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.

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.

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.

Evaluating the Derivative Value of Smart Grid Investment under Dual Carbon Target: A Hybrid Multi-Criteria Decision-Making Analysis

With the goal of“carbon peaking and carbon neutralization”,it is an inevitable trend for investing smart grid to promote the large-scale grid connection of renewable energy.Smart grid investment has a significant driving effect(derivative value),and evaluating this value can help to more accurately grasp the external effects of smart grid investment and support the realization of industrial linkage value with power grid investment as the core.Therefore,by analyzing the characterization of the derivative value of smart grid driven by investment,this paper constructs the evaluation index system of the derivative value of smart grid investment including 11 indicators.Then,the hybrid evaluation model of the derivative value of smart grid investment is developed based on anti-entropy weight(AEW),level based weight assessment(LBWA),and measurement alternatives and ranking according to the compromise solution(MARCOS)techniques.The results of case analysis show that for SG investment,the value of sustainable development can better reflect its derivative value,and when smart grid performs poorly in promoting renewable energy consumption,improving primary energy efficiency,and improving its own fault resistance,the driving force of its investment for future sustainable development will decline significantly,making the grid investment lack derivative value.In addition,smart grid investment needs to pay attention to the economy of investment,which is an important guarantee to ensure that the power grid has sufficient and stable sources of investment funds.Finally,compared with three comparison models,the proposed hybrid multi-criteria decision-making(MCDM)model can better improve the decision-making efficiency on the premise of ensuring robustness.

Investigation on the Long Term Operational Stability of Underground Energy Storage in Salt Rock

Underground energy storage is an important function of all energy supply systems,and especially concerning the seemingly eternal imbalance between production and demand.Salt rock underground energy storage,for one,is widely applied in both traditional and renewable energy fields;and this particular technique can be used to store natural gas,hydrogen,and compressed air.However,resource diversification and structural complexity make the supply system increasingly uncertain with the passing years,leading to great challenges for energy storage facilities in the present,and perhaps going into the future as well.Hence,it is necessary to research the operation stability of underground energy storage further.In this paper,a stability evaluation index system of Underground Gas Storage(UGS)is constructed with natural gas as the main medium,according to FLAC 3D cavity creep simulation software,along with fuzzy membership function to comprehensively determine the impact factor scoring model;the subjective weight is calculated based on the improved Analytic Hierarchy Process(AHP),the objective weight is calculated by the Entropy Weight Method(EWM),the combined constant weight is obtained by combining the variance maximization theory,and introducing the variable weight theory to obtain a more accurate combined variable weight.Finally,with this all being considered and accounted for,and with the four different conditions designed for UGS deployment case analysis and verification taken into consideration,the combined variable weight evaluation achieved excellent results;compared with the traditional constant weight method,in fact,the new evaluation results are more rigorous and objective.

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.

医院季度收入预测的比较研究

目的 探讨具有季度波动和长期趋势特征事物预测问题的方法论,为卫生领域同类预测问题提供定量决策方法论依据。方法 以某所医院季度收入预测作为实证算例载体,分别用乘积季节SARIMA法、X11-ARIMA法、X11-曲线函数外推法建立简单组合模型以及二次加权组合模型。结果 乘积季节SARIMA模型、X11-ARIMA模型、X11-二次多项式的平均相对误差分别为1.28%、0.96%、1.11%。对以上简单组合模型继续进行深度加权组合,预测误差为0.70%,模型预测性能更优。结论 SARIMA模型、X11-ARIMA模型、X11-二次多项式以及二次组合模型对于局部周期性波动、全局稳定性趋势的时序数据资料拟合效果不错;对于卫生管理领域预测问题有适用性,鉴于多种匹配方法原理不同、信息利用差异大,基于多种方法的二次组合模型取得更优性能。

Land use suitability analysis for town development planning in Nanjing hilly areas: A case study of Tangshan new town, China

