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基于Delphi Method和Factor Analysis构造粤港澳大学生信用评价体系 认领 引用
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作者 陈家辉 叶萌芳 +2 位作者 祁志峰 虞思静 尹佩贤 《价值工程》 2026年第16期40-43,共4页
随着互联网消费金融市场在我国逐年的扩张,大学生参与消费金融的人数和分期交易额均呈现爆发式增长。对于大学生的金融需求由于大学生群体信用评级体系不完善,造成群体从传统金融渠道获得融资的门槛高,流程复杂,合理金融需求无法被满足... 随着互联网消费金融市场在我国逐年的扩张,大学生参与消费金融的人数和分期交易额均呈现爆发式增长。对于大学生的金融需求由于大学生群体信用评级体系不完善,造成群体从传统金融渠道获得融资的门槛高,流程复杂,合理金融需求无法被满足,同时,借款申请信息没有共享,导致多头借贷行为始终难以杜绝,给非法校园金融产品留下“野蛮生长”空间。因此,本文基于Delphi Method和Factor Analysis,形成“专家预设-实证优化”的闭环验证机制筛选指标并构建粤港澳大学生信用体系,打造多维度信用评价网络,为大湾区大学生信用体系建设的差异化、特色化方向发展提供新的思路及借鉴。 展开更多
关键词 信用评价 信用指标 大学生信用 Delphi Method Factor Analysis
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Factor analysis and machine learning for predicting endpoint carbon content in converter steelmaking 认领 引用 被引量：3
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作者 Lihua Zhao Shuai Yang +3 位作者 Yongzhao Xu Zhongliang Wang Xin Liu Yanping Bao 《International Journal of Minerals,Metallurgy and Materials》 SCIE EI CAS CSCD 2025年第10期2469-2482,共14页
The endpoint carbon content in the converter is critical for the quality of steel products,and accurately predicting this parameter is an effective way to reduce alloy consumption and improve smelting efficiency.Howev... The endpoint carbon content in the converter is critical for the quality of steel products,and accurately predicting this parameter is an effective way to reduce alloy consumption and improve smelting efficiency.However,most scholars currently focus on modifying methods to enhance model accuracy,while overlooking the extent to which input parameters influence accuracy.To address this issue,in this study,a prediction model for the endpoint carbon content in the converter was developed using factor analysis(FA)and support vector machine(SVM)optimized by improved particle swarm optimization(IPSO).Analysis of the factors influencing the endpoint carbon content during the converter smelting process led to the identification of 21 input parameters.Subsequently,FA was used to reduce the dimensionality of the data and applied to the prediction model.The results demonstrate that the performance of the FA-IPSO-SVM model surpasses several existing methods,such as twin support vector regression and support vector machine.The model achieves hit rates of 89.59%,96.21%,and 98.74%within error ranges of±0.01%,±0.015%,and±0.02%,respectively.Finally,based on the prediction results obtained by sequentially removing input parameters,the parameters were classified into high influence(5%-7%),medium influence(2%-5%),and low influence(0-2%)categories according to their varying degrees of impact on prediction accuracy.This classi-fication provides a reference for selecting input parameters in future prediction models for endpoint carbon content. 展开更多
关键词 converter endpoint carbon content parameter classification factor analysis improved particle swarm optimization support vector machine
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WPPSI-III in Sudan:Validity,reliability,and confirmatory factor analysis in khartoum kindergarten and primary schools 认领 引用
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作者 Rwaa Omer Ali Ahmed Salaheldin Farah Attallah Bakhiet +2 位作者 Ayman Mohamed Taha Abdelaziz Ahmed FadlAlMawla AbdulRadi Ismael Salamah Albursan 《Journal of Psychology in Africa》 2025年第4期431-439,共9页
The study aims to determine the validity and reliability of the Wechsler Preschool and Primary Scale of Intelligence–Third Edition(WPPSI-III)scores in a sample of kindergarten and lower primary pupils from Khartoum S... The study aims to determine the validity and reliability of the Wechsler Preschool and Primary Scale of Intelligence–Third Edition(WPPSI-III)scores in a sample of kindergarten and lower primary pupils from Khartoum State,Sudan.It also aims to examine whether test’s factor structure in this sample replicated that of the original WPPSI-III.The study sample consisted of 384 kindergarten and primary school children in Khartoum State(females=50%mean age=4.14,SD=1.37),selected using stratified random sampling across its seven localities:Khartoum,Jebel Awliya,Khartoum Bahri,East Nile,Omdurman,Ombada,Karari.For concurrent validation,the children additionally completed the Goodenough Draw-a-Man Test,and the Colored Progressive Matrices.WPPSI-III scores demonstrated high internal consistency across the subtest items.Confirmatory factor analysis indicators for total,verbal,and performance intelligence were all excellent.The scale also showed weak to strong score stability ranging from 0.25(weak)to 0.88(strong)based on the Spearman-Brown equation,0.25 to 0.75 based on the Guttman split-half method.The Cronbach’s alpha coefficient scores ranged from 0.54 to 0.93.The WPPSI-III and Goodenough Draw-a-Man Test scores concurrent validity scores were poor(0.05)to modest(0.31),and while those with the Colored Progressive Matrices test were poor(r=0.04–0.18).Thesefindings provide evidence to suggest that the WPPSI-III is appropriate for research use with kindergarten and lower primary school students in Khartoum State,Sudan. 展开更多
