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.

Econometric Analysis of Research Papers on the Project of " Turning Vulnerable Farmland into Forests "

Taking the Database of Chinese Scientific and Technical Periodicals of Chongqing VIP Information Co. ,Ltd. as the statistical analysis source,we analyze the inter-annual trends,the authors institutions,journals distribution,disciplines distribution,paper subjects and authors' cooperation of research papers on the project of " turning vulnerable farmland into forests" in China during the period 1999 -2010,using the bibliometric method. The results show that during the period 1999 -2010,the research on the project of " turning vulnerable farmland into forests" always captured the attention of academia,and the number of research papers annually averaged more than 300; the relevant forestry functional departments at all levels,forestry-related research institutions and universities have paid close attention to the project of " turning vulnerable farmland into forests" in China; the group of core journals researched is concentrated in journals concerning forestry; in addition to forestry and agriculture,the research areas also touch upon economics,environment and other disciplines; the emphasis and hot spot of research are centered on applications, with few basic researches.

Winter Wheat Yield Estimation Based on Sparrow Search Algorithm Combined with Random Forest:A Case Study in Henan Province,China

Precise and timely prediction of crop yields is crucial for food security and the development of agricultural policies.However,crop yield is influenced by multiple factors within complex growth environments.Previous research has paid relatively little attention to the interference of environmental factors and drought on the growth of winter wheat.Therefore,there is an urgent need for more effective methods to explore the inherent relationship between these factors and crop yield,making precise yield prediction increasingly important.This study was based on four type of indicators including meteorological,crop growth status,environmental,and drought index,from October 2003 to June 2019 in Henan Province as the basic data for predicting winter wheat yield.Using the sparrow search al-gorithm combined with random forest(SSA-RF)under different input indicators,accuracy of winter wheat yield estimation was calcu-lated.The estimation accuracy of SSA-RF was compared with partial least squares regression(PLSR),extreme gradient boosting(XG-Boost),and random forest(RF)models.Finally,the determined optimal yield estimation method was used to predict winter wheat yield in three typical years.Following are the findings:1)the SSA-RF demonstrates superior performance in estimating winter wheat yield compared to other algorithms.The best yield estimation method is achieved by four types indicators’composition with SSA-RF)(R^(2)=0.805,RRMSE=9.9%.2)Crops growth status and environmental indicators play significant roles in wheat yield estimation,accounting for 46%and 22%of the yield importance among all indicators,respectively.3)Selecting indicators from October to April of the follow-ing year yielded the highest accuracy in winter wheat yield estimation,with an R^(2)of 0.826 and an RMSE of 9.0%.Yield estimates can be completed two months before the winter wheat harvest in June.4)The predicted performance will be slightly affected by severe drought.Compared with severe drought year(2011)(R^(2)=0.680)and normal year(2017)(R^(2)=0.790),the SSA-RF model has higher prediction accuracy for wet year(2018)(R^(2)=0.820).This study could provide an innovative approach for remote sensing estimation of winter wheat yield.yield.

Predicting Surface Urban Heat Island in Meihekou City, China: A Combination Method of Monte Carlo and Random Forest

Given the rapid urbanization worldwide, Urban Heat Island(UHI) effect has been a severe issue limiting urban sustainability in both large and small cities. In order to study the spatial pattern of Surface urban heat island(SUHI) in China’s Meihekou City, a combination method of Monte Carlo and Random Forest Regression(MC-RFR) is developed to construct the relationship between landscape pattern indices and Land Surface Temperature(LST). In this method, Monte Carlo acceptance-rejection sampling was added to the bootstrap layer of RFR to ensure the sensitivity of RFR to outliners of SUHI effect. The SHUI in 2030 was predicted by using this MC-RFR and the modeled future landscape pattern by Cellular Automata and Markov combination model(CA-Markov). Results reveal that forestland can greatly alleviate the impact of SUHI effect, while reasonable construction of urban land can also slow down the rising trend of SUHI. MC-RFR performs better for characterizing the relationship between landscape pattern and LST than single RFR or Linear Regression model. By 2030, the overall SUHI effect of Meihekou will be greatly enhanced, and the center of urban development will gradually shift to the central and western regions of the city. We suggest that urban designer and managers should concentrate vegetation and disperse built-up land to weaken the SUHI in the construction of new urban areas for its sustainability.

