891 resultados para Business Intelligence, BI Mobile, OBI11g, Decision Support System, Data Warehouse


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Dissertação apresentada na faculdade de Ciências e Tecnologia da Universidade Nova de Lisboa para a obtenção do grau de Mestre em Engenharia Electrotécnica e de Computadores

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This paper presents a decision support methodology for electricity market players’ bilateral contract negotiations. The proposed model is based on the application of game theory, using artificial intelligence to enhance decision support method’s adaptive features. This model is integrated in AiD-EM (Adaptive Decision Support for Electricity Markets Negotiations), a multi-agent system that provides electricity market players with strategic behavior capabilities to improve their outcomes from energy contracts’ negotiations. Although a diversity of tools that enable the study and simulation of electricity markets has emerged during the past few years, these are mostly directed to the analysis of market models and power systems’ technical constraints, making them suitable tools to support decisions of market operators and regulators. However, the equally important support of market negotiating players’ decisions is being highly neglected. The proposed model contributes to overcome the existing gap concerning effective and realistic decision support for electricity market negotiating entities. The proposed method is validated by realistic electricity market simulations using real data from the Iberian market operator—MIBEL. Results show that the proposed adaptive decision support features enable electricity market players to improve their outcomes from bilateral contracts’ negotiations.

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Thesis submitted to the Universidade Nova de Lisboa, Faculdade de Ciências e Tecnologia for the degree of Doctor of Philosophy in Environmental Engineering

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telligence applications for the banking industry. Searches were performed in relevant journals resulting in 219 articles published between 2002 and 2013. To analyze such a large number of manuscripts, text mining techniques were used in pursuit for relevant terms on both business intelligence and banking domains. Moreover, the latent Dirichlet allocation modeling was used in or- der to group articles in several relevant topics. The analysis was conducted using a dictionary of terms belonging to both banking and business intelli- gence domains. Such procedure allowed for the identification of relationships between terms and topics grouping articles, enabling to emerge hypotheses regarding research directions. To confirm such hypotheses, relevant articles were collected and scrutinized, allowing to validate the text mining proce- dure. The results show that credit in banking is clearly the main application trend, particularly predicting risk and thus supporting credit approval or de- nial. There is also a relevant interest in bankruptcy and fraud prediction. Customer retention seems to be associated, although weakly, with targeting, justifying bank offers to reduce churn. In addition, a large number of ar- ticles focused more on business intelligence techniques and its applications, using the banking industry just for evaluation, thus, not clearly acclaiming for benefits in the banking business. By identifying these current research topics, this study also highlights opportunities for future research.

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Engineering of negotiation model allows to develop effective heuristic for business intelligence. Digital ecosystems demand open negotiation models. To define in advance effective heuristics is not compliant with the requirement of openness. The new challenge is to develop business intelligence in advance exploiting an adaptive approach. The idea is to learn business strategy once new negotiation model rise in the e-market arena. In this paper we present how recommendation technology may be deployed in an open negotiation environment where the interaction protocol models are not known in advance. The solution we propose is delivered as part of the ONE Platform, open source software that implements a fully distributed open environment for business negotiation

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Engineering of negotiation model allows to develop effective heuristic for business intelligence. Digital ecosystems demand open negotiation models. To define in advance effective heuristics is not compliant with the requirement of openness. The new challenge is to develop business intelligence in advance exploiting an adaptive approach. The idea is to learn business strategy once new negotiation model rise in the e-market arena. In this paper we present how recommendation technology may be deployed in an open negotiation environment where the interaction protocol models are not known in advance. The solution we propose is delivered as part of the ONE Platform, open source software that implements a fully distributed open environment for business negotiation

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This paper presents a case study that explores the advantages that can be derived from the use of a design support system during the design of wastewater treatment plants (WWTP). With this objective in mind a simplified but plausible WWTP design case study has been generated with KBDS, a computer-based support system that maintains a historical record of the design process. The study shows how, by employing such a historical record, it is possible to: (1) rank different design proposals responding to a design problem; (2) study the influence of changing the weight of the arguments used in the selection of the most adequate proposal; (3) take advantage of keywords to assist the designer in the search of specific items within the historical records; (4) evaluate automatically the compliance of alternative design proposals with respect to the design objectives; (5) verify the validity of previous decisions after the modification of the current constraints or specifications; (6) re-use the design records when upgrading an existing WWTP or when designing similar facilities; (7) generate documentation of the decision making process; and (8) associate a variety of documents as annotations to any component in the design history. The paper also shows one possible future role of design support systems as they outgrow their current reactive role as repositories of historical information and start to proactively support the generation of new knowledge during the design process

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Nowadays, companies are living great difficulties on managing their business due to constant and unpredictable economic market fluctuations. Recent changes in market trends (such as the constant demand for new products and services, mass customization and the drastic reduction of delivery time) lead companies to adopt strategies of creating partnerships with other companies as a way to respond effectively to such difficult economical times. Collaborative Networks’ concept born by the consequence of companies could no longer consider their internal business processes’ management as sufficient and tend to seek for a collaborative approach with other partners for their critical processes. Information technologies (ICT) assumed a major role acting as “enablers” of these kinds of networks, enhancing information sharing and business process integration. Several new trends concerning ICT architectures have been created to support collaborative networks requirements, but still doesn’t exist a common platform to reduce the needed integration effort on virtual organizations. This study aims to investigate the current technological solutions available in the market which enhances the management of companies’ business processes (specially, Collaborative Planning). Finally, the research work ends with the presentation of a conceptual model to answer to the constraints evaluated.