关键词 intelligence tests validation reliability primary schools kindergartens confirmatory factor analysis cognitive abilities WPPSI-III Sudan
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Nursing interventions’impact on cardiovascular complications after gastrointestinal surgery in intensive care unit:Risk factor analysis 认领 引用
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作者 Ling Wang Peng Yang +1 位作者 Xue-Qing He Han Xia 《World Journal of Gastrointestinal Surgery》 SCIE 2025年第8期133-141,共9页
BACKGROUND Cardiovascular(CV)complications are common in intensive care unit(ICU)patients after gastrointestinal surgery and are associated with increased mortality and prolonged hospital stay.The optimization of post... BACKGROUND Cardiovascular(CV)complications are common in intensive care unit(ICU)patients after gastrointestinal surgery and are associated with increased mortality and prolonged hospital stay.The optimization of postoperative nursing interventions,particularly pain management,is crucial for reducing such complications.AIM To investigate the effects of enhanced recovery nursing on CV complications after gastrointestinal surgery in ICU patients and associated risk factors.METHODS A retrospective analysis was conducted on 78 adult patients who underwent gastrointestinal surgery in the ICU of our hospital between February 2023 and September 2024.Among them,40 patients received standard care(control group),while 38 received enhanced recovery nursing(observation group).We compared the incidence of CV complications and nursing satisfaction between the two groups.Patients were divided into CV complication and non-complication groups based on complication occurrence,and logistic regression analysis was used to identify risk factors.RESULTS In the control and observation groups,the incidence of CV complications was 30.0%(12/40)and 18.4%(7/38),with a nursing satisfaction rate of 70.0%(28/40)and 92.1%(35/38),respectively.The postoperative pain score at 14 days was significantly lower in the observation group(0.27±0.15)compared to the control group(1.65±0.37),with all differences being statistically significant(P<0.05).Univariate analysis indicated significant differences in age,body mass index,hypertension,diabetes,smoking history,history of heart failure,and previous myocardial infarction(P<0.05).Multivariate logistic regression identified heart failure history,previous myocardial infarction,age,hypertension,and diabetes as independent risk factors,with odds ratios of 1.195,1.528,1.062,1.836,and 1.942,respectively(all P<0.05).CONCLUSION Implementing enhanced recovery nursing for ICU patients after gastrointestinal surgery is beneficial in reducing the incidence of CV complications and improving nursing satisfaction. 展开更多
关键词 Enhanced recovery nursing interventions Intensive care unit Gastrointestinal surgery Cardiovascular complications Risk factor analysis
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A Proportional Integral Controller-Enhanced Non-Negative Latent Factor Analysis Model 认领 引用
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作者 Ye Yuan Siyang Lu Xin Luo 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2025年第6期1246-1259,共14页
A non-negative latent factor(NLF)model is able to be built efficiently via a single latent factor-dependent,non-negative and multiplicative update(SLF-NMU)algorithm for performing precise representation to high-dimens... A non-negative latent factor(NLF)model is able to be built efficiently via a single latent factor-dependent,non-negative and multiplicative update(SLF-NMU)algorithm for performing precise representation to high-dimensional and incomplete(HDI)matrix from many kinds of big-data-related applications.However,an SLF-NMU algorithm updates a latent factor relying on the current update increment only without considering past learning information,making a resultant model suffer from slow convergence.To address this issue,this study proposes a proportional integral(PI)controller-enhanced NLF(PI-NLF)model with two-fold ideas:1)Designing an increment refinement(IR)mechanism,which formulates the current and past update increments as the proportional and integral terms of a PI controller,thereby assimilating the past update information into the learning scheme smoothly with high efficiency;2)Deriving an IR-based SLF-NMU(ISN)algorithm,which updates a latent factor following the principle of an IR mechanism,thus significantly accelerating an NLF model's convergence rate.The simulation results on eight HDI matrices collected by real applications validate that a PI-NLF model outstrips several leading-edge models in both computational efficiency and accuracy when estimating missing data within an HDI matrix.The proposed PI-NLF model can be effectively applied to applications involving HDI matrix like e-commerce system,social network,and cloud service system.The code is available at http://gffzz188fe103f8f1460asqkpuxpv06uqv6xxc.ffgz.tsg.suse.edu.cn/yuanyeswu/PINLF/blob/mainIPINLF-code.zip. 展开更多