Analyzing the Relation between Greek Paper and Paperboard Imports and Exports with Macroeconomic Variables

This paper describes the relation between Greek imports and exports of paper and paperboard and a number of major macroeconomic variables, such as population, gross domestic product, the industrial production index and domestic round wood production. The Pearson correlation coefficient and multiple regression analysis were employed in the analysis of the data. The study shows that there is no significant relation between paper and paperboard imports as a dependent variable and population, gross domestic product and domestic round wood production as independent variables. Despite this, an acceptable model is constructed using only gross domestic product as an independent variable. The study also shows that there is a significant relation between the export of paper and paperboard and gross domestic product, the industrial production index and round wood production. The results indicate that gross domestic product as an independent variable has the greatest effect on wood imports and exports in Greece during the period studied. Using these models is confirmed that the use of socioeconomic variables and the construction of future scenarios for the Greek forest sector is very efficient considering the special characteristics of the Greek economy. These models could help the establishment of economic growth, the reduction of the financial and ecological deficit, the implementation of economic reforms and to increase new investments.

基于Random Forest和AHP的贵德县北部山区滑坡危险性评价

滑坡危险性评价是滑坡灾害防治和管理的重要依据。文章基于层次分析法和随机森林模型,结合距离函数法,探索性地提出了一种新的组合赋权法(RF-AHP)。采用RF-AHP对青海省贵德县北部山区滑坡进行了危险性评价,对比探讨了AHP、RF和RF-AHP三种模型评价结果与实际滑坡灾害的吻合性,结果表明:(1)RF-AHP在高危险区和极高危险区面积占比38.38%的情况下,包括了60.13%的滑坡灾害,结果准确性相比AHP和RF两种模型有较大提升;(2)随着危险性等级的逐步提高,RF-AHP区划结果中相应分区的灾害实际发生的比率也随之增高,并对三种方法出现结果差异的客观原因进行了分析讨论,证明RF-AHP适用于滑坡危险性评价工作。

Combined transplantation of GDAs^(BMP) and hr-decorin in spinal cord contusion repair

Following spinal cord injury, astrocyte proliferation and scar formation are the main factors inhibiting the regeneration and growth of spinal cord axons. Recombinant decorin suppresses inflammatory reactions, inhibits glial scar formation, and promotes axonal growth. Rat models of T8 spinal cord contusion were created with the NYU impactor and these models were subjected to combined transplantation of bone morphogenetic protein-4-induced glial-restricted precursor-derived astro- cytes and human recombinant decorin transplantation. At 28 days after spinal cord contusion, dou- ble-immunofluorescent histochemistry revealed that combined transplantation inhibited the early in- flammatory response in injured rats. Furthermore, brain-derived neurotrophic factor, which was se- creted by transplanted cells, protected injured axons. The combined transplantation promoted ax- onal regeneration and growth of injured motor and sensory neurons by inhibiting astrocyte prolif- eration and glial scar formation, with astrocytes forming a linear arrangement in the contused spinal cord, thus providing axonal regeneration channels.

Market analysis for timber and forest products in China

This paper introduces the general condition of forestry resources of China and the demand and supply of timber and forest products. The market for timber and forest producls has borne dual pressure because of the population explosion and growth of the domestic economy. A major contemporary strategy for sustainable forestry includes the promotion of the Forest Products Industry (FPI), the substitution of other materials for timber,and the encouragement of imports of timber and forest products. The author analyzes the effect of these policies on the market for timber and forest products. In addition, the difficulties encountered by most mid-to large -scale state- owned forest enterprises during the transition from a centrally-planned economy to a market economy are examined. Finally, the author points out the countermeasures and means for reform of these old forest enterprises with a view toward future prosperity of the market for timber and forest products.

Surface Partial Discharge Characteristics of Oil-paper Insulation Under Combined AC-DC Voltage

The valve side windings of converter transformers bear AC, DC, impulse, and reversal-polarity voltages during operation, which could result in serious insulation problems of the equipment. By performing experiments with surface discharge model of oil-paper insula- tion at 80 ℃ under combined AC-DC voltage for 200 h, we studied the spectrums and statistical parameters of partial discharges at different discharge stages. Furthermore, some fingerprint parameters were calculated in order to estimate the development situation of par- tial discharge, while the characteristic gases dissolved in the transformer oil were measured by gas chromatography. The surface discharges in the experiments were observed using a high speed camera, and a full discharge process could be marked off into four stages as follows. ①The elementary stage. When a partial discharge occurs near electrodes, electrical charges are injected into the region near electrodes and causing bubble generation. ②Due to their high resistivity and low dielectric constant, the bubbles would bare the major part of the voltage applied to samples. Therefore, discharge happens inside the small bubbles, and it emits a lot of light. ③Micromolecules of gas are produced in discharge, and further ionization in the transformer oil takes place simultaneously when high-energy electrons collide with oil molecules. ④The carrier charge moves forward to electrodes driven by the applied electric field, till they neutralize with the charge from electrodes, and hence discharge channels are formed subsequently.

