The necessity of having an effective computer-aided decision support system in the housing construction industry is rapidly growing alongside the demand for green buildings and green building products. Identifying and...The necessity of having an effective computer-aided decision support system in the housing construction industry is rapidly growing alongside the demand for green buildings and green building products. Identifying and defining financially viable low-cost green building materials and components, just like selecting them, is a crucial exercise in subjectivity. With so many variables to consider, the task of evaluating such products can be complex and discouraging. Moreover, the existing mode for selecting and managing, often very large information associated with their impacts constrains decision-makers to perform a trade-off analysis that does not necessarily guarantee the most environmentally preferable material. This paper introduces the development of a multi-criteria decision support system (DSS) aimed at improving the understanding of the principles of best practices associated with the impacts of low-cost green building materials and components. The DSS presented in this paper is to provide designers with useful and explicit information that will aid informed decision-making in their choice of materials for low-cost green residential housing projects. The prototype MSDSS is developed using macro-in-excel, which is a fairly recent database management technique used for integrating data from multiple, often very large databases and other information sources. This model consists of a database to store different types of low-cost green materials with their corresponding attributes and performance characteristics. The DSS design is illustrated with particular emphasis on the development of the material selection data schema, and application of the Analytical Hierarchy Process (AHP) concept to a material selection problem. Details of the MSDSS model are also discussed including workflow of the data evaluation process. The prototype model has been developed with inputs elicited from domain experts and extensive literature review, and refined with feedback obtained from selected expert builder and developer companies. This paper further demonstrates the application of the prototype MSDSS for selecting the most appropriate low-cost green building material from among a list of several available options, and finally concludes the study with the associated potential benefits of the model to research and practice.展开更多
Accurate cost estimation at the early stage of a construction project is key factor in a project’s success. But it is difficult to quickly and accurately estimate construction costs at the planning stage, when drawin...Accurate cost estimation at the early stage of a construction project is key factor in a project’s success. But it is difficult to quickly and accurately estimate construction costs at the planning stage, when drawings, documentation and the like are still incomplete. As such, various techniques have been applied to accurately estimate construction costs at an early stage, when project information is limited. While the various techniques have their pros and cons, there has been little effort made to determine the best technique in terms of cost estimating performance. The objective of this research is to compare the accuracy of three estimating techniques (regression analysis (RA), neural network (NN), and support vector machine techniques (SVM)) by performing estimations of construction costs. By comparing the accuracy of these techniques using historical cost data, it was found that NN model showed more accurate estimation results than the RA and SVM models. Consequently, it is determined that NN model is most suitable for estimating the cost of school building projects.展开更多
A multi-layer adaptive optimizing parameters algorithm is developed forimproving least squares support vector machines (LS-SVM) , and a military aircraft life-cycle-cost(LCC) intelligent estimation model is proposed b...A multi-layer adaptive optimizing parameters algorithm is developed forimproving least squares support vector machines (LS-SVM) , and a military aircraft life-cycle-cost(LCC) intelligent estimation model is proposed based on the improved LS-SVM. The intelligent costestimation process is divided into three steps in the model. In the first step, a cost-drive-factorneeds to be selected, which is significant for cost estimation. In the second step, militaryaircraft training samples within costs and cost-drive-factor set are obtained by the LS-SVM. Thenthe model can be used for new type aircraft cost estimation. Chinese military aircraft costs areestimated in the paper. The results show that the estimated costs by the new model are closer to thetrue costs than that of the traditionally used methods.展开更多
背景:临床上血管支架的使用涉及高昂的医疗费用,但同时也可能在减少患者心血管事件、改善生活质量等方面带来长期的效益,而经济学评估可以帮助决策者更好地理解治疗方法的成本与效益之间的平衡。目的:分析卫生经济学相关文献,探讨血管...背景:临床上血管支架的使用涉及高昂的医疗费用,但同时也可能在减少患者心血管事件、改善生活质量等方面带来长期的效益,而经济学评估可以帮助决策者更好地理解治疗方法的成本与效益之间的平衡。目的:分析卫生经济学相关文献,探讨血管支架效果与问题在医疗质量管理研究中的热点。方法:检索Web of Science核心集数据库关于血管支架的卫生经济学评价文献,采用VOSviewer_1.6.19软件对年度发文量、机构、国家和关键词等进行可视化分析,最后从卫生经济学和医疗质量管理角度分析血管支架效果与问题的研究热点。结果与结论:①最终纳入英文文献120篇,近10年此领域研究发文最高的年份是2019年,发文10篇,发文量最多的机构是美国哈佛大学(发文20篇),发文量最多的国家是美国(发文58篇)。②关键词聚类分析显示,裸金属支架和药物洗脱支架在冠脉疾病中的成本效果分析、血管成形术支架干预的成本效益分析、经皮冠状动脉介入治疗中应用冠脉支架的效果,这3个聚类研究方向为血管支架研究领域的卫生经济学评估的研究热点。③进一步总结医疗管理质量背景下血管支架治疗效果的研究热点为:血管支架的长期效果、安全性、药物释放机制研究、个体化治疗、再狭窄问题和支架镶嵌技术。④高被引文献分析结果显示,药物洗脱支架释放药物以减少血管再狭窄的风险,与裸金属支架相比再狭窄率较低,但通常成本较高;生物降解支架是结合裸金属支架和药物洗脱支架的优点,即避免长期的支架存在和减少再狭窄的风险,但它们的成本可能会更高,而且短期内可能会有一些并发症,目前应用并不广泛。⑤在进行血管支架成本效果比较时,除了直接的支架成本外,还需要考虑的因素包括支架再干预的风险和成本、并发症的风险和成本、药物治疗的持续时间和成本、患者的生活质量。因此,虽然药物洗脱支架和生物降解支架的初始成本可能高于裸金属支架,但它们可能在长期内带来更好的临床结果,从而产生更有利的成本效果。⑥未来的研究方向应注重个性化的血管支架治疗决策的制定、观察支架治疗的长期效果、支架对患者生活质量的影响、制定卫生政策、医疗资源合理分配及长期随访机制的建立。展开更多
