Evaluation of Comprehensive Performance of Agronomic Traits of Anmai 1241 by Grey Correlation Analysis and Cluster Analysis Methods

The agronomic traits of the new wheat variety Anmai 1241 were comprehensively evaluated,in order to provide comprehensive and objective theoretical basis for further improvement and production utilization of this variety.The winter water production test results of Anmai 1241 in 14 pilot sites of Henan Seed Management Station from 2016 to 2017 were summarized.The comprehensive performance of 11 agronomic traits of Anmai 1241 in different tests sites in Henan Province was evaluated by the grey correlation analysis and clustering analysis methods.The results showed that among the observed values of 11 traits,the variation coefficient,correlation degree and weight of black embryo rate were 181.64%,0.6679 and 0.1051,respectively.The clustering analysis showed that the 11 traits could be divided into 3 groups.The first type of traits(yield,number of grains per ear and 1000-grain weight)and the third group of traits(percentage of earbearing tillers,number of productive tillers and volume weight)belonged to the yield factor traits,and the sum of their weights was 0.5242.Yield and its related factors played an important role in the variety evaluation of Anmai 1241,and the effect of black embryo on yield should be eliminated in variety improvement.

A precise tidal prediction mechanism based on the combination of harmonic analysis and adaptive network-based fuzzy inference system model

An efficient and accurate prediction of a precise tidal level in estuaries and coastal areas is indispensable for the management and decision-making of human activity in the field wok of marine engineering. The variation of the tidal level is a time-varying process. The time-varying factors including interference from the external environment that cause the change of tides are fairly complicated. Furthermore, tidal variations are affected not only by periodic movement of celestial bodies but also by time-varying interference from the external environment. Consequently, for the efficient and precise tidal level prediction, a neuro-fuzzy hybrid technology based on the combination of harmonic analysis and adaptive network-based fuzzy inference system（ANFIS）model is utilized to construct a precise tidal level prediction system, which takes both advantages of the harmonic analysis method and the ANFIS network. The proposed prediction model is composed of two modules： the astronomical tide module caused by celestial bodies’ movement and the non-astronomical tide module caused by various meteorological and other environmental factors. To generate a fuzzy inference system（FIS） structure,three approaches which include grid partition（GP）, fuzzy c-means（FCM） and sub-clustering（SC） are used in the ANFIS network constructing process. Furthermore, to obtain the optimal ANFIS based prediction model, large numbers of simulation experiments are implemented for each FIS generating approach. In this tidal prediction study, the optimal ANFIS model is used to predict the non-astronomical tide module, while the conventional harmonic analysis model is used to predict the astronomical tide module. The final prediction result is performed by combining the estimation outputs of the harmonious analysis model and the optimal ANFIS model. To demonstrate the applicability and capability of the proposed novel prediction model, measured tidal level samples of Fort Pulaski tidal station are selected as the testing database. Simulation and experimental results confirm that the proposed prediction approach can achieve precise predictions for the tidal level with high accuracy, satisfactory convergence and stability.

Multi-attributed decision making for mining methods based on grey system and interval numbers

In the case of unknown weights, theories of multi-attributed decision making based on interval numbers and grey related analysis were used to optimize mining methods. As the representative of independence for the indicator, the smaller the correlation of indicators is, the greater the weight is. Hence, the weights of interval numbers of indicators were determined by using correlation coefficient. Relative closeness based on positive and negative ideal methods was calculated by introducing distance between interval numbers, which made decision making more rational and comprehensive. A new method of ranking interval numbers based on normal distribution was proposed for the optimization of mining methods, whose basic properties were discussed. Finally, the feasibility and effectiveness of this method were verified by theories and practice.

Kernel method-based fuzzy clustering algorithm

The fuzzy C-means clustering algorithm(FCM) to the fuzzy kernel C-means clustering algorithm(FKCM) to effectively perform cluster analysis on the diversiform structures are extended, such as non-hyperspherical data, data with noise, data with mixture of heterogeneous cluster prototypes, asymmetric data, etc. Based on the Mercer kernel, FKCM clustering algorithm is derived from FCM algorithm united with kernel method. The results of experiments with the synthetic and real data show that the FKCM clustering algorithm is universality and can effectively unsupervised analyze datasets with variform structures in contrast to FCM algorithm. It is can be imagined that kernel-based clustering algorithm is one of important research direction of fuzzy clustering analysis.