关键词 High-dimensional and incomplete(HDI)data learning algorithm non-negative latent factor(NLF)analysis proportional integral(PI)controller
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Research on the Construction of an Evaluation System for Innovation and Entrepreneurship Capabilities of Normal University Students Based on Factor Analysis Method 认领 引用
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作者 Fang Liu Chi Li Lihua Jia 《Journal of Contemporary Educational Research》 2025年第8期320-327,共8页
Under the National Innovation-Driven Development Strategy,establishing a scientifically sound evaluation system for normal university students’innovation and entrepreneurship capabilities serves as a crucial foundati... Under the National Innovation-Driven Development Strategy,establishing a scientifically sound evaluation system for normal university students’innovation and entrepreneurship capabilities serves as a crucial foundation for optimizing innovation education models and enhancing teacher candidates’comprehensive competencies.Based on existing indicator frameworks,we designed a questionnaire and applied exploratory factor analysis(EFA)to screen indicators,reduce dimensionality,and analyze weighting.This process identified key metrics for evaluating pedagogical students’innovation capacities,ultimately constructing a targeted assessment system for normal university students.The study provides theoretical support for cultivating teacher trainees’innovative capabilities while contributing to the national innovation strategy implementation. 展开更多
关键词 Factor analysis Innovation and entrepreneurship capability Indicator system Evaluation system Universities Normal university students
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Characterization of dissolved organic matter in urban sewage using excitation emission matrix fluorescence spectroscopy and parallel factor analysis 认领 引用 被引量：48
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作者 Weidong Guo Jing Xu +3 位作者 Jiangping Wang Yingrou Wen Jianfu Zhuo Yuchao Yan 《Journal of Environmental Sciences》 SCIE EI CAS 2010年第11期1728-1734,共7页
Wastewater dissolved organic matter （DOM） from different processing stages of a sewage treatment plant in Xiamen was characterized using fluorescence and absorption spectroscopy. Parallel factor analysis modeling of... Wastewater dissolved organic matter （DOM） from different processing stages of a sewage treatment plant in Xiamen was characterized using fluorescence and absorption spectroscopy. Parallel factor analysis modeling of excitation-emission matrix spectra revealed five fluorescent components occurring in sewage DOM： one protein-like （C1）, three humic-like （C2, C4 and C5） and one xenobiotic-like （C3） components. During the aerated grit chamber and primary sedimentation tank stage, there was only a slight decrease in fluorescence intensity and the absorption coefficient at 350 nm （a 350 ）. During the second aeration stage, high concentration of protein-like and short-wavelength-excited humic-like components were significantly degraded accompanied by significant loss of DOC （80%） and a 350 （30%）, indicating that C1 and C2 were the dominant constituents of sewage DOM. As a result, long-wavelength- excited C4 and C5 became the dominant humic-like components and the DOM molecular size inferred from the variation of spectral slope S （300–650 nm） and specific absorption （a 280 /DOC） increased. Combination use of F max of C1 and the ratio of C1/C5, or a 350 may provide a quantitative indication for the relative amount of raw or treated sewage in aquatic environment. 展开更多
关键词 dissolved organic matter sewage fluorescence EEM parallel factor analysis
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Factor analysis identifies subgroups of constipation 认领 引用 被引量：3
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作者 Philip G Dinning Mike Jones +6 位作者 Linda Hunt Sergio E Fuentealba Jamshid Kalanter Denis W King David Z Lubowski Nicholas J Talley Ian J Cook 《World Journal of Gastroenterology》 SCIE CAS CSCD 2011年第11期1468-1474,共7页
