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Addressing the evaluation of EDSS-maintenance

Addressing the evaluation of EDSS-maintenance

3rd Biennial Meeting of the International Environmental Modelling and Software Society: Summit on Environmental Modelling and Software, iEMSs 2006

作者： Turon, Clàudia Comas, Joaquim Cortés, Ulises Poch, Manel Laboratori D'Enginyeria Química i Ambiental University of Girona Campus Montilivi 17071 Girona Spain Knowledge Engineering and Machine Learning Group Technical University of Catalonia c/ Jordi Girona 1 and 3 08034 Barcelona Spain

ISBN: (纸本)1424308526

Daily operation and maintenance tasks are needed to guarantee the correct performance of constructed wetlands. The definition of these activities is a complex task since these actions vary according to the characteristics of each facility. To support the definition of these operation and maintenance protocols an Environmental Decision Support System (EDSS) has been constructed (EDSS-maintenance). The methodology used to develop EDSS-maintenance is based on the following five steps: environmental problem analysis, data and knowledge acquisition, model selection, model implementation and evaluation process. The first four steps have been finished;however, the evaluation process is ongoing. This document presents a new approach for this step: two numerical indices allow (a) verifying the performance of the EDSS-maintenance and (b) validating the compliance of the protocols with the user requirements. Moreover, another index enables an easy revision and improvement of the knowledge bases (problems, causes and actions) and so enhances the decision support system.

关键词： Wetlands

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USE: A Concept-Based Recommendation System to Support Creative Search

USE: A Concept-Based Recommendation System to Support Creati...

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IEEE WIC ACM International Conference on Web Intelligence (WI)

作者： J. Sousa Lopes S. Alvarez-Napagao J. Vazquez-Salceda KEMLg-Knowledge Engineering and Machine Learning Group UPC-Universitat Politècnica de Catalunya Barcelona Spain

Semiotics is a field where research on Computer Science methodologies has focused, mainly concerning Syntax and Semantics. These methodologies, however, are lacking of some flexibility for the continuously evolving web community, in which the knowledge is classified with tags rather than with ontologies. In this paper we propose a system for the recommendation of tagged pictures obtained from the Web. The system, driven by user feedback, executes an abductive reasoning (based on WordNet synset semantic relations) that is able to iteratively lead to new concepts which progressively represent the cognitive creative user state.

关键词： Intelligent agent learning systems machine learning Humans Internet Collaboration Conferences knowledge engineering Computer science Ontologies

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GESCONDA: From environmental data mining to environmental decision support

GESCONDA: From environmental data mining to environmental de...

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4th Biennial Meeting of International Congress on Environmental Modelling and Software: Integrating Sciences and Information Technology for Environmental Assessment and Decision Making, iEMSs 2008

作者： Sànchez-Marrè, M. Gibert, K. Knowledge Engineering and Machine Learning Group Technical University of Catalonia Catalonia Jordi Girona 1-3 08034 Barcelona Catalonia Spain Department of Statistics and Operations Research Technical University of Catalonia Jordi Girona 1-3 08034 Barcelona Catalonia Spain

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Simulating scenarios for decision-making in river basin systems through a Multi-Agent System

Simulating scenarios for decision-making in river basin syst...

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3rd Biennial Meeting of the International Environmental Modelling and Software Society: Summit on Environmental Modelling and Software, iEMSs 2006

作者： Rendón-Sallard, Thania Sanchez-Marre, Miquel Devesa, Francesc Poch, Manel Knowledge Engineering and Machine Learning Group Universitat Politècnica de Catalunya c/Jordi Girona 1-3 E08034 Barcelona Spain Universitat de Girona Campus de Montilivi s/n Girona Catalonia 17071 Spain

ISBN: (纸本)1424308526

The complexity of environmental problems makes the management of environmental systems especially difficult to be undertaken by traditional software systems. Particularly river catchment systems are very intricate to manage in order to achieve a good quality and quantity of water at the river. Multi-Agent systems (MAS) are able to cope with this complexity by integrating all the water systems involved at catchment scale through several agents who model real environmental situations. In this paper we describe the design of a MAS for simulating multiple scenarios in a river catchment system in order to support the decision-making of river basins management. The River Basin MAS has been designed and their functionalities have been studied. Moreover, we have selected the agent platform Jadex as a starting software platform for our new software development. With this proposal, we intend to provide feasible solutions at catchment scale throughout modelling and simulation of different scenarios in a river basin system.