Evaluation of Farmland Drainage Water Quality by Fuzzy–Gray Combination Method

The complex relationships between indicators and water conditions cause fuzzy and gray uncertainties in evaluation of water quality. Compared to conventional single-factor evaluation methods, the combination evaluation method can consider these two uncertainties to produce more objective and reasonable evaluation results. In this paper, we propose a combination evaluation method with two main parts:(1) the use of fuzzy comprehensive evaluation and gray correlation analysis as submodels with which to consider the fuzzy and gray uncertainties and(2) the establishment of a combination model based on minimum bias squares. In addition, using this method, we evaluate the water quality of a ditch in a typical rice–wheat system of Yixing city in the Taihu Lake Basin during three rainfall events. The results show that the ditch water quality is not good and we found the chemical oxygen demand to be the key indicator that affects water quality most significantly. The proposed combination evaluation method is more accurate and practical than single-factor evaluation methods in that it considers the uncertainties of fuzziness and grayness.

AN ANALYSIS OF THE APPLICABILITY OF FUZZY CLUSTERING IN ESTABLISHING AN INDEX FOR THE EVALUATION OF METEOROLOGICAL SERVICE SATISFACTION

An evaluation index is a prerequisite for the scientific evaluation of a public meteorological service.This paper aims to explore a technical method for determining and screening evaluation indicators.Based on public satisfaction survey data obtained in Wafangdian,China in 2010,this study investigates the suitability of fuzzy clustering analysis method in establishing an evaluation index.Through quantitative analysis of multilayer fuzzy clustering of various evaluation indicators,correlation analysis indicates that if the results of clustering were identical for two evaluation indicators in the same sub-evaluation layer,then one indicator could be removed,or the two indicators merged.For evaluation indicators in different sub-evaluation layers,although clustering reveals attribute correlations,these indicators may not be substituted for one another.Analysis of the applicability of the fuzzy clustering method shows that it plays a certain role in the establishment and correction of an evaluation index.

The Establishment of Mathematical Models for the Composition Analysis and Identification of Ancient Glass Products

Glass is the precious material evidence of the trade of the early Silk Road. The ancient glass was easily affected by the environmental impact and weathering, and the change of composition ratios affected the correct judgment of its category. In this paper, mathematical models and methods such as Chi-square test, weighted average method, principal component analysis, cluster analysis, binary classification model and grey correlation analysis were used comprehensively to analyze the data of sample glass products combined with their categories. The results showed that the weathered high-potassium glass could be divided into 12, 9, 10 and 27, 7, 22 and so on.

Spatiotemporal evolution and influencing factors of urban resilience in the Yellow River Basin,China

The Yellow River Basin of China is a key region that contains myriad interactions between human activities and natural environment.Industrialization and urbanization promote social-economic development,but they also have generated a series of environmental and ecological issues in this basin.Previous researches have evaluated urban resilience at the national,regional,urban agglomeration,city,and prefecture levels,but not at the watershed level.To address this research gap and elevate the Yellow River Basin’s urban resilience level,we constructed an urban resilience evaluation index system from five dimensions:industrial resilience,social resilience,environmental resilience,technological resilience,and organizational resilience.The entropy weight method was used to comprehensively evaluate urban resilience in the Yellow River Basin.The exploratory spatial data analysis method was employed to study the spatiotemporal differences in urban resilience in the Yellow River Basin in 2010,2015,and 2020.Furthermore,the grey correlation analysis method was utilized to explore the influencing factors of these differences.The results of this study are as follows:(1)the overall level of urban resilience in the Yellow River Basin was relatively low but showed an increasing trend during 2010–2015,and significant spatial distribution differences were observed,with a higher resilience level in the eastern region and a low-medium resilience level in the western region;(2)the differences in urban resilience were noticeable,with industrial resilience and social resilience being relatively highly developed,whereas organizational resilience and environmental resilience were relatively weak;and(3)the correlation ranking of resilience influencing factors was as follows:science and technology level>administrative power>openness>market forces.This research can provide a basis for improving the resilience level of cities in the Yellow River Basin and contribute to the high-quality development of the region.

A New Algorithm for Black-start Zone Partitioning Based on Fuzzy Clustering Analysis

On the process of power system black start after an accident, it can help to optimize the resources allocation and accelerate the recovery process that decomposing the power system into several independent partitions for parallel recovery. On the basis of adequate consideration of fuzziness of black-start zone partitioning, a new algorithm based on fuzzy clustering analysis is presented. Characteristic indexes are extracted fully and accurately. The raw data matrix is made up of the electrical distance between every nodes and blackstart resources. Closure transfer method is utilized to get the dynamic clustering. The availability and feasibility of the proposed algorithm are verified on the New-England 39 bus system at last.

