Optimal Choice of Cotton Subsidy Mode in China—Empirical Study Based on Principal Component Regression
نویسندگان
چکیده
Adopt principal component regression for researching the optimal subsidy mode of cotton production in China. The result indicates that, from the perspective of economic stimulatory effect, the optimal cotton subsidy in China is farm chemical subsidy rather than seed subsidy. The reason is that there are frequent pest disasters in cotton producing areas in China. So farm chemical subsidy is the most important factor ensuring cotton production. Meanwhile, cotton varieties must be optimized and improved to increase the ability to resist pests and diseases, and the forecasting for pests and diseases in cotton production areas must be enhanced, early warning mechanism and monitoring must be built, and in addition, it is strongly recommended that if financial resources allow, subsidies like seed subsidy, fertilizer subsidy, machinery subsidy and irrigation subsidy could also put into effect in China.
منابع مشابه
A Fault Diagnosis Method for Automaton based on Morphological Component Analysis and Ensemble Empirical Mode Decomposition
In the fault diagnosis of automaton, the vibration signal presents non-stationary and non-periodic, which make it difficult to extract the fault features. To solve this problem, an automaton fault diagnosis method based on morphological component analysis (MCA) and ensemble empirical mode decomposition (EEMD) was proposed. Based on the advantages of the morphological component analysis method i...
متن کاملA Fault Diagnosis Method for Automaton Based on Morphological Component Analysis and Ensemble Empirical Mode Decomposition
In the fault diagnosis of automaton, the vibration signal presents non-stationary and non-periodic, which make it difficult to extract the fault features. To solve this problem, an automaton fault diagnosis method based on morphological component analysis (MCA) and ensemble empirical mode decomposition (EEMD) was proposed. Based on the advantages of the morphological component analysis method i...
متن کاملPredicting the Young\'s Modulus and Uniaxial Compressive Strength of a typical limestone using the Principal Component Regression and Particle Swarm Optimization
In geotechnical engineering, rock mechanics and engineering geology, depending on the project design, uniaxial strength and static Youngchr('39')s modulus of rocks are of vital importance. The direct determination of the aforementioned parameters in the laboratory, however, requires intact and high-quality cores and preparation of their specimens have some limitations. Moreover, performing thes...
متن کاملEmpirical Seismic Vulnerability and Damage of Bottom Frame Seismic Wall Masonry Structure: A Case Study in Dujiangyan (China) Region
In order to understand the seismic performance and mechanism of bottom frame seismic wall masonry structure (BFSWMS) and its vulnerability in empirical seismic damage, based on the statistical and numerical analysis of the field seismic damage observation data of 2178 Dujiangyan structures in the Wenchuan great earthquake urban of China on May 12, 2008, a non-linear function model between the s...
متن کاملAn Empirical Comparison between Grade of Membership and Principal Component Analysis
t is the purpose of this paper to contribute to the discussion initiated byWachter about the parallelism between principal component (PC) and atypological grade of membership (GoM) analysis. The author testedempirically the close relationship between both analysis in a lowdimensional framework comprising up to nine dichotomous variables and twotypologies. Our contribution to the subject is also...
متن کامل