AIM:To determine whether distinct symptom groupings exist in a constipated population and whether such grouping might correlate with quantifiable pathophysiological measures of colonic dysfunction.METHODS:One hundred ... AIM:To determine whether distinct symptom groupings exist in a constipated population and whether such grouping might correlate with quantifiable pathophysiological measures of colonic dysfunction.METHODS:One hundred and ninety-one patients presenting to a Gastroenterology clinic with constipation and 32 constipated patients responding to a newspaper advertisement completed a 53-item,wide-ranging selfreport questionnaire.One hundred of these patients had colonic transit measured scintigraphically.Factor analysis determined whether constipation-related symptoms grouped into distinct aspects of symptomatology.Cluster analysis was used to determine whether indi-vidual patients naturally group into distinct subtypes.RESULTS:Cluster analysis yielded a 4 cluster solution with the presence or absence of pain and laxative unresponsiveness providing the main descriptors.Amongst all clusters there was a considerable proportion of patients with demonstrable delayed colon transit,irritable bowel syndrome positive criteria and regular stool frequency.The majority of patients with these characteristics also reported regular laxative use.CONCLUSION:Factor analysis identified four constipation subgroups,based on severity and laxative unresponsiveness,in a constipated population.However,clear stratification into clinically identifiable groups remains imprecise. 展开更多
关键词 Factor analysis Constipation Symptoms Clusters Laxatives
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Measuring speed consistency for freeway diverge areas using factor analysis 认领 引用 被引量：4
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作者 曲栩 郭唐仪 +1 位作者 王炜 胡启洲 《Journal of Central South University》 SCIE EI CAS 2013年第1期267-273,共7页
Although either absolute speed or speed difference can be considered as a measure for speed consistency, few researches consider both in practice. The factor analysis method was introduced to extract an optimal number... Although either absolute speed or speed difference can be considered as a measure for speed consistency, few researches consider both in practice. The factor analysis method was introduced to extract an optimal number of factors from numerous original measures. The freeway diverging zone was divided into four elements, namely the upstream, the diverge area, the downstream and the exit ramp. Operating speeds together with individual vehicle speeds were collected at each element with radar guns. Following the factor analysis procedure, two factors, which explain 96.722% of the variance in the original data, were retained from the initial seven speed measures. According to the loadings after Varimax rotation, the two factors are clearly classified into two categories. The first category is named "speed scale" reflecting the absolute speed, and the other one is named "speed dispersion" interpreting speed discreteness. Then, the weighted score of speed consistency for each diverge area is given in terms of linear combination of the two retained factors. To facilitate the level classification of speed consistency, the weighted scores are normalized in the range of (0, 1.0). The criterion for speed consistency classification is given as 0≤F N <0.30, good consistency; 0.30≤F N <0.60, fair consistency; 0.60≤ F N ≤1.00, poor consistency. The validation by comparing with previously developed measures shows that the proposed measure is acceptable in evaluating speed consistency. 展开更多
关键词 safety freeway speed consistency factor analysis
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Rutting influencing factors and prediction model for asphalt pavements based on the factor analysis method 认领 引用 被引量：8
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作者 Liu Gang Chen Leilei +1 位作者 Qian Zhendong Zhou Xiayang 《Journal of Southeast University(English Edition)》 EI CAS 2021年第4期421-428,共8页
To clarify the importance of various influencing factors on asphalt pavement rutting deformation and determine a screening method of model indicators,the data of the RIOHTrack full-scale track were examined using the ... To clarify the importance of various influencing factors on asphalt pavement rutting deformation and determine a screening method of model indicators,the data of the RIOHTrack full-scale track were examined using the factor analysis method(FAM).Taking the standard test pavement structure of RIOHTrack as an example,four rutting influencing factors from different aspects were determined through statistical analysis.Furthermore,the common influencing factors among the rutting influencing factors were studied based on FAM.Results show that the common factor can well characterize accumulative ESALs,center-point deflection,and temperature,besides humidity,which indicates that these three influencing factors can have an important impact on rutting.Moreover,an empirical rutting prediction model was established based on the selected influencing factors,which proved to exhibit high prediction accuracy.These analysis results demonstrate that the FAM is an effective screening method for rutting prediction model indicators,which provides a reference for the selection of independent model indicators in other rutting prediction model research when used in other areas and is of great significance for the prediction and control of rutting distress. 展开更多