Analysis of Factors Influencing Comprehensive Productivity of Agriculture in Henan Province on the Basis of Grey Correlation

According to the data from Henan Statistical Yearbook from 2002 to 2008, from production capital, production conditions, labour inputs and financial support, this paper selects 11 variables influencing comprehensive productivity of agriculture in Henan Province. Through calculation and analysis of grey correlation of variables and comprehensive productivity of agriculture, this paper determines the impact of different variables on comprehensive productivity of agriculture. The results show that the agricultural capital has become the most important factor influencing comprehensive productivity of agriculture in Henan Province, while the impact of production conditions, labour inputs and financial support on comprehensive productivity of agriculture in Henan Province diminishes in turn. Corresponding countermeasures and suggestions are put forward to promote the sustainable development of comprehensive productivity of agriculture in Henan Province as follows: strengthen agricultural financial system building, and ensure agricultural production expenditure; scientifically arrange allocation of agricultural resources, and improve agricultural production conditions; carry out training of agricultural skills, and elevate the quality of agricultural labour forces; increase financial expenditure for agricultural production, and optimize financial expenditure structure.

Prediction method of highway pavement rutting based on the grey theory

In order to make a scientific pavement maintenance decision, a grey-theory-based prediction methodological framework is proposed to predict pavement performance. Based on the field pavement rutting data,analysis of variance （ANOVA）was first used to study the influence of different factors on pavement rutting. Cluster analysis was then employed to investigate the rutting development trend.Based on the clustering results,the grey theory was applied to build pavement rutting models for each cluster, which can effectively reduce the complexity of the predictive model.The results show that axial load and asphalt binder type play important roles in rutting development.The prediction model is capable of capturing the uncertainty in the pavement performance prediction process and can meet the requirements of highway pavement maintenance,and,therefore,has a wide application prospects.

Analysis of the Influence Factors of Grain Supply-Demand Gap in China

Based on the analysis of the grain supply and demand gap’s current situation in China, this paper establishes an indicator system for the influence factors of grain supply and demand gap. Then this paper calculates the correlation degree between the main grain varieties’ supply and demand gap and its influence factors. The results show that sown area and unit yield have the greatest impact on wheat supply and demand gap;per capita disposable income and unit yield have the greatest impact on corn supply and demand gap;per capita disposable income and agricultural mechanization level have the greatest impact on the supply and demand gap of soybean and rice. From the analysis results, we can obtain the difference between the factors affecting the grain supply and demand gap, and provide a certain theoretical basis and new ideas for the balance of grain supply and demand in China.

Effects of Modulation Methods on the Drying Characteristics and Nutritional Quality of Medicago sativa Hay

Two-year-old Medicago sativa at budding initial stage was taken as research materials.Five methods were used to make green hay,including flatting stems ＋ spraying 2.5% K2CO3,flatting stems,sun curing,drying in shade and drying under 105 ℃ condition（CK）.Besides,effects of different green hay making methods on dry characteristics and nutritional quality of M.sativa green hay were studied,and a comprehensive evaluation of M.sativa green hays was conducted.Results showed that,except CK,the drying rates in other making methods were all fast at first,and then slow down.Both of drying under 105 ℃ condition and flatting stems ＋ spraying K2CO3 could speed up drying rate and reduce nutritional losses of green hay.Sun curing could also speed up drying rate,but it could not maintain the quality of green hay.The results of Grey Relational Analysis on five green hay making methods indicated that CK had the best comprehensive performance,followed by green hays made by flatting stems ＋ spraying K2CO3.Therefore,flatting stems ＋ spraying K2CO3 was a quick and easy method to make green hay,and it was worth to be recommended in practical production.

匝道合流交通场景下自动驾驶汽车安全性测试评价方法

针对高速匝道交通场景提出了一种基于自然驾驶数据的自动驾驶汽车安全性评价方法。通过分析合流区冲突特征,建立碰撞时间(Time to Collision,TTC)模型、后侵占时间(Post Encroachment Time,PET)模型、最小安全换道距离(Minimum Safe Spacing,MSS)交通冲突指标计算模型来确定安全性评价指标,利用模糊聚类自然驾驶指标数据确定指标阈值范围,搭建自动驾驶汽车仿真测试试验,应用层间相关性的重要性准则权重分配方法和灰色关联评分模型,计算得到不同控制算法下自动驾驶汽车安全性的综合评价得分。结果表明,被试车辆驾驶行为与理想驾驶行为在各安全性指标的关联度分布明显,计算总体关联度,得分可以直观说明不同自动驾驶系统的综合安全性能。

基于模糊数学的多源异构数据融合模型

针对多源异构型数据来源复杂、结构特殊,导致其融合难度较大的问题,为提升数据融合效率与准确性,提出一种基于模糊数学的多源异构数据融合模型.首先,利用联邦加权平均融合策略,整合从各传感器传输至数据级融合层中的元数据,得到数据级融合结果;其次,结合主成分分析法与典型相关分析法,提取出由网络本体语言统一后数据的特征,完成特征级数据融合;再次,根据模糊数学理论建立、更新模糊规则库,通过决策融合算法,得到决策级融合结果;最后,将上述不同层级的数据融合结果结合建立数据融合模型,得到最终的数据融合结果.实验结果表明,该方法的最大协方差值和绝对误差值不超过0.15,最短融合时间仅为12.6 ms.该方法的融合精度和稳定性较好,时效性与抗扰性均具有显著的优越性.

