With the existence of several conventional and advanced building thermal energy demand forecast models to improve the energy efficiency of buildings,it is hard to find an appropriate,convenient,and efficient model.Eva...With the existence of several conventional and advanced building thermal energy demand forecast models to improve the energy efficiency of buildings,it is hard to find an appropriate,convenient,and efficient model.Evaluations based on statistical indexes(MAE,RMSE,MAPE,etc.)that characterize the accuracy of the forecasts do not help in the identification of the efficient building thermal energy demand forecast tool since they do not reflect the efforts entailed in implementation of the forecast model,i.e.,data collection to production/use phase.Hence,this work presents a Gini Index based Measurement of Alternatives and Ranking according to COmpromise Solution(GI-MARCOS),a hybrid Multi Attribute Decision Making(MADM)approach for the identification of the most efficient building energy demand forecast tool.GI-MARCOS employs(i)GI based objective weight method:assigns meaningful objective weights to the attributes in four phases(1:pre-processing,2:implementation,3:post-processing,and 4:use phase)thereby avoiding unnecessary biases in the expert’s opinion on weights and applicable to domains where there is a lack of domain expertise,and(ii)MARCOS:provides a robust and reliable ranking of alternatives in a dynamic environment.A case study with three alternatives evaluated over three to six attributes in four phases of implementation(pre-processing,implementation,post-processing and use)reveals that the use of GI-MARCOS improved the accuracy of alternatives MLR and BM by 6%and 13%,respectively.Moreover,additional validations state that(i)MLR performs best in Phase 1 and 2,while ANN performs best in Phase 3 and 4 with BM providing a mediocre performance in all four phases,(ii)sensitivity analysis:provides robust ranking with interchange of weights across phases and attributes,and(iii)rank correlation:ranks produce by GI-MARCOS has a high correlation with GRA(0.999),COPRAS(0.9786),and ARAS(0.9775).展开更多
Inter-basin Water Transfer Projects require the appropriate financing model to attract large amounts of social investment.Therefore,financing model decision becomes the key of engineering construction.In three aspects...Inter-basin Water Transfer Projects require the appropriate financing model to attract large amounts of social investment.Therefore,financing model decision becomes the key of engineering construction.In three aspects,such as the subject,the object and the target of the financing model,Grey Target Model is established in this paper.First,the complex financing mode decision problems of Inter-basin Water Transfer Projects are decomposed by using hierarchical decomposition method.Then Analytical Hierarchy Process(AHP) method is used to calculate the comprehensive weight of evaluation index.Experts' opinions financing model are transformed into the evaluation matrix based on the Dephi method.The Weighted Grey Target Model is used to calculate the approaching degree of financing model and assists financing mode decision.In addition,this paper takes the water diversion project from the Han to the Wei River of Shaanxi Province as a verification example for the model.For other water diversion projects,the evaluation results are also reliable and provide theoretical references for the financing model decision of Inter-basin Water Transfer Projects.展开更多
用能方对节能服务公司(Energy Service Company,ESCO)的选择关系到合同能源管理(Energy Performance Contracting,EPC)能否顺利实施。从用能方的角度,采用灰色系统理论中的多目标加权灰靶决策模型,对存在多决策目标的ESCO选择问题进行...用能方对节能服务公司(Energy Service Company,ESCO)的选择关系到合同能源管理(Energy Performance Contracting,EPC)能否顺利实施。从用能方的角度,采用灰色系统理论中的多目标加权灰靶决策模型,对存在多决策目标的ESCO选择问题进行研究。通过层次分析法确定ESCO的11个决策目标的决策权数,根据综合效果测度值的比较,最终实现最优对策的选择。本文为用能方的ESCO选择问题提供了一种新的思路。展开更多
基金supported by The Indian Institute of Technology-Bombay(Institute Postdoctoral Fellowship-AO/Admin-1/Rect/33/2019).
文摘With the existence of several conventional and advanced building thermal energy demand forecast models to improve the energy efficiency of buildings,it is hard to find an appropriate,convenient,and efficient model.Evaluations based on statistical indexes(MAE,RMSE,MAPE,etc.)that characterize the accuracy of the forecasts do not help in the identification of the efficient building thermal energy demand forecast tool since they do not reflect the efforts entailed in implementation of the forecast model,i.e.,data collection to production/use phase.Hence,this work presents a Gini Index based Measurement of Alternatives and Ranking according to COmpromise Solution(GI-MARCOS),a hybrid Multi Attribute Decision Making(MADM)approach for the identification of the most efficient building energy demand forecast tool.GI-MARCOS employs(i)GI based objective weight method:assigns meaningful objective weights to the attributes in four phases(1:pre-processing,2:implementation,3:post-processing,and 4:use phase)thereby avoiding unnecessary biases in the expert’s opinion on weights and applicable to domains where there is a lack of domain expertise,and(ii)MARCOS:provides a robust and reliable ranking of alternatives in a dynamic environment.A case study with three alternatives evaluated over three to six attributes in four phases of implementation(pre-processing,implementation,post-processing and use)reveals that the use of GI-MARCOS improved the accuracy of alternatives MLR and BM by 6%and 13%,respectively.Moreover,additional validations state that(i)MLR performs best in Phase 1 and 2,while ANN performs best in Phase 3 and 4 with BM providing a mediocre performance in all four phases,(ii)sensitivity analysis:provides robust ranking with interchange of weights across phases and attributes,and(iii)rank correlation:ranks produce by GI-MARCOS has a high correlation with GRA(0.999),COPRAS(0.9786),and ARAS(0.9775).
基金partly supported by the National Natural Science Foundation of China (Grant Nos.51209170,and 51479160)the foundation for the Plan Projects of Water Conservancy Science and Technology of Shaanxi Province (Grant No.2013SLKJ05)the Project Supported by Natural Science Basic Research Plan in Shaanxi Province of China (Grant No.2016JQ5061)
文摘Inter-basin Water Transfer Projects require the appropriate financing model to attract large amounts of social investment.Therefore,financing model decision becomes the key of engineering construction.In three aspects,such as the subject,the object and the target of the financing model,Grey Target Model is established in this paper.First,the complex financing mode decision problems of Inter-basin Water Transfer Projects are decomposed by using hierarchical decomposition method.Then Analytical Hierarchy Process(AHP) method is used to calculate the comprehensive weight of evaluation index.Experts' opinions financing model are transformed into the evaluation matrix based on the Dephi method.The Weighted Grey Target Model is used to calculate the approaching degree of financing model and assists financing mode decision.In addition,this paper takes the water diversion project from the Han to the Wei River of Shaanxi Province as a verification example for the model.For other water diversion projects,the evaluation results are also reliable and provide theoretical references for the financing model decision of Inter-basin Water Transfer Projects.
文摘用能方对节能服务公司(Energy Service Company,ESCO)的选择关系到合同能源管理(Energy Performance Contracting,EPC)能否顺利实施。从用能方的角度,采用灰色系统理论中的多目标加权灰靶决策模型,对存在多决策目标的ESCO选择问题进行研究。通过层次分析法确定ESCO的11个决策目标的决策权数,根据综合效果测度值的比较,最终实现最优对策的选择。本文为用能方的ESCO选择问题提供了一种新的思路。