关键词 asphalt pavement rutting prediction influencing factors RIOHTrack full-scale track factor analysis method
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Modifying the Autism Spectrum Rating Scale(6–18 years)to a Chinese Context:An Exploratory Factor Analysis 认领 引用 被引量：11
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作者 Hao Zhou Lili Zhang +10 位作者 Xuerong Luo Lijie Wu Xiaobing Zou Kun Xia Yimin Wang Xiu Xu Xiaoling Ge Yong-Hui Jiang Eric Fombonne Weili Yan Yi Wang 《Neuroscience Bulletin》 SCIE CAS CSCD 2017年第2期175-182,共8页
The purpose of this study was to explore the psychometric properties of the Chinese version of the autism spectrum rating scale（ASRS）. We recruited 1,625community-based children and 211 autism spectrum disorder（ASD... The purpose of this study was to explore the psychometric properties of the Chinese version of the autism spectrum rating scale（ASRS）. We recruited 1,625community-based children and 211 autism spectrum disorder（ASD） cases from 4 sites, and the parents of all participants completed the Chinese version of the ASRS. A robust weighted least squares means and variance adjusted estimator was used for exploratory factor analysis. The3-factor structure included 59 items suitable for the current sample. The item reliability for the modi？ed Chinese version of the ASRS（MC-ASRS） was excellent. Moreover,with 60 as the cut-off point, receiver operating characteristic analysis showed that the MC-ASRS had excellent discriminate validity, comparable to that of the unmodi？ed Chinese version（UC-ASRS）, with area under the curve values of 0.952（95% CI： 0.936–0.967） and 0.948（95% CI：0.930–0.965）, respectively. Meanwhile, the con？rm factor analysis revealed that MC-ASRS had a better construct validity than UC-ASRS based on the above factor solution in another children sample. In conclusion, the MC-ASRS shows better ef？cacy in epidemiological screening for ASD in Chinese children. 展开更多
关键词 Autism spectrum disorder Screening Epidemiology Exploratory factor analysis Children
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Analysis of inhomogeneity of solidified microstructure of continuous casting copper tubular billet based on factor analysis 认领 引用 被引量：2
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作者 Jin-song Liu Chao-rui Shan +3 位作者 Da-yong Chen Hong-wu Song Chuan-lai Chen Yun-yue Chen 《China Foundry》 SCIE CAS CSCD 2023年第6期526-536,共11页
The horizontal continuous casting process,the initial step in TP2 copper tubular processing,directly determines the microstructure and properties of copper tubular.However,the process parameters of the continuous cast... The horizontal continuous casting process,the initial step in TP2 copper tubular processing,directly determines the microstructure and properties of copper tubular.However,the process parameters of the continuous casting characterize time variation,multiple disturbances and strong coupling.As a consequence,their influence on a casting billet is difficult to be determined.Due to the above issues,the common factor and special factor analysis of the factor analysis model were used in this study,and the casting experiment and billet metallographic experiment were carried out to diagnose and analyze the reason of the microstructure inhomogeneity.The multiple process parameters were studied and classified using common factor analysis,the cast billets with abnormal microstructures were identified by GT2 statistics,and the most important factors affecting the microstructural homogeneity were found by special factor analysis.The calculated and experimental results show that the principal parameters influencing the inhomogeneity of solidified microstructure are the primary inlet water pressure and the primary outlet water temperature.According to the consequence of the above investigation,the inhomogeneity of the copper billet microstructure can be effectively improved when the process parameters are controlled and adjusted. 展开更多
关键词 TP2 copper tubular billet horizontal continuous casting factor analysis microstructure inhomogeneity of casting billet quality diagnosis
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A State-Migration Particle Swarm Optimizer for Adaptive Latent Factor Analysis of High-Dimensional and Incomplete Data 认领 引用 被引量：2
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作者 Jiufang Chen Kechen Liu +4 位作者 Xin Luo Ye Yuan Khaled Sedraoui Yusuf Al-Turki MengChu Zhou 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2024年第11期2220-2235,共16页