Research on Dynamic Forecast of Flowering Period Based on Multivariable LSTM and Ensemble Learning Classification Task

The flowering forecast provides recommendations for orchard cleaning, pest control, field management and fertilization, which can help increase tree vigor and resistance. Flowering forecast is not only an important part of the construction of agro-meteorological index system, but also an important part of the meteorological service system. In this paper, by analyzing local meteorological data and phenological data of “Red Fuji” apples in Fen County, Linfen City, Shanxi Province, with the help of machine learning and neural networks, we proposed a method based on the combination of time series forecasting and classification forecasting is proposed to complete the dynamic forecasting model of local flowering in Ji County. Then, we evaluated the effectiveness of the model based on the number of error days and the number of days in advance. The implementation shows that the proposed multivariable LSTM network has a good effect on the prediction of meteorological factors. The model loss is less than 0.2. In the two-category task of flowering judgment, the idea of combining strategies in ensemble learning improves the effect of flowering judgment, and its AUC value increases from 0.81 and 0.80 of single model RF and AdaBoost to 0.82. The proposed model has high applicability and accuracy for flowering forecast. At the same time, the model solves the problem of rounding decimals in the prediction of flowering dates by the regression method.

中国造纸业绿色战略演进历程

中国造纸业绿色战略的实践从萌芽期算起已经走过了60年艰难而富有成效的发展历程。在当今国家生态文明建设和实现双碳目标的背景下,对中国造纸业绿色发展过程进行回顾和总结,挖掘绿色战略的演进规律,并预估未来的战略趋势是十分必要的。根据绿色经济和绿色战略理论,以及可再生资源型企业绿色战略演进的一般规律,本文对中国造纸业绿色战略实践的重要事件和举措进行系统梳理,发现中国造纸业绿色战略总体上经历了开环和闭环绿色战略两大阶段。其中,开环绿色战略阶段包含原料导向(林纸一体化)绿色战略和末端治理绿色战略;闭环绿色战略阶段包含循环绿色战略和“循环+”绿色战略。据此,运用超循环经济理论,可以预计中国造纸业绿色战略的未来发展趋势,即林纸超循环绿色战略。

绒毛皂荚特定森林环境育苗技术组合与常规育苗对比试验

[目的]提高绒毛皂荚场地发芽率,加速种群回归。[方法]在特定的森林环境进行育苗技术组合试验,并以苗圃常规育苗为对照,研究不破坏林地环境的小铲破土和地表播种+死地被物多种覆盖方式技术组合对发芽率与苗木生长的影响。[结果]小铲破土播种或地表播种加4种不同死地被物覆盖方式技术组合的场地发芽率分别为(A_(1))61.67%、(A_(2))55.56%、(A_(3))61.11%、(A_(4))57.22%,均高于常规育苗(CK)的35.03%;A_(1)小铲破土播种后,盖1 cm厚表层有机土+3 cm厚粗腐殖质+未分解的枯枝落叶组合和A_(3)种子直播土壤地表后,盖3 cm厚的粗腐殖质+未分解枯枝落叶同为最佳组合;常规育苗的苗木成苗率(成苗数与发芽数之比×100%)与苗木生长量略高于其他处理;但从成苗数的绝对数比较,CK小于A_(1)、A_(2)、A_(3)、A_(4)处理的106、85、95和88株。[结论]特定的森林环境母树下小铲破土或地表播种后+林地死地被物覆盖组合育苗是提高场地发芽率和成苗数的有效方法。

“双碳”背景下林纸供应链利益分配影响因素分析

“双碳”背景下林纸供应链的创新发展,与“降碳、减污、扩绿、增长”等领域发展息息相关。企业在林纸供应链内追逐更高的利益是其参与合作的重要动力源,必须合理配置整体收益,才能充分调动企业参与林纸供应链的积极性。每个企业为林纸供应链发展做出的贡献不同,在利益分配过程中,应充分考虑各个企业的核心竞争能力、主观努力水平和客观贡献程度、生态绩效贡献以及风险承担强度等影响因素,合理分配林纸供应链参与企业间利益,从而保障林纸供应链参与企业间稳定长久的合作关系。

