence sources is proposed, which is determined on the evidence distance theory. From the numerical examples, the proposed method provides a reasonable result with good convergence efficiency. In addition, the new rule retrieves to the Yager's formula when all the evidence sources contradict to each other completely.

Settlement Prediction of Dredger Fill with the Optimal Combination Model

Post-construction settlement has gained increasing attention because it frequently causes engineering problems. A combined model is a commonly used prediction model that overcomes the difficulty of a single model( i. e., cannot reflect various regulations of settlement at some stages or the entire process). In this study,the correlation coefficient,maximum error values,and other values were obtained according to the fitting and predicted results of a single model. The coefficient of variation was then introduced to determine the weight of each model forming the combination. The proposed model was used to fit and predict for settlement and overcome the issue of utilizing a single model while determining the weight. The fitting predictive effect was also analyzed using the settlement fitting precision results. The fitting precision of optimizing the combination model is high. The predicted data of the post-construction settlement are closer to the calculated value of the settlement monitoring data. Moreover,the proposed model has good practicability,does not require the interval data of settlement,and restricts the model number. Thus,this model can be applied in the engineering field.

Nonlinear combined forecasting model based on fuzzy adaptive variable weight and its application

In order to enhance forecasting precision of problems about nonlinear time series in a complex industry system,a new nonlinear fuzzy adaptive variable weight combined forecasting model was established by using conceptions of the relative error,the change tendency of the forecasted object,gray basic weight and adaptive control coefficient on the basis of the method of fuzzy variable weight.Based on Visual Basic 6.0 platform,a fuzzy adaptive variable weight combined forecasting and management system was developed.The application results reveal that the forecasting precisions from the new nonlinear combined forecasting model are higher than those of other single combined forecasting models and the combined forecasting and management system is very powerful tool for the required decision in complex industry system.

Generalized weighted functional proportional mean combining forecasting model and its method of parameter estimation

A new kind of combining forecasting model based on the generalized weighted functional proportional mean is proposed and the parameter estimation method of its weighting coefficients by means of the algorithm of quadratic programming is given. This model has extensive representation. It is a new kind of aggregative method of group forecasting. By taking the suitable combining form of the forecasting models and seeking the optimal parameter, the optimal combining form can be obtained and the forecasting accuracy can be improved. The effectiveness of this model is demonstrated by an example.

The Average Errors for Linear Combinations of Bernstein Operators on the Wiener Space

In this paper, we discuss the average errors of function approximation by linear combinations of Bernstein operators. The strongly asymptotic orders for the average errors of the combinations of Bernstein operators sequence are determined on the Wiener space.

Growth Performance and Adaptability of Sugarcane Combinations Under Different Ecological Environments

The experiments of sugarcane combination evaluation were conducted on 119 combinations during 2017-2018 crossing season in Nanning,Chongzuo and Laibin of Guangxi.The conjoint analysis of variance and estimation of genetic parameters were performed based on brix weight.Furthermore,combination stability was analyzed by regression analysis model and AMMI model.The results showed that differences in brix weight among combinations,environments and interaction between environments and combinations were all extremely significant(P<0.01),and the broad-sense heritability of brix weight belonged to medium level or slightly lower at the three sites.In both Chongzuo and Laibin,the variation coefficients of brix weight were large,but that in Nanning was small.Combinations 643,404,575,972,636,144,YC95,1470,755,409,701,832,YC37 and 579 performed high yield,high genetic stability and stronger adaptability.The results of comprehensive analysis in both brix weight and selection rate of combination showed that 449,YC127,796,YC44,533,570,YC123,391,546,403,YC90 and 252 performed high brix weight and high selection rate of combination in Nanning;combinations 643,212,YC61,432,903,YC95,YC44,368,YC83,YC127,YC112,701,411,YC90 and YC123 demonstrated high brix weight and high selection rate of combination in Chongzuo;and combinations 643,404,449,144,403 and YC48 had high brix weight and high selection rate of combination in Laibin.

A weighted averaging method for signal probability of logic circuit combined with reconvergent fan-out structures

By analyzing the structures of circuits,a novel approach for signal probability estimation of very large-scale integration(VLSI)based on the improved weighted averaging algorithm(IWAA)is proposed.Considering the failure probability of the gate,first,the first reconvergent fan-ins corresponding to the reconvergent fan-outs were identified to locate the important signal correlation nodes based on the principle of homologous signal convergence.Secondly,the reconvergent fan-in nodes of the multiple reconverging structure in the circuit were identified by the sensitization path to determine the interference sources to the signal probability calculation.Then,the weighted signal probability was calculated by combining the weighted average approach to correct the signal probability.Finally,the reconvergent fan-out was quantified by the mixed-calculation strategy of signal probability to reduce the impact of multiple reconvergent fan-outs on the accuracy.Simulation results on ISCAS85 benchmarks circuits show that the proposed method has approximate linear time-space consumption with the increase in the number of the gate,and its accuracy is 4.2%higher than that of the IWAA.