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This paper discusses the problems inherent within traditional supply chain management's forecast and inventory management processes arising when tackling demand driven supply chain. A demand driven supply chain management architecture developed by Orchestr8 Ltd., U.K. is described to demonstrate its advantages over traditional supply chain management. Within this architecture, a metrics reporting system is designed by adopting business intelligence technology that supports users for decision making and planning supply activities over supply chain health.

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Multiple versions of information and associated problems are well documented in both academic research and industry best practices. Many solutions have proposed a single version of the truth, with Business intelligence being adopted by many organizations. Business Intelligence (BI), however, is largely based on the collection of data, processing and presentation of information to meet different stakeholders’ requirement. This paper reviews the promise of Enterprise Intelligence, which promises to support decision-making based on a defined strategic understanding of the organizations goals and a unified version of the truth.

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Inom Business Intelligence har begreppet Self-Service Business Intelligence (Self-Service BI) vuxit fram. Self-Service BI omfattar verktyg vilka möjliggör för slutanvändare att göra analyser och skapa rapporter utan teknisk support. Ett av dessa verktyg är Microsoft PowerPivot.På Transportstyrelsens Järnvägsavdelning finns behov av ett Self-Service BI-verktyg. Vi fick i uppdrag av Sogeti att undersöka om PowerPivot var ett lämpligt verktyg för Transportstyrelsen. Målet med uppsatsen har varit att testa vilka tekniska möjligheter och begränsningar PowerPivot har samt huruvida PowerPivot är användbart för Transportstyrelsen.För att få en djupare förståelse för Self-Service BI har vi kartlagt vilka möjligheter och begränsningar med Self-Service BI-verktyg som finns beskrivna i litteraturen. Vi har sedan jämfört dessa med våra testresultat vilket har varit syftet med uppsatsen.Resultatet av testerna har visat att Transportstyrelsens Järnvägsavdelning initialt behöver teknisk support för att använda PowerPivot. Testerna har även visat att vissa av Transportstyrelsens krav inte kan uppfyllas. Detta minskar användbarheten för Transportstyrelsen.Vidare har vi kommit fram till att Self-Service BI inte alltid är enkelt att använda för slutanvändare utan teknisk support. Resultatet visar även att det krävs en BI-infrastruktur för att enkelt skapa rapporter med god kvalitet och högsta möjliga korrekthet.

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Soil erosion on sloping agricultural land poses a serious problem for the environment, as well as for production. In areas with highly erodible soils, such as those in loess zones, application of soil and water conservation measures is crucial to sustain agricultural yields and to prevent or reduce land degradation. The present study, carried out in Faizabad, Tajikistan, was designed to evaluate the potential of local conservation measures on cropland using a spatial modelling approach to provide decision-making support for the planning of spatially explicit sustainable land use. A sampling design to support comparative analysis between well-conserved units and other field units was established in order to estimate factors that determine water erosion, according to the Revised Universal Soil Loss Equation (RUSLE). Such factor-based approaches allow ready application using a geographic information system (GIS) and facilitate straightforward scenario modelling in areas with limited data resources. The study showed first that assessment of erosion and conservation in an area with inhomogeneous vegetation cover requires the integration of plot-based cover. Plot-based vegetation cover can be effectively derived from high-resolution satellite imagery, providing a useful basis for plot-wise conservation planning. Furthermore, thorough field assessments showed that 25.7% of current total cropland is covered by conservation measures (terracing, agroforestry and perennial herbaceous fodder). Assessment of the effectiveness of these local measures, combined with the RUSLE calculations, revealed that current average soil loss could be reduced through low-cost measures such as contouring (by 11%), fodder plants (by 16%), and drainage ditches (by 53%). More expensive measures such as terracing and agroforestry can reduce erosion by as much as 63% (for agroforestry) and 93% (for agroforestry combined with terracing). Indeed, scenario runs for different levels of tolerable erosion rates showed that more cost-intensive and technologically advanced measures would lead to greater reduction of soil loss. However, given economic conditions in Tajikistan, it seems advisable to support the spread of low-cost and labourextensive measures.

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Nowadays, a wide offer of mobile augmented reality (mAR) applications is available at the market, and the user base of mobile AR-capable devices -smartphones- is rapidly increasing. Nevertheless, likewise to what happens in other mobile segments, business models to put mAR in value are not clearly defined yet. In this paper, we focus on sketching the big picture of the commercial offer of mAR applications, in order to inspire a posterior analysis of business models that may successfully support the evolution of mAR. We have gathered more than 400 mAR applications from Android Market, and analyzed the offer as a whole, taking into account some technology aspects, pricing schemes and user adoption factors. Results show, for example, that application providers are not expecting to generate revenues per direct download, although they are producing high-quality applications, well rated by the users.