Wencui Chen

Abstract: Highway construction project does not exist for its own, but also to meet the needs of the society. Its development strategy should be based on the overall goal of the society, not just for its own. Therefore, the sustainable evaluation of the highway construction should be considered from the two parts of sustainability of social needs and economic development. In this paper, using the BP neural network algorithm, through the analysis of sustainable development of the following four areas in road construction: economics, environmental resources, operations, management systems and policy, the author studies the sustainable development evaluation of highway construction project.

Abstract: The working hypothesis of this study revolves around the lack of integration of sustainability and project management. Organisations, nowadays are increasingly keen on to include sustainability in their business. Project management can help make this process a success but little guidance is available on how to apply sustainability to specific projects. This work has analysed connections between the two disciplines by means of a comprehensive literature review covering more than 100 references. Sustainability has become a very important step, particularly in terms of environmental aspects. However, slightly less progress has been made socially. In any case, the ideal characteristics for a project and its management might be considered sustainable have still not been specified to this day. The main scientific contribution of this article is a new conceptual framework helping project managers deal with sustainable projects. This framework is based on the supposition that project products designed using sustainability criteria, sustainable project processes, organisations committed to sustainability that carry out projects, and project managers trained in sustainability are all necessary elements, although, maybe not enough, to attain sustainable projects. In addition, the article suggests a future research agenda that might specify how project management can help incorporate sustainability into organisations and their projects.

Abstract: Electricity is a special energy which is hard to store, so the electricity demand forecasting remains an important problem. Accurate short-term load forecasting (STLF) plays a vital role in power systems because it is the essential part of power system planning and operation, and it is also fundamental in many applications. Considering that an individual forecasting model usually cannot work very well for STLF, a hybrid model based on the seasonal ARIMA model and BP neural network is presented in this paper to improve the forecasting accuracy. Firstly the seasonal ARIMA model is adopted to forecast the electric load demand day ahead; then, by using the residual load demand series obtained in this forecasting process as the original series, the follow-up residual series is forecasted by BP neural network; finally, by summing up the forecasted residual series and the forecasted load demand series got by seasonal ARIMA model, the final load demand forecasting series is obtained. Case studies show that the new strategy is quite useful to improve the accuracy of STLF.

Abstract: Making sustainable decisions is a major concern for government departments seeking to develop best practices and innovative methods to deal with complex decision-making problems. This article is concerned with decision-making in sustainable development contexts, which must guarantee a long-term balance between environmental integrity, social equality and economic efficiency, in addition to evaluating options over the short, medium and long term. This article provides an up-to-date survey of research that evaluates the sustainability of decisions and puts forward an innovative multi-period single synthesizing criterion approach for selecting projects in sustainable development contexts. The proposed approach is then used to select the best compromise out of several sustainable forest management options while considering economic benefits, environmental impact and decision-maker preferences.

Abstract: The suitability of the project delivery system (PDS) selected for a project greatly influences the efficiency of project implementation. In Iran, traditional design-bid-build (DBB) is commo...

Abstract: To enable efficient managerial decisions in planning and generation of construction process, we need technologies to analyze and evaluate their conditions and to predict their further evolution. One of advanced methods to generate them is based on artificial neural networks (ANN). This paper represents the outcome from a research in construction process organization and management to build roof structures at the planning and operation stage, assisted by the ANN methodology. Relying on systems analysis and expert survey, the authors have designed a 4-layer feedforward ANN with a node pattern of 15-6-3-1. The authors used the concept of fuzzy sets to measure input and output of the network. The paper clearly illustrates the function of ANN and describes the learning algorithm by the backward propagation of errors relative to the resulting ANN. The authors have identified problems related to generation of the labeled training data in the researched field and developed a network learning approach that combines extraction of expert knowledge about the system with learning on training examples from real-life construction project.