关键词： Multi agent systems

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Estimation of machine settings for spinning of yarns-new algorithms for comparing complex structures

Estimation of machine settings for spinning of yarns-new alg...

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22nd International Conference on Case-Based Reasoning Research and Development, ICCBR 2014

作者： Sevilla-Villanueva, Beatriz Sànchez-Marrè, Miquel Fischer, Thomas V. Knowledge Engineering and Machine Learning Group Universitat Politècnica de Catalunya-BarcelonaTech Jordi Girona 1-3 Barcelona Catalonia08034 Spain DITF Denkendorf Center for Management Research Koerschtalstr. 26 Denkendorf73770 Germany

ISBN: (纸本)9783319112084

The textile industry in Europe is facing a new challenge in order to stay competitive into the textile market. They need to be flexible, cost efficient and produce with high quality. The setting of the machinery parameters is therefore an important aspect that combines implicit knowledge of workers and engineers with explicit knowledge. This makes it an ideal domain for CBR. It is used for an automatic parameter setting but the data cannot be reduced to a flat representation, as yarns and fabrics are multicomponent artefacts. Therefore we propose a combination of 4 algorithms to evaluate the similarity of the yarns. The application was successfully applied for spinning and it can be applied in the following steps of the textile processes like weaving. © Springer International Publishing Switzerland 2014.

关键词： Textile industry

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Semantic clustering using multiple ontologies

Semantic clustering using multiple ontologies

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作者： Batet, Montserrat Valls, Aïda Gibert, Karina Sánchez, David Research Group Department of Computer Science and Mathematics Universitat Rovira i Virgili Avda. Països Catalans 26 43007 Tarragona Catalunya Spain Knowledge Engineering and Machine Learning Group Department of Statistics and Operations Research Universitat Politècnica de Catalunya Spain

ISBN: (纸本)9781607506423

Data mining tools able to semantically interpret textual or linguistic data are acquiring a growing importance. Moreover, the development of large ontologies for general and specific domains provides new tools to include background knowledge into data mining techniques such as clustering. In this paper we present an unsupervised clustering method that exploits the semantics of categorical data by means of ontologies, and it is also able to manage numerical data. Our method is able to use different ontologies in order to assess the meaning of the values during the clustering process, leading to a set of clusters with a clearer semantic interpretation in a particular domain. The influence of using one or several ontologies is analyzed by using real data collected from visitors to the Ebre Delta Natural Park, which is a protected natural reserve in Catalonia (Spain). © 2010 The authors and IOS Press. All rights reserved.

关键词： Ontology

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Tools for environmental data Mining and intelligent Decision Support

Tools for environmental data Mining and intelligent Decision...

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6th Biennial Meeting of the International Environmental Modelling and Software Society: Managing Resources of a Limited Planet, iEMSs 2012

作者： Gibert, Karina Sànchez-Marrè, Miquel Sevilla, Beatriz Knowledge Engineering and Machine Learning Group Universitat Politècnica de Catalunya-BarcelonaTech Barcelona Catalonia Spain Department of Statistics and Operation Research Universitat Politècnica de Catalunya-BarcelonaTech Barcelona Catalonia Spain Software Department Universitat Politrcnica de Catalunya-BarcelonaTech Catalonia Spain

ISBN: (纸本)9788890357428

The joint workshop in Data Mining for Environmental Scientists and Intelligent Environmental Decision Support Systems tries to provide a common discussion forum to communicate environmentalists with data miners and intelligent decision support systems developers. As environmentalists are the consumers of both products, Data Mining (DM) and Intelligent Decision Support Systems (IDSS) are complementary disciplines that must properly link to permit the maximum benefits of data analysis at highest levels. Here, a preliminary analysis of the state of the software tools in environmental DM and IDSS is presented.

关键词： Data mining

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CONCIENS: Organizational Awareness in Real-Time Strategy Games

CONCIENS: Organizational Awareness in Real-Time Strategy Gam...