High-dimensional and incomplete(HDI) matrices are primarily generated in all kinds of big-data-related practical applications. A latent factor analysis(LFA) model is capable of conducting efficient representation lear... High-dimensional and incomplete(HDI) matrices are primarily generated in all kinds of big-data-related practical applications. A latent factor analysis(LFA) model is capable of conducting efficient representation learning to an HDI matrix,whose hyper-parameter adaptation can be implemented through a particle swarm optimizer(PSO) to meet scalable requirements.However, conventional PSO is limited by its premature issues,which leads to the accuracy loss of a resultant LFA model. To address this thorny issue, this study merges the information of each particle's state migration into its evolution process following the principle of a generalized momentum method for improving its search ability, thereby building a state-migration particle swarm optimizer(SPSO), whose theoretical convergence is rigorously proved in this study. It is then incorporated into an LFA model for implementing efficient hyper-parameter adaptation without accuracy loss. Experiments on six HDI matrices indicate that an SPSO-incorporated LFA model outperforms state-of-the-art LFA models in terms of prediction accuracy for missing data of an HDI matrix with competitive computational efficiency.Hence, SPSO's use ensures efficient and reliable hyper-parameter adaptation in an LFA model, thus ensuring practicality and accurate representation learning for HDI matrices. 展开更多
关键词 Data science generalized momentum high-dimensional and incomplete(HDI)data hyper-parameter adaptation latent factor analysis(LFA) particle swarm optimization(PSO)
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Source Apportionment of Ambient PM10 in the Urban Area of Longyan City,China:a Comparative Study Based on Chemical Mass Balance Model and Factor Analysis Method 认领 引用 被引量：1
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作者 QIU Li-min LIU Miao +2 位作者 WANG Ju ZHANG Sheng-nan FANG Chun-sheng 《Chemical Research in Chinese Universities》 SCIE CAS CSCD 2012年第2期204-208,共5页
In order to identify the day and night pollution sources of PM10 in ambient air in Longyan City,the authors analyzed the elemental composition of respirable particulate matters in the day and night ambient air samples... In order to identify the day and night pollution sources of PM10 in ambient air in Longyan City,the authors analyzed the elemental composition of respirable particulate matters in the day and night ambient air samples and various pollution sources which were collected in January 2010 in Longyan with inductivity coupled plasma-mass spectrometry（ICP-MS）.Then chemical mass balance（CMB） model and factor analysis（FA） method were applied to comparatively study the inorganic components in the sources and receptor samples.The results of factor analysis show that the major sources were road dust,waste incineration and mixed sources which contained automobile exhaust,soil dust/secondary dust and coal dust during the daytime in Longyan City,China.There are two major sources of pollution which are soil dust and mixture sources of automobile exhaust and secondary dust during the night in Longyan.The results of CMB show that the major sources are secondary dust,automobile exhaust and road dust during the daytime in Longyan.The major sources are secondary dust,soil dust and automobile exhaust during the night in Longyan.The results of the two methods are similar to each other and the results will guide us to plan to control the PM10 pollution sources in Longyan. 展开更多
关键词 Factor analysis（FA） method Chemical mass balance（CMB） model Source apportionment Atmospheric particle PM10
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Modeling Indicator Systems for Evaluating Environmental Sustainable Development Based on Factor Analysis 认领 引用 被引量：1
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作者 WU Hao CHEN Xiaoling +3 位作者 HE Ying HE Xiaorong CAI Xiaobin XU Keya 《Wuhan University Journal of Natural Sciences》 EI CAS 2006年第4期997-1002,共6页
Indicator systems of environmental sustainable development in the Poyang Lake Basin are established from 51 elementary indexes by factor analysis, which is composed of four steps such as the factor model, the paramete... Indicator systems of environmental sustainable development in the Poyang Lake Basin are established from 51 elementary indexes by factor analysis, which is composed of four steps such as the factor model, the parameter estimation, the factor rotation and the factor score. Under the condition that the cumulative proportion is greater than 85%, 5 explicit factors of environmental sustainable development as well as its factor score by region are carried out. The result indicates some impact factors to the basin environmental in descending sort order are volume of water, volume of waste gas discharge,volume of solid wasters.the degree to comprehensive utilization of waste gas, waste water and solid wastes, the emission volume of waste gas, waste water and solid wastes. It is helpful and important to provide decision support for constituting sustainable development strategies and evaluate the sustainable development status of each city. 展开更多