文摘The necessity of having an effective computer-aided decision support system in the housing construction industry is rapidly growing alongside the demand for green buildings and green building products. Identifying and defining financially viable low-cost green building materials and components, just like selecting them, is a crucial exercise in subjectivity. With so many variables to consider, the task of evaluating such products can be complex and discouraging. Moreover, the existing mode for selecting and managing, often very large information associated with their impacts constrains decision-makers to perform a trade-off analysis that does not necessarily guarantee the most environmentally preferable material. This paper introduces the development of a multi-criteria decision support system (DSS) aimed at improving the understanding of the principles of best practices associated with the impacts of low-cost green building materials and components. The DSS presented in this paper is to provide designers with useful and explicit information that will aid informed decision-making in their choice of materials for low-cost green residential housing projects. The prototype MSDSS is developed using macro-in-excel, which is a fairly recent database management technique used for integrating data from multiple, often very large databases and other information sources. This model consists of a database to store different types of low-cost green materials with their corresponding attributes and performance characteristics. The DSS design is illustrated with particular emphasis on the development of the material selection data schema, and application of the Analytical Hierarchy Process (AHP) concept to a material selection problem. Details of the MSDSS model are also discussed including workflow of the data evaluation process. The prototype model has been developed with inputs elicited from domain experts and extensive literature review, and refined with feedback obtained from selected expert builder and developer companies. This paper further demonstrates the application of the prototype MSDSS for selecting the most appropriate low-cost green building material from among a list of several available options, and finally concludes the study with the associated potential benefits of the model to research and practice.
文摘Accurate cost estimation at the early stage of a construction project is key factor in a project’s success. But it is difficult to quickly and accurately estimate construction costs at the planning stage, when drawings, documentation and the like are still incomplete. As such, various techniques have been applied to accurately estimate construction costs at an early stage, when project information is limited. While the various techniques have their pros and cons, there has been little effort made to determine the best technique in terms of cost estimating performance. The objective of this research is to compare the accuracy of three estimating techniques (regression analysis (RA), neural network (NN), and support vector machine techniques (SVM)) by performing estimations of construction costs. By comparing the accuracy of these techniques using historical cost data, it was found that NN model showed more accurate estimation results than the RA and SVM models. Consequently, it is determined that NN model is most suitable for estimating the cost of school building projects.
文摘A multi-layer adaptive optimizing parameters algorithm is developed forimproving least squares support vector machines (LS-SVM) , and a military aircraft life-cycle-cost(LCC) intelligent estimation model is proposed based on the improved LS-SVM. The intelligent costestimation process is divided into three steps in the model. In the first step, a cost-drive-factorneeds to be selected, which is significant for cost estimation. In the second step, militaryaircraft training samples within costs and cost-drive-factor set are obtained by the LS-SVM. Thenthe model can be used for new type aircraft cost estimation. Chinese military aircraft costs areestimated in the paper. The results show that the estimated costs by the new model are closer to thetrue costs than that of the traditionally used methods.
文摘背景:临床上血管支架的使用涉及高昂的医疗费用,但同时也可能在减少患者心血管事件、改善生活质量等方面带来长期的效益,而经济学评估可以帮助决策者更好地理解治疗方法的成本与效益之间的平衡。目的:分析卫生经济学相关文献,探讨血管支架效果与问题在医疗质量管理研究中的热点。方法:检索Web of Science核心集数据库关于血管支架的卫生经济学评价文献,采用VOSviewer_1.6.19软件对年度发文量、机构、国家和关键词等进行可视化分析,最后从卫生经济学和医疗质量管理角度分析血管支架效果与问题的研究热点。结果与结论:①最终纳入英文文献120篇,近10年此领域研究发文最高的年份是2019年,发文10篇,发文量最多的机构是美国哈佛大学(发文20篇),发文量最多的国家是美国(发文58篇)。②关键词聚类分析显示,裸金属支架和药物洗脱支架在冠脉疾病中的成本效果分析、血管成形术支架干预的成本效益分析、经皮冠状动脉介入治疗中应用冠脉支架的效果,这3个聚类研究方向为血管支架研究领域的卫生经济学评估的研究热点。③进一步总结医疗管理质量背景下血管支架治疗效果的研究热点为:血管支架的长期效果、安全性、药物释放机制研究、个体化治疗、再狭窄问题和支架镶嵌技术。④高被引文献分析结果显示,药物洗脱支架释放药物以减少血管再狭窄的风险,与裸金属支架相比再狭窄率较低,但通常成本较高;生物降解支架是结合裸金属支架和药物洗脱支架的优点,即避免长期的支架存在和减少再狭窄的风险,但它们的成本可能会更高,而且短期内可能会有一些并发症,目前应用并不广泛。⑤在进行血管支架成本效果比较时,除了直接的支架成本外,还需要考虑的因素包括支架再干预的风险和成本、并发症的风险和成本、药物治疗的持续时间和成本、患者的生活质量。因此,虽然药物洗脱支架和生物降解支架的初始成本可能高于裸金属支架,但它们可能在长期内带来更好的临床结果,从而产生更有利的成本效果。⑥未来的研究方向应注重个性化的血管支架治疗决策的制定、观察支架治疗的长期效果、支架对患者生活质量的影响、制定卫生政策、医疗资源合理分配及长期随访机制的建立。
