Fuzzy association rules (FARs) can be powerful in assessing regional soil quality, a critical step prior to land planning and utilization; however, traditional FARs mined from soil quality database, ignoring the impor...Fuzzy association rules (FARs) can be powerful in assessing regional soil quality, a critical step prior to land planning and utilization; however, traditional FARs mined from soil quality database, ignoring the importance variability of the rules, can be redundant and far from optimal. In this study, we developed a method applying different weights to traditional FARs to improve accuracy of soil quality assessment. After the FARs for soil quality assessment were mined, redundant rules were eliminated according to whether the rules were significant or not in reducing the complexity of the soil quality assessment models and in improving the comprehensibility of FARs. The global weights, each representing the importance of a FAR in soil quality assessment, were then introduced and refined using a gradient descent optimization method. This method was applied to the assessment of soil resources conditions in Guangdong Province, China. The new approach had an accuracy of 87%, when 15 rules were mined, as compared with 76% from the traditional approach. The accuracy increased to 96% when 32 rules were mined, in contrast to 88% from the traditional approach. These results demonstrated an improved comprehensibility of FARs and a high accuracy of the proposed method.展开更多
China has a large potential to reduce CO2 emission in the Asian region. In this study, life cycle analyses of energy supply technologies in China were evaluated for enforcing the clean development mechanism （CDM）. W...China has a large potential to reduce CO2 emission in the Asian region. In this study, life cycle analyses of energy supply technologies in China were evaluated for enforcing the clean development mechanism （CDM）. Wind power, integrated coal gasification combined cycle （IGCC）, natural gas combined cycle （NGCC）, and ultra super critical power plant （USC） were chosen as new power generation technologies. The system function of the developed model was enhanced to extend coverage to new technologies for power generation systems in China. CO2 intensities, energy profit ratios, and CO2 emission reductions are estimated based on the assumption that these power plants were constructed at Shanxi, Xinjiang, and Shanghai. Wind power showed the best results with regard to CO2 intensity and energy profit ratio. However, it also has some disadvantages with regard to the utilization factor and the lifetime. It is considered that wind power will become an important part of CDM activities as the utilization factor and the lifetime improve. An NGCC using a natural gas pipeline was found to be most advantageous in reducing CO2 emission. IGCC and USC were inferior to NGCC with regard to energy profit ratios and CO2 emission reductions.展开更多
How to have a more long-term vitality in the fierce competition in the industry and complex market environment, to have the more powerful anti-risk capability and competitive advantage is a modem airport managers have...How to have a more long-term vitality in the fierce competition in the industry and complex market environment, to have the more powerful anti-risk capability and competitive advantage is a modem airport managers have an urgent need to solve the problem. Because the nature of this paper will be ＂core competence＂ deemed to maintain long-term vitality and airport businesses a competitive advantage in the fierce competition in the industry. It can interpret and summarize the definition of core competence connotation airport, specificity and identification method to construct a two-dimensional Airport Enterprise core competence evaluation system and core competencies of three large enterprises of China＇ s civil aviation airport with the area to evaluate the scientific and operational test evaluation model.展开更多
The dynamic conditional correlation(DCC) model has been widely used for modeling the conditional correlation of multivariate time series by Engle(2002). However, the stationarity conditions have been established only ...The dynamic conditional correlation(DCC) model has been widely used for modeling the conditional correlation of multivariate time series by Engle(2002). However, the stationarity conditions have been established only recently and the asymptotic theory of parameter estimation for the DCC model has not yet to be fully discussed. In this paper, we propose an alternative model, namely the scalar dynamic conditional correlation(SDCC) model. Sufficient and easily-checked conditions for stationarity, geometric ergodicity, andβ-mixing with exponential-decay rates are provided. We then show the strong consistency and asymptotic normality of the quasi-maximum-likelihood estimator(QMLE) of the model parameters under regular conditions.The asymptotic results are illustrated by Monte Carlo experiments. As a real-data example, the proposed SDCC model is applied to analyzing the daily returns of the FSTE(financial times and stock exchange) 100 index and FSTE 100 futures. Our model improves the performance of the DCC model in the sense that the Li-Mc Leod statistic of the SDCC model is much smaller and the hedging efficiency is higher.展开更多