Land use suitability analysis plays an important role in sustainable land use and solving environmental problems caused by rapid urban development.A land use suitability mapping approach for town development planning in hilly areas was constructed based on two multi-criteria evaluation methods:Weighted Linear Combination(WLC)and Ordered Weighted Averaging(OWA),to comparatively evaluate and map land use suitability of Tangshan new town in Nanjing,China.Fourteen evaluation factors related to topographic,environmental,socio-economics and historical sites data were used as suitability criteria.The analytic hierarchy process(AHP)method and GIS techniques were integrated into the evaluation models to create the land use suitability map for town development planning.The results of WLC approach showed that 11.4%of the total area is highly suitable while the 48.6%is unsuitable.The results of WLC and OWA approach showed the distribution of degree of land use suitability is almost the same.The areas located at the southern and eastern flat regions are highly suitable for land use,whereas the areas close to the mountain forests,steep slopes,waters,and hot springs,have lower suitability for land use.Sensitivity analysis indicated that the suitability results of the two proposed methods are robust.Indirect validation was achieved by mutual comparison of suitability maps derived from the WLC and OWA methods.It demonstrated that the overall agreement is 90.81%and kappa coefficient is 0.81,indicating that both methods provide very similar spatial suitability distributions.By overlaying the resultant map with the previous master plan map of Tangshan new town,the overlay map once again indicated a satisfactory ecological fit between the two maps.At last,several recommendations are proposed aiming at improving the long-term town development plan for Tangshan new town.

Neural Network Compact Ensemble and Its Applications

There has been many methods in constructing neural network （NN） ensembles, where the method of simultaneous training has succeed in generalization performance and efficiency. But just like regular methods of constructing NN ensembles, it follows the two steps, first training component networks, and then combining them. As the two steps being independent, an assumption is used to facilitate interactions among NNs during the training stage. This paper presents a compact ensemble method which integrates the two steps of ensemble construction into one step by attempting to train individual NNs in an ensemble and weigh the individual members adaptively according to their individual performance in the same learning process. This provides an opportunity for the individual NNs to interact with each other based on their real contributions to the ensemble. The classification performance of NN compact ensemble （NNCE） was validated through some benchmark problems in machine learning, including Australian credit card assessment, pima Indians diabetes, heart disease, breast cancer and glass. Compared with other ensembles, the classification error rate of NNCE can be decreased by 0.45% to 68%. In addition, the NNCE was applied to fault diagnosis for rolling element bearing. The 11 time-domain statistical features are extracted as the properties of data, and the NNCE is employed to classify the data. With the results of several experiments, the compact ensemble method is shown to give good generalization performance. The compact ensemble method can recognize the different fault types and various fault degrees of the same fault type.

Winter wheat yield estimation based on assimilated Sentinel-2 images with the CERES-Wheat model

Assimilating Sentinel-2 images with the CERES-Wheat model can improve the precision of winter wheat yield estimates at a regional scale. To verify this method, we applied the ensemble Kalman filter(EnKF) to assimilate the leaf area index(LAI) derived from Sentinel-2 data and simulated by the CERES-Wheat model. From this, we obtained the assimilated daily LAI during the growth stage of winter wheat across three counties located in the southeast of the Loess Plateau in China: Xiangfen, Xinjiang, and Wenxi. We assigned LAI weights at different growth stages by comparing the improved analytic hierarchy method, the entropy method, and the normalized combination weighting method, and constructed a yield estimation model with the measurements to accurately estimate the yield of winter wheat. We found that the changes of assimilated LAI during the growth stage of winter wheat strongly agreed with the simulated LAI. With the correction of the derived LAI from the Sentinel-2 images, the LAI from the green-up stage to the heading–filling stage was enhanced, while the LAI decrease from the milking stage was slowed down, which was more in line with the actual changes of LAI for winter wheat. We also compared the simulated and derived LAI and found the assimilated LAI had reduced the root mean square error(RMSE) by 0.43 and 0.29 m^(2) m^(–2), respectively, based on the measured LAI. The assimilation improved the estimation accuracy of the LAI time series. The highest determination coefficient(R2) was 0.8627 and the lowest RMSE was 472.92 kg ha^(–1) in the regression of the yields estimated by the normalized weighted assimilated LAI method and measurements. The relative error of the estimated yield of winter wheat in the study counties was less than 1%, suggesting that Sentinel-2 data with high spatial-temporal resolution can be assimilated with the CERES-Wheat model to obtain more accurate regional yield estimates.

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.