关键词 factor analysis the Poyang Lake Basin environment evaluation sustainable development indicator systems
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Evaluation and classification of residential greenbelt quality based on factor analysis & clustering analysis:An example of Xinxiang City,China 认领 引用 被引量：1
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作者 乔丽芳 张毅川 齐安国 《Journal of Forestry Research》 CAS 2008年第4期311-314,共4页
Five factors expressing greenbelt quality and one factor expressing quantity were adopted for evaluation of the residential greenbelt, and the AHP （Analytical Hierarchy Process） method was used to determine the valu... Five factors expressing greenbelt quality and one factor expressing quantity were adopted for evaluation of the residential greenbelt, and the AHP （Analytical Hierarchy Process） method was used to determine the value of factors. Thirty residential areas were selected as the samples. Two principal components were extracted and their expression was constructed by method of factor anlysis, therefore, quality evaluation of residential greenbelt was obtained. The accuracy of the function and implement quality classification toward the residential greenbelts in Xinxiang City were validated by clustering analysis method. The results showed that the greenbelt quality of fourteen residential areas was higher than the average level, of which eleven were newly-built residential areas. The 30 residential areas were classified into three types according to their greenbelt features and their formation by clustering analysis method. Finally rational proposal basing on aforesaid evaluating results was proposed for construction and renewal of residential greenbelt, upon which directive basis was provided for construction and renewal of residential greenbelt. 展开更多
关键词 residential area greenbelt quality evaluation factor analysis clustering analysis
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Assessment of phytoplankton class abundance using fluorescence excitation-emission matrix by parallel factor analysis and nonnegative least squares 认领 引用
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作者 苏荣国 陈小娜 +2 位作者 吴珍珍 姚鹏 石晓勇 《Chinese Journal of Oceanology and Limnology》 CSCD 2015年第4期878-889,共12页
The feasibility of using fluorescence excitation-emission matrix(EEM) along with parallel factor analysis(PARAFAC) and nonnegative least squares(NNLS) method for the differentiation of phytoplankton taxonomic groups w... The feasibility of using fluorescence excitation-emission matrix(EEM) along with parallel factor analysis(PARAFAC) and nonnegative least squares(NNLS) method for the differentiation of phytoplankton taxonomic groups was investigated. Forty-one phytoplankton species belonging to 28 genera of five divisions were studied. First, the PARAFAC model was applied to EEMs, and 15 fluorescence components were generated. Second, 15 fluorescence components were found to have a strong discriminating capability based on Bayesian discriminant analysis(BDA). Third, all spectra of the fluorescence component compositions for the 41 phytoplankton species were spectrographically sorted into 61 reference spectra using hierarchical cluster analysis(HCA), and then, the reference spectra were used to establish a database. Finally, the phytoplankton taxonomic groups was differentiated by the reference spectra database using the NNLS method. The five phytoplankton groups were differentiated with the correct discrimination ratios(CDRs) of 100% for single-species samples at the division level. The CDRs for the mixtures were above 91% for the dominant phytoplankton species and above 73% for the subdominant phytoplankton species. Sixteen of the 85 field samples collected from the Changjiang River estuary were analyzed by both HPLC-CHEMTAX and the fluorometric technique developed. The results of both methods reveal that Bacillariophyta was the dominant algal group in these 16 samples and that the subdominant algal groups comprised Dinophyta, Chlorophyta and Cryptophyta. The differentiation results by the fluorometric technique were in good agreement with those from HPLC-CHEMTAX. The results indicate that the fluorometric technique could differentiate algal taxonomic groups accurately at the division level. 展开更多