基金Supported by the National Natural Science Foundation of China (Nos.40671145 and 60573115)the Provincial Natural Science Foundation of Guangdong,China (Nos.04300504 and 05006623)
文摘Fuzzy association rules (FARs) can be powerful in assessing regional soil quality, a critical step prior to land planning and utilization; however, traditional FARs mined from soil quality database, ignoring the importance variability of the rules, can be redundant and far from optimal. In this study, we developed a method applying different weights to traditional FARs to improve accuracy of soil quality assessment. After the FARs for soil quality assessment were mined, redundant rules were eliminated according to whether the rules were significant or not in reducing the complexity of the soil quality assessment models and in improving the comprehensibility of FARs. The global weights, each representing the importance of a FAR in soil quality assessment, were then introduced and refined using a gradient descent optimization method. This method was applied to the assessment of soil resources conditions in Guangdong Province, China. The new approach had an accuracy of 87%, when 15 rules were mined, as compared with 76% from the traditional approach. The accuracy increased to 96% when 32 rules were mined, in contrast to 88% from the traditional approach. These results demonstrated an improved comprehensibility of FARs and a high accuracy of the proposed method.
文摘China has a large potential to reduce CO2 emission in the Asian region. In this study, life cycle analyses of energy supply technologies in China were evaluated for enforcing the clean development mechanism （CDM）. Wind power, integrated coal gasification combined cycle （IGCC）, natural gas combined cycle （NGCC）, and ultra super critical power plant （USC） were chosen as new power generation technologies. The system function of the developed model was enhanced to extend coverage to new technologies for power generation systems in China. CO2 intensities, energy profit ratios, and CO2 emission reductions are estimated based on the assumption that these power plants were constructed at Shanxi, Xinjiang, and Shanghai. Wind power showed the best results with regard to CO2 intensity and energy profit ratio. However, it also has some disadvantages with regard to the utilization factor and the lifetime. It is considered that wind power will become an important part of CDM activities as the utilization factor and the lifetime improve. An NGCC using a natural gas pipeline was found to be most advantageous in reducing CO2 emission. IGCC and USC were inferior to NGCC with regard to energy profit ratios and CO2 emission reductions.
文摘How to have a more long-term vitality in the fierce competition in the industry and complex market environment, to have the more powerful anti-risk capability and competitive advantage is a modem airport managers have an urgent need to solve the problem. Because the nature of this paper will be ＂core competence＂ deemed to maintain long-term vitality and airport businesses a competitive advantage in the fierce competition in the industry. It can interpret and summarize the definition of core competence connotation airport, specificity and identification method to construct a two-dimensional Airport Enterprise core competence evaluation system and core competencies of three large enterprises of China＇ s civil aviation airport with the area to evaluate the scientific and operational test evaluation model.
基金supported by National Natural Science Foundation of China(Grant No.71771224)National Social Science Foundation of China(Grant Nos.14ZDA044 and 15BGJ037)+1 种基金the Program for National Statistics Science Research Plan(Grant No.2016LD02)the Program for Innovation Research in Central University of Finance and Economics
文摘The dynamic conditional correlation(DCC) model has been widely used for modeling the conditional correlation of multivariate time series by Engle(2002). However, the stationarity conditions have been established only recently and the asymptotic theory of parameter estimation for the DCC model has not yet to be fully discussed. In this paper, we propose an alternative model, namely the scalar dynamic conditional correlation(SDCC) model. Sufficient and easily-checked conditions for stationarity, geometric ergodicity, andβ-mixing with exponential-decay rates are provided. We then show the strong consistency and asymptotic normality of the quasi-maximum-likelihood estimator(QMLE) of the model parameters under regular conditions.The asymptotic results are illustrated by Monte Carlo experiments. As a real-data example, the proposed SDCC model is applied to analyzing the daily returns of the FSTE(financial times and stock exchange) 100 index and FSTE 100 futures. Our model improves the performance of the DCC model in the sense that the Li-Mc Leod statistic of the SDCC model is much smaller and the hedging efficiency is higher.
