首页 | 本学科首页   官方微博 | 高级检索  
文章检索
  按 检索   检索词:      
出版年份:   被引次数:   他引次数: 提示:输入*表示无穷大
  收费全文   2篇
  免费   0篇
环保管理   1篇
基础理论   1篇
  2013年   1篇
  1974年   1篇
排序方式: 共有2条查询结果,搜索用时 15 毫秒
1
1.
ABSTRACT: An auto-regressive model has been developed for hydrologic data simulation. The model is computationally easier, parsimonious in number of model parameters and more stable in statistical characteristics than the existing auto-regressive model. The proposed model was used for synthesizing 10 sequences, each of 100 year length, of monthly flows for the river Beas. The statistical parameters were calculated using 49-year historical record for the river. The data was also synthesized using existing auot-regressive model. The synthesized sequences have been compared. The results indicate that the proposed model is as good as the existing auto-regressive model in preserving the mean and standard deviation of historical record. It is further shown that the proposed model requires less parameters than the auto-regressive model for simulation of long-term dependence.  相似文献   
2.
ABSTRACT

The main purpose of Green Supply Chain Management (GSCM) is to improve the quality of supply chain management strategies and environmental performance. As per current statistics, the chemical industry is growing fast in Bangladesh. In order to compete for global competition, GSCM is essential in this sector. This paper proposes a systematic approach of structural framework whose aim is to enhance the probability of constructive implementation of GSCM in the field chemical industry in Bangladesh. Therefore, this framework evaluates the appropriate interrelationship along with the drivers of GSCM in the chemical industry. In total, eight drivers were finalized from an associated literature review with the help of survey and by taking expert opinions via the Delphi methodology. In addition to MICMAC analysis, the driving and the dependence powers for all the drivers were determined. Moreover, the structural frameworks for the drivers were developed by means of total interpretive structural modeling (TISM) technique. As a result, the findings indicate that the most significant driver was supplier pressure and willingness and the most important barrier was high cost. Finally, the main objective of this research is expected to help industrial managers to evaluate and understand the critical areas where they should emphasize to implement GSCM in the chemical industry.  相似文献   
1
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号