基于电池企业价值评估的市场法改进

电池行业内部注册和上市的企业数量逐渐增多,并购交易活动也在不断增加,这就使相关行业对电池企业价值评估的需求不断增多。寻找合适的评估方法是正确评估企业价值的关键,在对电池企业的特征进行分析后,发现运用传统价值评估模型存在局限性,而市场法对其有一定的适用性。因此以市场法的理论为依据,对可比公司和价值乘数的选择进行优化,最终得到一种适用于电池企业的价值评估模型。经验检验表明:改进市场法所评估的价值更接近企业的实际,更契合电池行业的特性。

充填体破坏特征的聚类分析及数值模拟

充填体破坏是影响矿山安全稳定的重要因素之一。为研究充填体的破坏特征,采用室内实验、机器学习层次聚类分析及数值模拟等方法,对矸石胶结充填体(GCPB)裂纹演化的全状态进行了研究。结果表明:当GCPB试样PC-5、PC-10、PC-15、PC-20的特征键平均键长能量分别大于35、50、60、150 ms·mV时,出现宏观主裂纹面,且主裂纹破坏面随水泥掺量的增加由张拉破坏面向剪切破坏面转变;破坏过程中特征键子集尺度Ω与损伤变量D之间呈负线性相关关系,Ω可表征充填体损伤演化程度;在应力达到峰值应力和破坏后残余强度前键长值特征空间相关长度ξ表现为明显增长,为充填体宏观损伤的开始及第1次破坏结束的前兆特征;通过颗粒流程序(PFC)数值模拟,可以有效观测到裂纹的类型和变化规律,数值模拟结果与聚类分析结果一致。

4种薯类食品多项指标的灰色模式识别分析

选择我国不同地区红薯、山药、葛根、紫薯4种薯类食品作为研究对象,对食品多指标测定与综合评价.从燃烧热、燃烧稳定性、脂肪、灰分、粗纤维含量方面评价食品营养.测定4种食品燃烧热、燃烧稳定性、脂肪、灰分及粗纤维含量,并从食品营养方面用化学计量方法进行质量评价与分类.结果表明,4种薯类食品燃烧热大小顺序为:葛根>红薯>山药>紫薯,燃烧稳定性排序为:山药>葛根>紫薯>红薯,脂肪含量顺序为:葛根>紫薯>红薯>山药,灰分含量顺序为:葛根>山药>红薯>紫薯,粗纤维含量顺序为:紫薯>山药>葛根>红薯,多指标化学计量分析顺序为:山药>葛根>紫薯>红薯.这项研究为热重分析方法研究食品燃烧稳定性评价与研究提供理论支持,这项研究建立的多指标综合评价体系为食品营养评价提供一种新思路,这项研究为大规模开发食品资源以及食品分类研究提供有力地科学依据.

一种基于Fuzzy聚类分析的疾病预测诊断模型

使用模糊聚类分析的方法,在医学上建立了疾病预测诊断模型,并将其应用于临床疾病诊断。通过实例检验表明,该方法具有良好的实际应用前景。

张家口柴宣盆地浅层地下水水化学特征及水质评价

地下水作为张家口地区的主要供水水源,近年来受人类活动影响水质有恶化的趋势,影响了当地的用水安全,确定地下水化学特征与水质状况对水资源合理利用具有重要意义。基于2020年水质数据,选取Ca^(2+)、Mg^(2+)、K^(+)、Na^(+)、HCO^(-)_(3)、TH、pH、TDS、SO_(4)^(2-)、Cl^(-)、Al^(3+)、NO^(-)_(3)、F^(-)、Cr^(6+)等水质因子,通过数理统计法、Piper三线图、Gibbs图和岩石风化端元图对张家口柴宣盆地地区浅层地下水水化学特征进行分析,并采用模糊综合评价和改进内梅罗指数法对水质进行评价。结果表明:研究区地下水是Ca^(2+)和HCO^(-)_(3)为主的弱碱性淡水,微硬水、硬水和极硬水分别占39.51%、34.57%和25.93%;沿地下水流向,地下水化学类型由HCO_(3)-Ca·Mg、HCO_(3)-Na、SO_(4)·Cl-Na型转变为HCO_(3)-Ca·Mg、HCO_(3)-Na、SO_(4)·Cl-Ca·Mg型,水化学组分的空间分布特征主要受到硅酸盐、碳酸盐的风化溶解和人类活动影响;地下水水质整体满足III类标准,但部分地区水质较差;沿着地下水流向,水质逐渐变差,主要受原生地质环境和工业、农业污染的影响。