Whole-Process Project Cost Management Based on Building Information Modeling (BIM)

The whole-process project cost management based on building information modeling(BIM)is a new management method,aiming to realize the comprehensive optimization and improvement of project cost management through the application of BIM technology.This paper summarizes and analyzes the whole-process project cost management based on BIM,aiming to explore its application and development prospects in the construction industry.Firstly,this paper introduces the role and advantages of BIM technology in engineering cost management,including information integration,data sharing,and collaborative work.Secondly,the paper analyzes the key technologies and methods of the whole-process project cost management based on BIM,including model construction,data management,and cost control.In addition,the paper also discusses the challenges and limitations of the whole-process BIM project cost management,such as the inconsistency of technical standards,personnel training,and consciousness change.Finally,the paper summarizes the advantages and development prospects of the whole-process project cost management based on BIM and puts forward the direction and suggestions for future research.Through the research of this paper,it can provide a reference for construction cost management and promote innovation and development in the construction industry.

Control and Management of Construction Project Cost

Project cost can control the input in construction project and improve economic benefits of construction enterprises,so it is an important section of construction engineering.Reasonable control and management of project cost is the principle that building units must obey in the whole process of project,particularly in the construction stage,so it is extremely important to control and manage the project cost.This paper first analyzed possible causes for the unreasonable cost of construction projects,and put forward pertinent strategies for the control and management of construction project cost.

Research on the Development of Project Cost Informatization in the Era of Big Data

Under the background of big data,Informatization plays an important role in the development of the engineering cost industry.The rapid development of the industry and the increasing complexity of construction projects require higher standards of informatization.The current information processing methods and models have been difficultly to meet new requirements.Based on this,this study deeply analyzes the key factors that impede the informatization of engineering cost development,and tries to find corresponding solutions through theoretical analysis and empirical research to break these constraints.This will play a guiding role in the development of informatization in China's engineering cost industry.

Cost Risk Appraisal： An Application of Project RiskManagement Process in Libyan Construction Projects

Projects delay and cost overrun have become general facts in the construction industry. Project cost risk analysis considers the different costs associated with a project and focuses on the uncertainties and risks that may affect these costs. An implementation of PRM （project risk management） process on regional construction project has been carried out to maximize the likelihood of project meeting its objectives within its constraints. Qualitative and quantitative risk analyses have been carried out. The qualitative analysis is presented in a table that shows top ranked risks in Libyan construction projects based on probability-impact grid technique. In quantitative risk analyses, Mont Carlo simulation technique has been conducted to quantify and evaluate the overall level of risk exposure associated with the project completion cost. A project simulation uses a model that translates cost uncertainties into their potential impact on project objectives. A frequency curve model that represents simulation results of project completion costs has been constructed. The frequency curve model shows all possible outcomes of expected project cost at different probabilities. Project manager or decision maker can select the appropriate project budget. If a probability of 0.95 confident project budget is selected that means cost overrun risk can be minimized to a probability of 0.05. It is very helpful for project manager to take decisions based on information that shows project completion cost and its associated probability rather than usin single information of estimated cost.

Discussion on Construction Project Cost Composition and Its Management

That budget estimate exceeds estimate, budget exceeds budget estimate, and actual budget exceeds budget usually exists in the management of construction project cost, suggesting the cost management and control of construction project are not the management and control of product cost in a general sense. In terms of construction project, cost management and control is the core of the project and is implemented throughout all stages of the project, so it is complicated system engineering. In this paper, construction project cost composition and its management measures are mainly discussed.

Research and Application of Construction Project Cost Control in Engineering Bidding Stage

In order to strengthen cost control in construction project bidding stage, this paper takes the price control in bidding stage as the main line, dedicated to determine the key point in the stage of cost control, and establishes the more objective and reasonable evaluation in view of the comprehensive evaluation method, and combined with the practical application of engineering to demonstrate. This paper not only improved the tendering and bidding stage method of cost control in construction project in our country, and improves the method system of engineering cost control.

Effective control of the project cost in the project implementation

After the completion of design, the construction project shall begin its implementation, which should be taken effective measures to strengthen the management of project cost and properly manage the funds to achieve the overall goal of the construction projects. Control of the project cost in the project implementation is mainly divided into bidding, contracting, construction and settlement. The following is the analysis and discussions of the author＇s experiences to the control of the project cost in the project implementation and the management measures.

