Ranking Volatility in Building Energy Consumption Using Ensemble Learning and Information Entropy

Given the rise in building energy consumption and demand worldwide, energy inefficiency detection has become extremely important. A significant portion of the energy used in commercial buildings is wasted as a result of poor maintenance, degradation or improperly controlled equipment. Most facilities employ sensors to track energy consumption across multiple buildings. Smart fault detection and diagnostic systems use various anomaly detection techniques to discover point anomalies in consumption. While these systems work reasonably well in detecting equipment anomalies over short-term intervals, further exploration is needed in finding methods that consider long-term consumption to detect anomalous buildings. This paper presents a novel approach for a multi-building campus to rank and visualize the long-term volatility of building consumption. This allows for the optimal allocation of limited time and resources for the detection and resolution of energy waste. The proposed method first classifies daily consumption into 5 classes using an ensemble learner and then calculates the information entropy on the resulting classification set to determine volatility. The ensemble learner receives input from a K-Nearest Neighbor classifier, a Random Forest classifier and an Artificial Neural Network. In general, buildings are expected to keep the same energy profile over time, all else being equal. Buildings that frequently change energy profiles are ranked and flagged by the system for review, which would call for the next step to reduce waste and costs and to increase the sustainability of buildings. Data on energy consumption for 132 buildings is obtained from energy management at the Georgia Institute of Technology. Experimental results show the effectiveness of the proposed approach

Entity-Centric Abstraction and Modeling Framework for Transportation Architectures

A comprehensive framework for representing transpportation architectures is presented. After discussing a series of preceding perspectives and formulations, the intellectual underpinning of the novel framework using an entity-centric abstraction of transportation is described. The entities include endogenous and exogenous factors and functional expressions are offered that relate these and their evolution. The end result is a Transportation Architecture Field which permits analysis of future concepts under the holistic perspective. A simulation model which stems from the framework is presented and exercised producing results which quantify improvements in air transportation due to advanced aircraft technologies. Finally, a modeling hypothesis and its accompanying criteria are proposed to test further use of the framework for evaluating new transportation solutions

An Integrated Decision-Making Framework for Transportation Architectures: Application to Aviation Systems Design

The National Transportation System (NTS) is undoubtedly a complex system-of-systems---a collection of diverse 'things' that evolve over time, organized at multiple levels, to achieve a range of possibly conflicting objectives, and never quite behaving as planned. The purpose of this research is to develop a virtual transportation architecture for the ultimate goal of formulating an integrated decision-making framework. The foundational endeavor begins with creating an abstraction of the NTS with the belief that a holistic frame of reference is required to properly study such a multi-disciplinary, trans-domain system. The culmination of the effort produces the Transportation Architecture Field (TAF) as a mental model of the NTS, in which the relationships between four basic entity groups are identified and articulated. This entity-centric abstraction framework underpins the construction of a virtual NTS couched in the form of an agent-based model. The transportation consumers and the service providers are identified as adaptive agents that apply a set of preprogrammed behavioral rules to achieve their respective goals. The transportation infrastructure and multitude of exogenous entities (disruptors and drivers) in the whole system can also be represented without resorting to an extremely complicated structure. The outcome is a flexible, scalable, computational model that allows for examination of numerous scenarios which involve the cascade of interrelated effects of aviation technology, infrastructure, and socioeconomic changes throughout the entire system.Ph.D.Committee Chair: Schrage, Daniel P.; Committee Co-Chair: Mavris, Dimitri N.; Committee Member: Amy R. Pritchett; Committee Member: DeLaurentis, Daniel A.; Committee Member: Moore, Mark D.; Committee Member: Wilhite, Ala

A Spotlight Search Method for Multi-criteria Optimization Problems

Presented at the 9th AIAA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, Atlanta, GA, September 4-6, 2002.This paper intended to be an entry for graduate student paper competition. But the committee had cancelled the session for some reason and decided to accept this paper as a ?normal? paper instead.In many engineering applications including multidisciplinary optimization (MDO) problems, a decision maker often tends to evaluate and optimize multiple criteria at the same time to carry out a tradeoff study. Nevertheless, solving a multi-criteria optimization (MCO) problem, in general, is a difficult practice. Numerous methods have been proposed and applied to various applications over the past few decades. This paper introduces a new MCO method suitable for continuous, nonlinear MCO problems. The concept of the proposed method, a spotlight search method (SSM), is easily comprehendible and its implementation is simple and straightforward. Mathematical formulations show that this method can be considered as a variation of the goal attainment method (GAM). Five test problems are selected and numerical experiments are presented to demonstrate the usefulness of SSM with comparison to GAM. It is observed that SSM finds the Pareto front more efficiently for all test problems