基于三维足迹家族模型的资源环境可持续性评价

为探讨资源环境可持续评价研究的重要性,通过建立以生态足迹、水足迹与碳足迹为基本成员的足迹家族模型,引入多个资源环境压力指标,并基于DPSIR框架,运用综合集成法分析确立资源环境可持续性评价指标体系,由随机森林法与层次分析法确定各项指标的组合权重,运用模糊综合评价法分析区域资源环境压力状况与可持续性状况,进而开展了基于三维足迹家族模型的南京市资源环境可持续评价研究。结果表明,2012~2021年南京市水土资源均有占用存量资本,但占用情况整体呈下降趋势,碳足迹处于低压力范围,资源环境可持续性逐年向好;2012~2019年南京市资源环境可持续状况为弱可持续,2020~2021年为强可持续。

“双碳”背景下林纸绿色供应链利益分配优化模型及应用研究

在“双碳”发展背景下,考虑核心竞争能力、主观投入水平、客观贡献程度、生态绩效贡献度、风险承担强度等影响因素,构建优化夏普利值法模型,应用算例并结果分析,从研究结果可知,在林纸绿色供应链发展及利益分配过程中,首先要认识到影响因素对林纸绿色供应链的发展及利益分配的重要性。其次,要始终将绿色化贯穿林纸绿色供应链整个发展过程,充分体现林纸绿色供应链发展与“双碳”发展的目标一致性。

环境因子组合和负样本选取策略对花岗岩区崩岗易发性评价的影响

不同环境因子组合和负样本选取策略对崩岗易发性评价结果存在较多不确定性。为探究其对评价结果的影响,该研究以江西省兴国县花岗岩区为例,利用地理探测器探测17个环境因子的统计量q值,根据累计q值百分比大小依次选择4、7、10和17个环境因子进行组合;利用单随机欠采样、频率比法及改进频率比法等负样本选取策略构建与正样本等量的负样本数据集;采用随机森林模型进行易发性评价,并对评价结果进行对比分析。结果表明:1)3种负样本选取策略下的模型精度随着因子数量的增加先下降再上升,考虑4个环境因子的模型AUC(area under curve)值分别为0.729、0.909和0.909,较最优环境因子组合仅相差0.020~0.038,说明考虑主控环境因子,即可得到较为理想的精度;2)通过频率比法选取的负样本数据集更具合理性;3)研究区内高和极高易发区主要分布在兴国县西南部,而极低易发区主要分布在兴国县北部及东部,这与实际情况较吻合。该研究通过探究不同环境因子组合和负样本选取策略对崩岗易发性评价的影响,可为花岗岩区崩岗的防灾减灾提供科学依据。

PBL、CBL联合Paper Review教学模式在甲状腺外科规培医师教学中的应用

目的:探索PBL、CBL联合Paper Review在甲状腺外科规范化培训中的应用效果。方法:教学对象随机分为实验组(PBL、CBL联合Paper Review)和对照组(传统LBL)。比较两组学员出科成绩、临床能力及满意度测评。结果:实验组出科成绩、临床能力及教学满意度明显高于对照组(P<0.05);结论:PBL、CBL联合Paper Review能有效提高教学质量和学员的临床能力。

基于多特征组合的建筑垃圾分类方法

城市的快速发展产生大量建筑垃圾,引发了城市污染,产生“垃圾围城”现象。本文以北京市某区域为研究区域,研究多特征组合方法对高光谱影像的建筑垃圾分类精度的作用,并利用ASD QualitySpecTrek手持式光谱仪实地测量的光谱数据和珠海一号高光谱影像进行建筑垃圾分类试验;提取了光谱特征、植被指数、水体指数和纹理特征等90种特征变量,利用平均不纯度减少的方法对其进行特征重要性排序,选取其中重要性综合结果相对较高的特征变量构成分类多特征组合向量,利用随机森林算法对多特征组合向量进行建筑垃圾分类。试验结果表明,采用多特征组合的随机森林分类方法比传统的随机森林方法效果更好,总体分类精度达85.86%,Kappa系数为0.80,而原始的随机森林方法总体分类精度仅有83.48%,Kappa系数为0.75,这表明了多特征组合随机森林算法的有效性。