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.

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.

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.

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.

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.

Employment Quality EvaluationModel Based on Hybrid Intelligent Algorithm

In order to solve the defect of large error in current employment quality evaluation,an employment quality evaluation model based on grey correlation degree method and fuzzy C-means(FCM)is proposed.Firstly,it analyzes the related research work of employment quality evaluation,establishes the employment quality evaluation index system,collects the index data,and normalizes the index data;Then,the weight value of employment quality evaluation index is determined by Grey relational analysis method,and some unimportant indexes are removed;Finally,the employment quality evaluation model is established by using fuzzy cluster analysis algorithm,and compared with other employment quality evaluation models.The test results show that the employment quality evaluation accuracy of the design model exceeds 93%,the employment quality evaluation error can meet the requirements of practical application,and the employment quality evaluation effect is much better than the comparison model.The comparison test verifies the superiority of the model.

The Implementation Effects of a Nationwide Sloping Farmland Soil Erosion Control Project in China

To understand implementation of a nationwide sloping farmland soil erosion comprehensive control project during China＇s 12 th Five-Year Plan we used data collection and expert consultation. We selected 24 indexes across three aspects including project management, engineering construction and implementation benefit and used AHP-grey correlation analysis methods. We found that the scores for engineering construction were greater than 0.65 in most of the provinces, autonomous regions and municipalities. These scores are high and scores for project management and implementation benefit are between 0.45–0.65; however, overall scores are low. The comprehensive evaluation results are normally distributed. The composite scores for Sichuan, Yunnan and Guizhou are 0.71, 0.68 and 0.68 respectively, indicating that the implementation effects are good. The scores for Jilin and Liaoning are 0.38 and 0.42 respectively, indicating that the implementation effects need improvement. Scores for other provinces are between 0.45–0.65 and the effects are medium. The evaluation results show certain zonal rules spatially and the implementation effect in karst regions of Southwest China is the highest, followed by the purple soil region in Southwest China, Loess Plateau region of Northwest China, earth-rock mountain region of North China and red soil hilly region of South China. The implementation effect in the black soil region of Northeast China suggests that improvement is needed in this region.

基于灰色关联分析法及GSA-LSSVM的汽轮机排汽焓预测模型

排汽焓是汽轮发电机组热经济性诊断必不可少的一个参数。通过汽轮机功率方程与灰色关联分析(grey correlation analysis,GCA)理论确定了模型的输入变量,利用万有引力搜索算法(gravitational search algorithm,GSA)优化了最小二乘支持向量机(least squares support vector machine,LSSVM)的惩罚因子μ以及核径向范围σ2个参数。通过比较分析,选用RBF_kernel为LSSVM的核函数。以GCA-GSA-LSSVM为基础,建立了预测汽轮机排汽焓的数学模型,并将其与BP神经网络、RBF神经网络进行对比,同时分析了该数学模型的鲁棒性。结果表明基于GCA-GSA-LSSVM的汽轮机排汽焓预测模型具有精度高、泛化能力强、鲁棒性强等优点,该方法为精确预测机组节能潜力提供了一种有力的工具。