Entity-Centric Abstraction and Modeling of Future Transportation Architectures

Presented is a foundational, embryonic frame of reference for contemplating future transportation architectures open to practically any configuration, seeking innovation in transportation not through a particular technology but through a new way of thinking. The approach foregoes the usual employment of a reductionism perspective in favor of the view that one must first understand the whole before the individual parts of a complex system are designed, for the essence of the problem likely appears only from this holistic perspective. Nevertheless, it does not necessarily make communication between the involved facets any easier. An effective lexicon is proposed to bridge the gap between understanding and communication across the multiple domains that under-gird transportation. The holistic perspective with an effective lexicon establishes the foundation for the primary thrust of the paper: the establishment of an entity-centric abstraction framework that allows practitioners and theorists to navigate, communicate, model and design collaboratively as well as produce a useful product to the decision makers. The framework effectively guides modeling in such a way that nearly any conceivable combination of transportation resources, economies or policies is admissible. Overlaid with socioeconomic data and utilizing an agent-based modeling technique, simulation studies are reported upon for the dual purpose of documenting the use of the entity-centric abstraction approach as well as to expose key findings concerning the potential benefit of emerging aviation technologies

Abstraction and Modeling Hypothesis for Future Transportation Architectures

AIAA/ICAS International Symposium: The Next 100 Years, Dayton, OH, July 14-17, 2003.The goal of a future transportation architecture is an expansion in mobility, enabling new types of travel and commerce currently not affordable and thus producing induced societal benefit. From the design perspective, the complexity, high dimensionality and diverse nature of the design space make study of such architectures extremely difficult. An abstraction framework and modeling hypothesis are proposed, steps vital to the proper start of such an aggressive challenge. The core entities within a transportation architecture are abstracted: stakeholders (consumers, regulators, service providers, etc.), resources (vehicles, infrastructure, etc.) and networks (both explicit for resources and implicit for stakeholders). This abstraction leads to a general description for transportation that is useful from a conceptual modeling point of view stakeholders employ particular resources, organized in networks, in order to achieve mobility objectives. The modeling hypothesis is created stemming from the description and focused upon the need to examine the architecture from a system-of-systems perspective, under the belief that the organization of transportation resources is just as important as the nature and performance of those resources. Subsets of the methodologies are tested on three exploratory research thrusts and the findings are used to project a future path towards full validation of the modeling hypothesis. Ultimately, decision-makers at multiple levels can use the methodologies to quickly understand and visualize the relative merits of alternative architectures

A Methodology for Assessing Business Models of Future Air Transportation in the Atlanta Regional Transportation System

Presented at the 4th AIAA ATIO Conference, Chicago, IL, September 20-23, 2004.A methodology employing physics-based and economics-based tools in conjunction with probabilistic treatment is developed to study Personal Air Vehicle business model. In the context of the paper, a business model is a mathematical representation of a service provider business operation. Vehicle concepts and hypothesized metrics such as mobility freedom and 'value of time'are embedded in the methodology. Market behavior of the complex transportation environment is captured as part of the equation through Agent-based Modeling and Monte Carlo Simulation techniques. This simulation platform for the transportation environment facilitates the case study of the Atlanta Regional Transportation System. The establishment of this model lays the foundation for creating a robust and adaptive design methodology that allows experts in fields other than aerospace engineering to contribute their expertise towards the realization of this very diverse and dynamic future air transportation system

An Integrated Decision-making Method to Identify Design Requirements Through Agent-based Simulation for Personal Air Vehicle System

Presented at AIAA Aircraft Technology, Integration, and Operation (ATIO) Technical Forum, October 1-3, 2002, Los Angeles, CA.A product?s design requirements guide the next development efforts. Thus, correct decision-making is critical in generating design requirements as vehicle concepts are being formulated. A new method is proposed to account for system-of-systems aspects and to aid a decision-making process in synthesizing design requirements for a personal air vehicle system. The use of an agent-based modeling technique facilitates the abstraction of the key elements in the whole system. A traveling party is treated as an agent, and the infrastructure environment in the national transportation system is easily represented in the model. A number of simulations are performed to demonstrate the capability of this new approach. The method not only measures the effect of design requirements of a personal air vehicle system through sensitivity analyses, but also evaluates the effect of system technologies quantitatively, while maintaining the system-of-systems perspective. With this powerful method, designers can extract essential technical requirements that allow polishing of concept vehicles; policy makers can investigate the infrastructure and technology impact of new systems; and business planners can perform an analysis based on their own market assumptions