Search results for "Forecast"

Ten important articles on noninvasive ventilation in critically ill patients and insights for the future: A report of expert opinions

2017

Background Noninvasive ventilation is used worldwide in many settings. Its effectiveness has been proven for common clinical conditions in critical care such as cardiogenic pulmonary edema and chronic obstructive pulmonary disease exacerbations. Since the first pioneering studies of noninvasive ventilation in critical care in the late 1980s, thousands of studies and articles have been published on this topic. Interestingly, some aspects remain controversial (e.g. its use in de-novo hypoxemic respiratory failure, role of sedation, self-induced lung injury). Moreover, the role of NIV has recently been questioned and reconsidered in light of the recent reports of new techniques such as high-fl…

Assessment of the Present and Future Offshore Wind Power Potential: A Case Study in a Target Territory of the Baltic Sea Near the Latvian Coast

2013

Offshore wind energy development promises to be a significant domestic renewable energy source in Latvia. The reliable prediction of present and future wind resources at offshore sites is crucial for planning and selecting the location for wind farms. The overall goal of this paper is the assessment of offshore wind power potential in a target territory of the Baltic Sea near the Latvian coast as well as the identification of a trend in the future wind energy potential for the study territory. The regional climate model CLM and High Resolution Limited Area Model (Hirlam) simulations were used to obtain the wind climatology data for the study area. The results indicated that offshore wind en…

Forecasting the onset of an allergic risk to poaceae in Nancy and Strasbourg (France) with different methods

2008

International audience; Pollen of Poaceae is among the most allergenic pollen in Europe with pollen of birch. It is therefore useful to elaborate models to help pollen allergy sufferers. The objective of this study was to construct forecast models that could predict the first day characterized by a certain level of allergic risk called here the Starting Date of the Allergic Risk . Models result from four forecast methods (three summing and one multiple regression analysis) used in the literature. They were applied on Nancy and Strasbourg from 1988 to 2005 and were tested on 2006. Mean Absolute Error and Actual forecast abili ty test are the parameters used to choose best models, assess and …

E-MIP: A new mechanism for dynamic coalition formation in a robot team

2004

When mobile robots colonies move in dynamic, not predictable and time variable environments, the problem now is on how can they achieve distributed solving strategies for solving complicate and difficult tasks. The development of a new robotic architecture for the coordination of robot colonies in dangerous and dynamic environments is outlined. The name of this new architecture is Economic Metaphor of Italian Politics (E-MIP), because it takes inspiration from the political organizations of Italian democratic governments, where the leader isn't only one robot but a government of three robots constitutes it while a second group of robots, the Robot Citizens, are the executor of the mission. …

Early Warning Systems for Food Security in West Africa: Evolution, Achievements and Challenges

2010

In West Africa, early warning systems (EWSs) for food security have been widely recognized to have contributed, in the last 20 years, to an improved ability to deal with famine emergencies. Nevertheless, despite the advancements in understanding of the environmental and socio-economic dynamics and despite the improved technologies, tackling food security remains a difficult task for decision makers as demonstrated by local food crises in many countries of the region. African Monsoon Multidisciplinary Analysis, while improving the understanding of the monsoon system, allowed us to better orient research challenges to provide EWS with improved products, effectively meeting the needs of end-us…

2014

Sales forecasting is an essential task in retailing. In particular, consumer-oriented markets such as fashion and electronics face uncertain demands, short life cycles and a lack of historical sales data which strengthen the challenges of producing accurate forecasts. This survey paper presents state-of-the-art methods in the sales forecasting research with a focus on fashion and new product forecasting. This study also reviews different strategies to the predictive value of user-generated content and search queries.

Comment améliorer la prévision des ventes pour le marketing ? Les apports de la théorie du chaos

2013

National audience; La littérature en marketing constate un décalage entre les avancées réalisées par les chercheurs qui développent de nouvelles méthodes de prévision des ventes, et l'usage massif de méthodes traditionnelles reposant sur l'hypothèse de linéarité des processus analysés. Cette recherche expose la contribution poten¬tielle de la théorie du chaos à l'amélioration de la prévision des ventes. Une illustration de ces apports est proposée avec une application à la prévision des ventes de consoles de jeux vidéo au Japon. Les résultats mettent en évidence la capacité de la méthode proposée à détecter la présence de chaos dans la série et montrent la possibilité de préciser l'horizon …

A new method for forecasting energy output of a large-scale solar power plant based on long short-term memory networks a case study in Vietnam

2021

Abstract This paper proposes a new model for short-term forecasting power generation capacity of large-scale solar power plant (SPP) in Vietnam considering the fluctuations of weather factors when applying the Long Short-Term Memory networks (LSTM) algorithm. At first, a configuration of the model based on the LSTM algorithm is selected in accordance with the weather and operating conditions of SPP in Vietnam. Not only different structures of LSTM model but also other conventional forecasting methods for time series data are compared in terms of error accuracy of forecast on test data set to evaluate the effectiveness and select the most suitable LSTM configuration. The most suitable config…

An improvement of June-September rainfall forecasting in the Sahel based upon region April-May moist static energy content (1968-1997)

1999

This study provides statistical evidence that June–September Sahelian rainfall hindcasts currently based on oceanic thermal predictors apprehend more the negative trend than the interannual rainfall variations. Four physically meaningful predictors of June–September Sahel rainfall are first selected through the near-surface April–May information and several experimental hindcasts provided. We then discuss the skills achieved using regression techniques and cross-validated discriminant functions. In that context, 8/11 of the driest seasons and 8/10 of the wettest are correctly predicted. Finally using completely independent training and working periods we show that better and significant hin…

Forecasting daily urban electric load profiles using artificial neural networks

2004

The paper illustrates a combined approach based on unsupervised and supervised neural networks for the electric energy demand forecasting of a suburban area with a prediction time of 24 h. A preventive classification of the historical load data is performed during the unsupervised stage by means of a Kohonen's self organizing map (SOM). The actual forecast is obtained using a two layered feed forward neural network, trained with the back propagation with momentum learning algorithm. In order to investigate the influence of climate variability on the electricity consumption, the neural network is trained using weather data (temperature, relative humidity, global solar radiation) along with h…