关键词 fluorescence excitation-emission matrix parallel factor analysis nonnegative least squares phytoplankton fluorescence components
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Factor analysis to detect the causes of land degradation in Maduo County,northeastern Qinghai-Tibet Plateau 认领 引用
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作者 Fei Peng Xian Xue +2 位作者 Tao Wang CuiHua Huang Fang Zhang 《Research in Cold and Arid Regions》 2010年第2期154-161,共8页
The area of desertified land has increased by 27.3% from 1987 to 2000 in Maduo County,northeastern Qinghai-Tibet Plateau.Driving forces of land degradation has been extensively studied in the region.Using Factor Analy... The area of desertified land has increased by 27.3% from 1987 to 2000 in Maduo County,northeastern Qinghai-Tibet Plateau.Driving forces of land degradation has been extensively studied in the region.Using Factor Analysis (FA),we evaluate contribution of human activity and natural environmental change to land degradation.Four common factors were extracted in this study.The result shows that climate related other than human-related factors,are the major inducing factors of land degradation in Maduo County.Climate change and consequent change of permafrost account for 70% to the land degradation.Increasing evaporation and declining precipitation in the beginning of the growing season hamper seedling establishment.Decreasing frozen days and rising active layer lower bound make surface soil loose and less soil moisture available for plant. 展开更多
关键词 land degradation factor analysis permafrost climate variations Maduo County Yellow River
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Comprehensive Evaluation of Processing Quality of Tibetan Native Hulless Barley Variety by Factor Analysis 认领 引用
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作者 Jin Yu-long Bai Ting +5 位作者 Zhang Yu-hong Zhu Ming-xia Zhang Zhi-wei Wang Shan-shan Liu Xiao-jiao Jia Fu-chen 《Journal of Northeast Agricultural University(English Edition)》 CAS 2021年第2期61-68,共8页
The purpose of this study was to explore the quality of the Tibetan native hulless barley variety in depth and to evaluate the characteristics of its processing quality using ratio analysis.For this study,10 native ba... The purpose of this study was to explore the quality of the Tibetan native hulless barley variety in depth and to evaluate the characteristics of its processing quality using ratio analysis.For this study,10 native barley varieties were chosen with the detection of 24 quality indexes in order to build a system of comprehensive evaluation.The results of the factor analysis indicated that seven common factors with an eigenvalue greater than 1 were extracted,cumulatively accounting for 96.21%of the total variance.The first common factor,including ASP,GLU,SER,GLY,ARG,TYR and CYS contents,accounted for 33.82%of the variance.The second common factor,including ash,the total starch,soluble fiber,VB3,Cu,Mn,Na and beta-glucan contents,accounted for 19.46%of the variance.The third common factor,including the total dietary fiber,α-VE,K,Zn and glutelin.The fourth common factor,including B,Ba and prolamin,explained the barley starch character of the rheological property.The fifth common factor included crude fiber.The sixth and the seventh common factors did not account for a substantial amount of variance.According to the comprehensive evaluation model,the score consequence was as the following:Zangqing25>Pengnaigabu>Lhasa changhei>2004Qing21>Lhasa duanbai>Liangamu>Zhikonggaxia>lianmubai>Jiangreejiu>Longzihei. 展开更多
关键词 Tibetan hulless barley process quality comprehensive evaluation factor analysis
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Simultaneous Spectrophotometric Determination of Four Components including Acetaminophen by Taget Factor Analysis 认领 引用
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作者 张立庆 《Journal of Wuhan University of Technology(Materials Science)》 SCIE EI CAS 2007年第3期569-571,共3页
UV Spectrophotometric Target Factor Analysis （TFA） was used for the simultaneous determination of four components （acetaminophen, guuaifenesin, caffeine, Chlorphenamine maleate） in cough syrup. The computer Frogra... UV Spectrophotometric Target Factor Analysis （TFA） was used for the simultaneous determination of four components （acetaminophen, guuaifenesin, caffeine, Chlorphenamine maleate） in cough syrup. The computer Frogram of TFA is based on VC＋＋ language. The difficulty of overlapping of absorption spectra of four compounds was overcome by this procedure. The experimental results show that the average recovery of each component is all in the range from 98.9% to 106.8% and each component obtains satisfactory results without any pre-separation. 展开更多
关键词 acetaminophen taget factor analysis spectrophotometry four-component simultaneous determination
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