Exploring the Digital Talent Training Mode of Project Cost Specialty in Higher Vocational Colleges

Project construction,design,management,operation,and maintenance are all undergoing digital transformations,and project cost professionals’working mode and content will change as a result.This paper reviews the existing challenges in traditional talent training and adjusts training ideas as well as training modes to conform to the industry’s digital transformation trend as a training base for project cost talents.

Nationwide trends and predictors of inpatient mortality in 83884 transjugular intrahepatic portosystemic shunt

AIM: To evaluate and validate the national trends and predictors of in-patient mortality of transjugular intrahepatic portosystemic shunt (TIPS) in 15 years.METHODS: Using the National Inpatient Sample which is a part of Health Cost and Utilization Project, we identified a discharge-weighted national estimate of 83884 TIPS procedures performed in the United States from 1998 to 2012 using international classification of diseases-9 procedural code 39.1. The demographic, hospital and co-morbility data were analyzed using a multivariant analysis. Using multi-nominal logistic regression analysis, we determined predictive factors related to increases in-hospital mortality. Comorbidity measures are in accordance to the Comorbidity Software designed by the Agency for Healthcare Research and Quality.RESULTS: Overall, 12.3% of patients died during hospitalization with downward trend in-hospital mortality with the mean length of stay of 10.8 ± 13.1 d. Notable, African American patients (OR = 1.809 vs Caucasian patients, P < 0.001), transferred patients (OR = 1.347 vs non-transferred, P < 0.001), emergency admissions (OR = 3.032 vs elective cases, P < 0.001), patients in the Northeast region (OR = 1.449 vs West, P < 0.001) had significantly higher odds of in-hospital mortality. Number of diagnoses and number of procedures showed positive correlations with in-hospital death (OR = 1.249 per one increase in number of procedures). Patients diagnosed with acute respiratory failure (OR = 8.246), acute kidney failure (OR = 4.359), hepatic encephalopathy (OR = 2.217) and esophageal variceal bleeding (OR = 2.187) were at considerably higher odds of in-hospital death compared with ascites (OR = 0.136, P < 0.001). Comorbidity measures with the highest odds of in-hospital death were fluid and electrolyte disorders (OR = 2.823), coagulopathy (OR = 2.016), and lymphoma (OR = 1.842).CONCLUSION: The overall mortality of the TIPS procedure is steadily decreasing, though the length of stay has remained relatively constant. Specific patient ethnicity, location, transfer status, primary diagnosis and comorbidities correlate with increased odds of TIPS in-hospital death.

Prediction model for cost data of a power transmission and transformation project based on Pearson correlation coefficient-IPSO-ELM

In view of the difficulty in predicting the cost data of power transmission and transformation projects at present,a method based on Pearson correlation coefficient-improved particle swarm optimization(IPSO)-extreme learning machine(ELM)is proposed.In this paper,the Pearson correlation coefficient is used to screen out the main influencing factors as the input-independent variables of the ELM algorithm and IPSO based on a ladder-structure coding method is used to optimize the number of hidden-layer nodes,input weights and bias values of the ELM.Therefore,the prediction model for the cost data of power transmission and transformation projects based on the Pearson correlation coefficient-IPSO-ELM algorithm is constructed.Through the analysis of calculation examples,it is proved that the prediction accuracy of the proposed method is higher than that of other algorithms,which verifies the effectiveness of the model.

Optimization design of anti-seismic engineering measures for intake tower based on non-dominated sorting genetic algorithm-Ⅱ

High-rise intake towers in high-intensity seismic areas are prone to structural safety problems under vibration.Therefore,effective and low-cost anti-seismic engineering measures must be designed for protection.An intake tower in northwest China was considered the research object,and its natural vibration characteristics and dynamic response were first analyzed using the mode decomposition response spectrum method based on a three-dimensional finite element model.The non-dominated sorting genetic algorithm-II(NSGA-II)was adopted to optimize the anti-seismic scheme combination by comprehensively considering the dynamic tower response and variable project cost.Finally,the rationality of the original intake tower antiseismic design scheme was evaluated according to the obtained optimal solution set,and recommendations for improvement were proposed.The method adopted in this study may provide significant references for designing anti-seismic measures for high-rise structures such as intake towers located in high-intensity earthquake areas.