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13th International Conference of the Catalan-Association-for-Artificial-Intelligence (CCIA)

作者： Alvarez-Napagao, Sergio Gomez-Sebastia, Ignasi Vazquez-Salceda, Javier Koch, Fernando Knowledge Engineering and Machine Learning Group Spain Institute of Information and Computing Sciences Netherlands Departament de Llenguatges i Sistemes Informátics Universitat Politécnica de Catalunya (UPC) E-08034 Barcelona C/Jordi Girona 1-3 Spain Utrecht University 3508TB Utrecht PO Box 80089 Netherlands

ISBN: (纸本)9781607506430;9781607506423

The implementation of AI in commercial games is usually based on low level designs that makes the control predictable, unadaptive, and non reusable. Recent algorithms such as HTN or GOAP prove that higher levels of abstraction can be applied for better performance. We propose that approaches based on Organizational Theory can help providing a sound alternative for these implementations. In this paper we present CONCIENS, an integration of the ALIVE organizational framework into commercial games. We introduce a proof-of-concept implementation based on the integration to Warcraft III.

关键词： artificial intelligence organizational theory games

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SPFLOW: An easy and extensible library for deep probabilistic learning using sum-product networks

arXiv

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arXiv 2019年

作者： Molina, Alejandro Vergari, Antonio Stelzner, Karl Peharz, Robert Subramani, Pranav Di Mauro, Nicola Poupart, Pascal Kersting, Kristian Machine Learning Group Computer Science Department TU Darmstadt Germany Probabilistic Learning Group Empirical Inference Department Max-Planck-Institute Germany Machine Learning Group Engineering Dept. University of Cambridge United Kingdom Knowledge Acquisition & Machine Learning Group University of Bari "Aldo Moro" Italy Waterloo AI Institute Vector Institute University of Waterloo CA Canada Centre for Cognitive Science TU Darmstadt Germany

We introduce SPFlow, an open-source Python library providing a simple interface to inference, learning and manipulation routines for deep and tractable probabilistic models called Sum-Product Networks (SPNs). The library allows one to quickly create SPNs both from data and through a domain specific language (DSL). It efficiently implements several probabilistic inference routines like computing marginals, conditionals and (approximate) most probable explanations (MPEs) along with sampling as well as utilities for serializing, plotting and structure statistics on an SPN. Moreover, many of the algorithms proposed in the literature to learn the structure and parameters of SPNs are readily available in SPFlow. Furthermore, SPFlow is extremely extensible and customizable, allowing users to promptly distill new inference and learning routines by injecting custom code into a lightweight functional-oriented API framework. This is achieved in SPFlow by keeping an internal Python representation of the graph structure that also enables practical compilation of an SPN into a TensorFlow graph, C, CUDA or FPGA custom code, significantly speeding-up computations. Copyright © 2019, The Authors. All rights reserved.

关键词： Python

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The use of Synthetic Data to solve the scalability and data availability problems in Smart City Digital Twins

arXiv

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arXiv 2022年

作者： Almirall, Esteve Callegaro, Davide Bruins, Peter Santamaría, Mar Martrínez, Pablo Cortés, Ulises Esade Business School URL University Spain 300.000km *** Spain Knowledge Engineering and Machine Learning Group Universitat Politècnica de Catalunya Spain

The A.I. disruption and the need to compete on innovation are impacting cities that have an increasing necessity to become innovation hotspots. However, without proven solutions, experimentation, often unsuccessful, is needed. But experimentation in cities has many undesirable effects not only for its citizens but also reputational if unsuccessful. Digital Twins, so popular in other areas, seem like a promising way to expand experimentation proposals but in simulated environments, translating only the "half-baked" ones, the ones with higher probability of success, to real environments and therefore minimizing risks. However, Digital Twins are data intensive and need highly localized data, making them difficult to scale, particularly to small cities, and with the high cost associated to data collection. We present an alternative based on synthetic data that given some conditions, quite common in Smart Cities, can solve these two problems together with a proof-of-concept based on NO2 pollution. © 2022, CC BY.

关键词： Smart city

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