https://isfcolombia.uniandes.edu.co/images/201519/LRD22.pdf

Using project management as a way to sustainability. From a comprehensive review to a framework definition

Multicriteria decision making for sustainable development: A systematic review

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...

Performance Analysis of Alternative Contracting Methods for Highway Construction Projects: Case Study for Iran

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.

/pdf/a-new-strategy-for-short-term-load-forecasting-2tektj7197.pdf

A New Strategy for Short-Term Load Forecasting

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.

Mingshun Li

Papers

Application of BP Neural Network Algorithm in Sustainable Development of Highway Construction Projects