Sk Nasir Ahmed

sk_nasir_ahmadPredoctoral Fellow 2014-2015, Institute for Environmental Science and Policy

Network Analysis of Resource Consumption Patterns
The world around us is changing rapidly and so do our trends and patterns in energy and resource consumption. For a more sustainable world, we need to be better able to capture and track our trends in energy and resource consumption in order to maintain the balance among people, planet and prosperity, commonly known as triple bottom line of sustainability.

Traditionally, statistical tools (e.g., mean, median, standard deviation) have been widely used to gage and assess trends and patterns in energy and resource consumption. With the advancement in data collection and data storage technology, however, modern datasets are becoming too large. Moreover, standard indicators used widely to analyze those data can fail to capture a meaningful output, and the processing and visualization of these datasets is also becoming a major challenge. Furthermore, datasets often contain inherent errors and outliers that can skew a distribution and significantly bias the results. Consequently, new mathematical and statistical tools are required to address these issues. The main objective of my research is to formalize a novel network methodology, apply it to datasets from the World Bank Data Catalogue, model the outcomes of the methodology using machine learning techniques and provide a GIS and JavaScript platform to visualize the results. The results will help compare countries with similar development standard, and thus aid policy makers and planners to build a more sustainable world. This methodology has already been implemented on US water consumption data and the results were extremely encouraging.[1]

  1. N. Ahmad and S. Derrible, “Evolution of Public Supply Water Withdrawal in the USA: A Network Approach: Water Withdrawal in the USA: A Network Approach,” J. Ind. Ecol., vol. 19, no. 2, pp. 321–330, Apr. 2015.


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