Calculation of Water Pollution Control Performance Index:A Case Study of Beijing City

To explore water pollution control level in Beijing,performance evaluation index system of water pollution control in Beijing was constructed based on DPSR framework.Taking driving force,pressure,state and response as primary indexes,25 secondary indexes were established.The combined weighting of the index system was conducted by entropy weight method,coefficient of variation method and CRITIC method.The performance index of water pollution control in Beijing from 2010 to 2018 was calculated,and its dynamic change trend was analyzed.The results showed that the performance index of water pollution control in Beijing was low from 2010 to 2014,but increased year by year from 2015 to 2018,with a good trend.

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.

Synthetic Evaluation of Steady-state Power Quality Based on Combination Weighting and Principal Component Projection Method

With integration of renewable energy and use of non-linear loads in power systems,the power quality problem is increasingly attracting attention of researchers.In China,standards for individual power quality indexes are set.However,when evaluating power quality in practice,individual indexes cannot directly reflect a comprehensive level of power quality.In this paper,a comprehensive analysis of various indexes is conducted to obtain a unified parameter for describing the characteristics of power quality from an overall perspective.First,weight values of power quality indexes are calculated by combining the subjective and objective weight.Then,based on the principal components of the projection method,projection values of boundary data and data to be evaluated are obtained.Finally,using these projection values,a grade range for power quality data is located.A practical case study is presented to show the validity of the proposed method for evaluating power quality.

Safety Evaluation Method for Long-Term Operation of Metro Based on Combination Weighting Method

Metros are critical infrastructure in big cities and evaluation of their safe operation is of increasing im-portance.To make a reasonable safety evaluation for the metro during operation,this paper establishes a rational safety evaluation model based on long-term monitoring data of Shanghai Metro Line 2.Four evaluation indicators,ie.,absolute settlement,relative curvature,deformation rate and curvature radius,are adopted.Analytic hierar-chy process(AHP)and entropy method are combined to determine the weights of the indicators.The risk level values at different mileage are calculated and five danger levels are defined accordingly to determine the safety state of Shanghai Metro Line 2,ie.,safe,relatively safe,critical,relatively dangerous,and dangerous.Safety evaluation of Shanghai Metro Line 2 shows that:83.81%areas of Shanghai Metro Line 2 are in safe,relatively safe and critical states,while 15.63%and 0.57%areas are in relatively dangerous and dangerous states,respectively;the parts of Shanghai Metro Line 2 where the risk level values exceed the critical value are mainly distributed around the mileage at 6.0-7.5km and 8.5-11.0 km,and the risk level value peaks around the mileage at 7.3km,to which much attention should be attached and relevant protective measures be taken;the sections with the high risk level values coincide with the distinctly deforming arcas of the metro,indicating that this evaluation method is valid.

A combination weighting model based on iMOEA/D-DE

This paper proposes a combination weighting(CW)model based on iMOEA/D-DE(i.e.,improved multiobjective evolutionary algorithm based on decomposition with differential evolution)with the aim to accurately compute the weight of evaluation methods.Multi-expert weight considers only subjective weights,leading to poor objectivity.To overcome this shortcoming,a multiobjective optimization model of CW based on improved game theory is proposed while considering the uncertainty of combination coefficients.An improved mutation operator is introduced to improve the convergence speed,and thus better optimization results are obtained.Meanwhile,an adaptive mutation constant and crossover probability constant with self-learning ability are proposed to improve the robustness of MOEA/D-DE.Since the existing weight evaluation approaches cannot evaluate weights separately,a new weight evaluation approach based on relative entropy is presented.Taking the evaluation method of integrated navigation systems as an example,certain experiments are carried out.It is proved that the proposed algorithm is effective and has excellent performance.

Spatial diversity and combination technology using amplitude and phase weighting method for phase-coherent underwater acoustic communications

The UWA channel is characterized as a time-dispersive rapidly fading channel, which in addition exhibits Doppler instabilities and limited bandwidth. To eliminate inter- symbol interference caused by multipath propagation, spatial diversity equalization is the main technical means. The paper combines the passive phase conjugation and spatial processing to maximize the output array gain. It uses signal-to-noise-plus-interference to evaluate the quality of signals received at different channels. The amplitude of signal is weighted using Sigmoid function. Second order PLL can trace the phase variation caused by channel, so the signal can be accumulated in the same phase. The signals received at different channels need to be normal- ized. It adopts fractional-decision feedback diversity equalizer （FDFDE） and achieves diversity equalization by using different channel weighted coefficients. The simulation and lake trial data processing results show that, the optimized diversity receiving equalization algorithm can im- prove communication system＇s ability in tracking the change of underwater acoustic channel, offset the impact of multipath and noise and improve the performance of communication system. The performance of the communication receiving system is better than that of the equal gain combination. At the same time, the bit error rate （BER） reduces 1.8%.

