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Long Time Horizons (long + time_horizon)

Distribution by Scientific Domains

Business, Economics, Finance and Accounting	40%

Selected Abstracts

Reducing risk of shortages due to drought in water supply systems using genetic algorithms,

IRRIGATION AND DRAINAGE, Issue 2 2009
V. Nicolosi
évaluation des risques; gestion de l'eau; sécheresse; éléments déclenchant pour les plans sécheresse Abstract The evaluation of risk of shortages due to drought in water supply systems is a necessary step both in the planning and in the operation stage. A methodology for unconditional (planning) and conditional (operation) risk evaluation is presented in this study. The risk evaluation is carried out by means of an optimisation model based on genetic algorithms aimed to define thresholds for the implementation of mitigation measures tested through Monte Carlo simulation that makes use of a stochastic generation of streamflows. The GA enables the optimisation of reservoir storages which identify monthly thresholds for shifting three states of the system (normal, alert and alarm) to which correspond different mitigation measures such as water demand rationing, additional supplies from alternative sources or reduction of release for ecological use. For unconditional risk evaluation a long time horizon has been considered (40 years), while the conditional risk evaluation is performed on a short time horizon (2,3 months). Results of simulations have been studied by means of consolidated indices of performance and frequency analysis of shortages of a given entity corresponding to different planning/management policies. A multi-use water system has been used as a case study including competing irrigation and industrial demands. Copyright © 2008 John Wiley & Sons, Ltd. L'évaluation du risque de manques d'eau dus à la sécheresse dans les systèmes d'approvisionnement en eau est une étape nécessaire à la fois pour la planification et l'exploitation. Une méthodologie pour l'évaluation du risque inconditionnel (planification) et conditionnel (exploitation) est présentée dans cette étude. L'évaluation du risque est effectuée au moyen d'un modèle d'optimisation basé sur des algorithmes génétiques visant à définir des seuils pour la mise en ,uvre des mesures d'atténuation testés par une méthode de Monte Carlo générant les débits des rivières. L'algorithme génétique permet d'optimiser les stockages de réservoir avec des seuils mensuels pour identifier trois états du système (normal, alerte et alarme) auxquels correspondent différentes mesures d'atténuation telles que rationnement de la demande en eau, approvisionnements complémentaires par des sources alternatives ou réduction des lâchures pour l'usage écologique. Pour l'évaluation des risques inconditionnels un horizon à long terme a été considéré (40 ans) tandis que l'évaluation conditionnelle est faite sur un horizon à court terme (2 ou 3 mois). Les résultats des simulations ont été étudiés au moyen d'indices de performance consolidés et de l'analyse de la fréquence des manques d'eau pour une entité donnée correspondant à différentes politiques de planification et gestion. L'étude de cas porte sur un système multi-usage comportant une demande d'irrigation en concurrence avec les demandes industrielles. Copyright © 2008 John Wiley & Sons, Ltd. [source]

A new production function estimate of the euro area output gap,

JOURNAL OF FORECASTING, Issue 1-2 2010
Matthieu Lemoine
Abstract We develop a new version of the production function (PF) approach for estimating the output gap of the euro area. Assuming a CES (constant elasticity of substitution) technology, our model does not call for any (often imprecise) measure of the capital stock and improves the estimation of the trend total factor productivity using a multivariate unobserved components model. With real-time data, we assess this approach by comparing it with the Hodrick,Prescott (HP) filter and with a Cobb,Douglas PF approach with common cycle and implemented with a multivariate unobserved components model. Our new PF estimate appears highly concordant with the reference chronology of turning points and has better real-time properties than the univariate HP filter for sufficiently long time horizons. Its inflation forecasting power appears, like the other multivariate approach, less favourable than the statistical univariate method. Copyright © 2009 John Wiley & Sons, Ltd. [source]

Using limiting factors analysis to overcome the problem of long time horizons

NEW DIRECTIONS FOR EVALUATION, Issue 122 2009
Raymond Gullison
In recent years, donors to biodiversity conservation projects have sought greater accountability, using professional evaluators to help assess the degree to which grantees are achieving conservation objectives. One of the most formidable challenges evaluators face is the time required both for ecological systems to respond to management interventions and over which grantees must maintain their biodiversity conservation gains. The authors present a simple methodology, called limiting factors analysis, which was developed during the course of evaluating several large portfolios of conservation projects. The method is a practical basis for rapidly assessing whether current conditions are likely to prevent grantees from achieving their long-term objectives. Use of the methodology is illustrated with examples from recent evaluations of the Andes Amazon Initiative and the Columbia Basin Water Transactions Program. © Wiley Periodicals, Inc. [source]

The sourcing of technological knowledge: distributed innovation processes and dynamic change

R & D MANAGEMENT, Issue 4 2003
Jeremy Howells
This paper outlines the knowledge and technology sourcing practices of a range of key firms and organisations across the UK based on primary research, and analyses the key factors related to managing the technological knowledge boundaries of the firm. In particular, the paper considers the dynamic dimension considerations to such issues. As such it outlines important differences between short and long time horizons, before analysing in more detail some of the implications for firms of technological change over the long term. The paper seeks to highlight the importance of the time dimension in helping to explain why and how firms source technological knowledge externally and how they align their sourcing activities to their strategies associated with developing current and future capabilities. [source]

Mechanistic model for prediction of formate dehydrogenase kinetics under industrially relevant conditions

BIOTECHNOLOGY PROGRESS, Issue 1 2010
T. Schmidt
Abstract Formate dehydrogenase (FDH) from Candida boidinii is an important biocatalyst for the regeneration of the cofactor NADH in industrial enzyme-catalyzed reductions. The mathematical model that is currently applied to predict progress curves during (semi-)batch reactions has been derived from initial rate studies. Here, it is demonstrated that such extrapolation from initial reaction rates to performance during a complete batch leads to considerable prediction errors. This observation can be attributed to an invalid simplification during the development of the literature model. A novel mechanistic model that describes the course and performance of FDH-catalyzed NADH regeneration under industrially relevant process conditions is introduced and evaluated. Based on progress curve instead of initial reaction rate measurements, it was discriminated from a comprehensive set of mechanistic model candidates. For the prediction of reaction courses on long time horizons (>1 h), decomposition of NADH has to be considered. The model accurately describes the regeneration reaction under all conditions, even at high concentrations of the substrate formate and thus is clearly superior to the existing model. As a result, for the first time, course and performance of NADH regeneration in industrial enzyme-catalyzed reductions can be accurately predicted and used to optimize the cost efficiency of the respective processes. © 2009 American Institute of Chemical Engineers Biotechnol. Prog., 2010 [source]