Search results for "Decision support system"
showing 10 items of 306 documents
Inferring Decision Strategies from Clickstreams in Decision Support Systems: A New Process-Tracing Approach using State Machines
2011
The importance of online shopping has grown remarkably over the last decade. In 2009, every West European spent on average € 483 online and this amount is expected to grow to € 601 in 2014. In Germany, the number of online shoppers has almost doubled since 2000: 44% of all adults regularly buy products onlinetoday. In Western Europe, online sales reached € 68 billion in 2009 and Forrester research forecasts it will reach € 114 billion by 2014 with an 11% compound annual growth rate.
Global Cropland Yield Monitoring with Gaussian Processes
2021
Agriculture monitoring, and in particular food security, requires near real-time information on crop growing conditions for early detection of possible production deficits. In this work, we propose the use of Gaussian processes (GPs). together with in-situ, EO and ERA-Interim climate reanalysis data for crop yield forecasting. Country-level agricultural survey data from FAOSTAT are used for quantitative assessment. The study is conducted in the framework of the ASAP (Anomaly hot Spots of Agricultural Production) early warning decision support system of the European Commission, which aims at providing timely information about possible crop production anomalies worldwide. After grouping count…
Integrated Computer-Aided Innovation: The PROSIT approach
2009
Abstract The paper presents a methodology aimed at the improvement of the product development cycle through the integration of Computer-Aided Innovation (CAI) with Optimization and PLM systems. The interoperability of these tools is obtained through the adoption of Optimization systems as a bridging element between CAI and PLM systems. This methodology was developed within the PROSIT project ( http://www.kaemart.it/prosit ). The paper describes the main issues related to the integration of these complementary instruments and the solutions proposed by the authors. More specifically, the main idea of the PROSIT project to link CAI and Optimization systems is the adoption of the latter tools n…
LC3: A spatio-temporal and semantic model for knowledge discovery from geospatial datasets
2015
International audience; There is a need for decision-makers to be provided with both an overview of existing knowledge, and information which is as complete and up-to-date as possible on changes in certain features of the biosphere. Another objective is to bring together all the many attempts which have been made over the years at various levels (international, Community, national and regional) to obtain more information on the environment and the way it is changing. As a result, remote sensing tools monitor large amount of land cover informations enabling study of dynamic processes. However the size of the dataset require new tools to identify pattern and extract knowledge. We propose a mo…
Verbal ordinal classification with multicriteria decision aiding
2008
Abstract Professionals in neuropsychology usually perform diagnoses of patients’ behaviour in a verbal rather than in a numerical form. This fact generates interest in decision support systems that process verbal data. It also motivates us to develop methods for the classification of such data. In this paper, we describe ways of aiding classification of a discrete set of objects, evaluated on set of criteria that may have verbal estimations, into ordered decision classes. In some situations, there is no explicit additional information available, while in others it is possible to order the criteria lexicographically. We consider both of these cases. The proposed Dichotomic Classification (DC…
Reference point approach for multiple decision makers
2005
We consider multiple criteria decision-making problems where a group of decision-makers wants to find the most preferred solution from a discrete set of alternatives. We develop a method that uses achievement functions for charting subsets of reference points that would support a certain alternative to be the most preferred one. The resulting descriptive information is provided to the decision-makers in the form of reference acceptability indices and central reference points for each decision alternative. Then, the decision-makers can compare this information with their own preferences. We demonstrate the use of the method using a strategic multiple criteria decision model for an electricit…
Multivariate Gaussian criteria in SMAA
2006
Abstract We consider stochastic multicriteria decision-making problems with multiple decision makers. In such problems, the uncertainty or inaccuracy of the criteria measurements and the partial or missing preference information can be represented through probability distributions. In many real-life problems the uncertainties of criteria measurements may be dependent. However, it is often difficult to quantify these dependencies. Also, most of the existing methods are unable to handle such dependency information. In this paper, we develop a method for handling dependent uncertainties in stochastic multicriteria group decision-making problems. We measure the criteria, their uncertainties and…
Applying data driven decision making to rank vocational and educational training programs with TOPSIS
2021
Abstract In this paper we present a multi-criteria classification of Vocational and Educational Programs in Extremadura (Spain) during the period 2009–2016. This ranking has been carried out through the integration into a complete database of the detailed information of individuals finishing such studies together with their labor data. The multicriteria method used is TOPSIS together with a new decision support method for assessing the influence of each criterion and its dependence on the weights assigned to them. This new method is based on a worst-best case scenario analysis and it is compared to a well known global sensitivity analysis technique based on the Pearson's correlation ratio.
Emergent vulnerabilities in Integrated Operations: A proactive simulation study of economic risk
2009
Abstract The protection of critical infrastructure requires an understanding of the effects of change on current and future safety and operations. Vulnerabilities may emerge during the rollout of updated techniques and integration of new technology with existing work practices. Managers need to understand how their decisions, often focused on economic priorities, affect the dynamics of vulnerability over time. Such understanding is difficult to obtain, as the historical data typically used for decision support, prediction and forecasting may not be available. We report on the use of group model building and simulation to consider proactively the effects of a 10-year, multi-billion dollar mo…
A Conceptual Architecture of Ontology Based KM System for Failure Mode and Effects Analysis
2014
Failure Mode and Effects Analysis (FMEA) is a systematic method for procedure analyses and risk assessment. It is a structured way to identify potential failure modes of a product or process, probability of their occurrence, and their overall effects. The basic purpose of this analysis is to mitigate the risk and the impact associated to a failure by planning and prioritizing actions to make a product or a process robust to failure. Effective manufacturing and improved quality products are the fruits of successful implementation of FMEA. During this activity valuable knowledge is generated which turns into product or process quality and efficiency. If this knowledge can be shared and reused…