Water quality characteristics and assessment of Yongding New River by improved comprehensive water quality identification index based on game theory

The Yongding New River is essential for the water supplies of Tianjin.To date,there is no comprehensive report that assesses the year-round water quality of the Yongding New River Main stream.Moreover,little attention has been given to determining a combined weight for improving the traditional comprehensive water quality identification index(ICWQII)by the game theory.Seven water quality parameters were investigated monthly along the main stream of the Yongding New River from May 2018 to April 2019.Organic contaminants and nitrogen pollution were mainly caused by point sources pollution,and the total phosphorus mainly by non-point source pollution.Dramatic spatio-temporal variations of water quality parameters were jointly caused by different pollutant sources and hydrometeorological factors.In terms of this study,an improved comprehensive water quality identification index(ICWQII)based on entropy weight or variation coefficient and traditional CWQII underestimated the water qualities,and an ICWQII based on the superstandard multiple method overvalued the assessments.By contrast,water qualities assessments done with an ICWQII based on the game theory matched perfectly with the practical situation.The ICWQII based on game theory proposed in this study takes into account not only the degree of disorder and variation of water quality data,but also the influence of standard-exceeded pollution indicators,whose results are relatively reasonable.All findings and the ICWQII based on game theory can provide scientific support for decisions related to the water environment management of the Yongding New River and other waters.

A Hybrid FCW-EMD and KF-BA-SVM Based Model for Short-term Load Forecasting

This paper proposes a hybrid short-term load forecasting method,which is based on the fuzzy combination weights as well as the empirical mode decomposition process(FCW-EMD),and support vector machine optimized via the Bat algorithm as well as the Kalman filtering process(KF-BA-SVM).The subjective weight is presented as a new theory and is applied to capture the inherent correlation effectively among hourly loads.Based on the proposed objective weights and subjective weights,the fuzzy combination weights theory(FCW)-a new similar day selection theory is presented,which improves the accuracy of the similar day selection,and correspondingly,makes the original data for EMD processing decrease dramatically.BA is introduced to optimize parameters of the SVM model for further improving the forecasting accuracy.Using the decomposed load series via empirical model decomposition(EMD)as inputs to SVM and further correcting the output of SVM via KF,a hybrid FCW-EMD and KF-BA-SVM short-term load forecasting method is established.Numerical case studies on the load forecasting of a transformer substation in south China show that the proposed hybrid forecasting model outperforms other forecasting methods and effectively improves the prediction accuracy.

Model construction for field operation machinery selection and configuration in wheat-maize double cropping system

In order to scientifically and reasonably select the field operation machinery in the wheat-maize double cropping system,first,the selection evaluation index system was constructed through the existing national standards and industry standards.Then the selection evaluation model was established based on the improved fuzzy comprehensive evaluation method.And the method of subjective weight and objective weight was used to overcome the drawbacks of the previous single weighting method that could not take into account the subject and object information of each indicator,and the weight value of each index was obtained in the evaluation system.Finally,the tillage process was used as an example,the field experiment was carried out to obtain the evaluation index value,and the model of selection evaluation was verified.The selection results of moldboard plough and rotary cultivator were as follows:the order of the comprehensive evaluation results of the moldboard plough results was ranked from high to low as 1LFK-435(IIM),1LFK-535(IM),1LF-342(IIIM),1LFT-445(IVM),1LFT-545(VM),and the best machine type of the moldboard plough was IIM;the order of the comprehensive evaluation results of the rotary cultivator was ranked from high to low as 1GQKGN-240(IIIR),1GKNSM-250(IVR),1GKN-230K(IR),1GKN-250K(IIR),1GQKGN-220(VR),and the optimal model of the rotary cultivator was IIIR.The experimental results showed that the results obtained by the evaluation model were in agreement with the local actual situation.The evaluation model will provide a scientific method for the selection of wheat and maize double cropping field operation machinery.