A novel improved model for building energy consumption prediction based on model integration

Building energy consumption prediction plays an irreplaceable role in energy planning, management, and conservation. Constantly improving the performance of prediction models is the key to ensuring the efficient operation of energy systems. Moreover, accuracy is no longer the only factor in revealing model performance, it is more important to evaluate the model from multiple perspectives, considering the characteristics of engineering applications. Based on the idea of model integration, this paper proposes a novel improved integration model (stacking model) that can be used to forecast building energy consumption. The stacking model combines advantages of various base prediction algorithms and forms them into “meta-features” to ensure that the final model can observe datasets from different spatial and structural angles. Two cases are used to demonstrate practical engineering applications of the stacking model. A comparative analysis is performed to evaluate the prediction performance of the stacking model in contrast with existing well-known prediction models including Random Forest, Gradient Boosted Decision Tree, Extreme Gradient Boosting, Support Vector Machine, and K-Nearest Neighbor. The results indicate that the stacking method achieves better performance than other models, regarding accuracy (improvement of 9.5%–31.6% for Case A and 16.2%–49.4% for Case B), generalization (improvement of 6.7%–29.5% for Case A and 7.1%-34.6% for Case B), and robustness (improvement of 1.5%–34.1% for Case A and 1.8%–19.3% for Case B). The proposed model enriches the diversity of algorithm libraries of empirical models

OPEC’s oil exporting strategy and macroeconomic (in)stability

Aguiar-Conraria and Wen (2008) argued that dependence on foreign oil raises the likelihood of equilibrium indeterminacy (economic instability) for oil importing countries. We argue that this relation is more subtle. The endogenous choices of prices and quantities by a cartel of oil exporters, such as the OPEC, can affect the directions of the changes in the likelihood of equilibrium indeterminacy. We show that fluctuations driven by self-fulfilling expectations under oil shocks are easier to occur if the cartel sets the price of oil, but the result is reversed if the cartel sets the quantity of production. These results offer a potentially interesting explanation for the decline in economic volatility (i.e., the Great Moderation) in oil importing countries since the mid-1980s when the OPEC cartel changed its market strategies from setting prices to setting quantities, despite the fact that oil prices are far more volatile today than they were 30 years ago.>Organization of Petroleum Exporting Countries ; Petroleum industry and trade

Advances in the Design and Implementation of a Multi-Tier Architecture in the GIPSY Environment

We present advances in the software engineering design and implementation of the multi-tier run-time system for the General Intensional Programming System (GIPSY) by further unifying the distributed technologies used to implement the Demand Migration Framework (DMF) in order to streamline distributed execution of hybrid intensional-imperative programs using Java.Comment: 11 pages, 3 figure

A demand-driven approach for a multi-agent system in Supply Chain Management

This paper presents the architecture of a multi-agent decision support system for Supply Chain Management (SCM) which has been designed to compete in the TAC SCM game. The behaviour of the system is demand-driven and the agents plan, predict, and react dynamically to changes in the market. The main strength of the system lies in the ability of the Demand agent to predict customer winning bid prices - the highest prices the agent can offer customers and still obtain their orders. This paper investigates the effect of the ability to predict customer order prices on the overall performance of the system. Four strategies are proposed and compared for predicting such prices. The experimental results reveal which strategies are better and show that there is a correlation between the accuracy of the models' predictions and the overall system performance: the more accurate the prediction of customer order prices, the higher the profit. © 2010 Springer-Verlag Berlin Heidelberg

Towards a typology for systemic financial instability

This article seeks to provide a categorisation of events of systemic financial instability that have been experienced in recent decades, seeking to draw out common elements from these seemingly-diverse events. We maintain that despite the apparent diversity of events of financial instability, a useful summary categorisation is between bank, market-price and market-liquidity based crises. There are important subcategories of each type, such as domestic versus international, currency crisis linked, single-institution based, equity-related, property, commodities, deregulation and disintermediation linked crises. Such financial crises are usefully examined in the light of the theories of financial instability, not least to illuminate common generic patterns that can be helpful in macroprudential surveillance. We derive a framework for analysing the evolution of such crises, highlighting that it is vulnerability of a financial system that is the key common element to a crisis, besides the nature of propagation of a crisis to the wider economy. Besides having general applicability, notably to OECD countries, the typology and generic features have some relevant implications for euro area countries. Development of securities markets, the likelihood of regional crises and the likely impact of ageing are among aspects that warrant vigilance by policy makers in the euro zone