Electricity markets are complex environments with very particular characteristics. MASCEM is a market simulator developed to allow deep studies of the interactions between the players that take part in the electricity...
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ISBN:
(纸本)9783642198748
Electricity markets are complex environments with very particular characteristics. MASCEM is a market simulator developed to allow deep studies of the interactions between the players that take part in the electricity market negotiations. This paper presents a new proposal for the definition of MASCEM players' strategies to negotiate in the market. The proposed methodology is multi-agent based, using reinforcement learning algorithms to provide players with the capabilities to perceive the changes in the environment, while adapting their bids formulation according to their needs, using a set of different techniques that are at their disposal. Each agent has the knowledge about a different method for defining a strategy for playing in the market, the main agent chooses the best among all those, and provides it to the market player that requests, to be used in the market. This paper also presents a methodology to manage the efficiency/effectiveness balance of this method, to guarantee that the degradation of the simulator processing times takes the correct measure.
In this paper, we present an agent-based dialog simulation technique for learning new dialog strategies and evaluate conversational agents. Using this technique the effort necessary to acquire data required to train t...
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ISBN:
(纸本)9783642198748
In this paper, we present an agent-based dialog simulation technique for learning new dialog strategies and evaluate conversational agents. Using this technique the effort necessary to acquire data required to train the dialog model and then explore new dialog strategies is considerably reduced. A set of measures has also been defined to evaluate the dialog strategy that is automatically learned and compare different dialog corpora. We have applied this technique to explore the space of possible dialog strategies and evaluate the dialogs acquired for a conversational agent that collects monitored data from patients suffering from diabetes.
The prediction accuracy of the fuzzy diatom models depends on both the manner of defining the fuzzy sets used (their number, shape and the parameters of the membership function (MF)) and the kind of the similarity met...
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ISBN:
(纸本)9783642286636;9783642286643
The prediction accuracy of the fuzzy diatom models depends on both the manner of defining the fuzzy sets used (their number, shape and the parameters of the membership function (MF)) and the kind of the similarity metric used. In this paper, we define new similarity metric, which takes into the account the maximum number of diatoms abundance in specific environmental parameter range. The inverse sigmoid MF is used to shape each MF to describe this relationship, in order to produce more accurate models. This improvement of the ecological modelling is achieved through the process of evaluation results for interpretability;higher prediction accuracy and over fitting resistant. The evaluation results compared with classical classification algorithms have confirmed these findings. Based on these results, one model for each water-quality category class is presented and discussed. From ecological point of view, each model is verified with the existing diatom indicator references found in literature by the biological expert.
In this paper, we introduce DegExt, a graph-based language-independent keyphrase extractor,which extends the keyword extraction method described in [6]. We compare DegExt with two state-of-the-art approaches to keyphr...
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ISBN:
(数字)9783642180293
ISBN:
(纸本)9783642180286
In this paper, we introduce DegExt, a graph-based language-independent keyphrase extractor,which extends the keyword extraction method described in [6]. We compare DegExt with two state-of-the-art approaches to keyphrase extraction: GenEx [11] and Text Rank [8]. Our experiments on a collection of benchmark summaries show that DegExt outperforms Text Rank and GenEx in terms of precision and area under curve (AUC) for summaries of 15 keyphrases or more at the expense of a non-significant decrease of recall and F-measure. Moreover, DegExt surpasses both GenEx and Text Rank in terms of implementation simplicity and computational complexity.
Over the last decades, Particle Filter also known as the Sampling Importance Resampling algorithm has successfully been applied to solve different problems in Engineering, e.g., trajectory tracking, non-linear estimat...
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ISBN:
(纸本)9783642205040
Over the last decades, Particle Filter also known as the Sampling Importance Resampling algorithm has successfully been applied to solve different problems in Engineering, e.g., trajectory tracking, non-linear estimation, and many others. Basically, the Particle Filter algorithm consists of a population of particles, which are sampled to estimate a posterior probability distribution. Unfortunately, in some cases the algorithm suffers from particle degeneracy, in which most particles converge prematurely to local minima due a loss of diversity of the population, and therefore do not contribute to estimation of the true probability distribution. In this paper, in order to tackle this drawback and to improve the performance of the standard Particle Filter we propose a modification to the algorithm by inserting a sampling mechanism inspired by Differential Evolution. Simulation results of the enhanced hybrid version are presented and compared with the standard Particle Filter algorithm and show the suitability of the proposed approach.
The high incidence of breast cancer in women has increased significantly in the recent years. Breast MRI involves the use of magnetic resonance imaging to look specifically at the breast. Contrast-enhanced breast MRIs...
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ISBN:
(纸本)9783642196430
The high incidence of breast cancer in women has increased significantly in the recent years. Breast MRI involves the use of magnetic resonance imaging to look specifically at the breast. Contrast-enhanced breast MRIs acquired by contrast injection have been shown to be very sensitive in the detection of breast cancer, but are also time-consuming and cause waste of medical resources. This paper utilizes the use of type-II fuzzy sets to enhance the contrast of the breast MRI image. To evaluate the performance of our approach, we run tests over different MRI breast images and show that the overall accuracy offered by the employed approach is high.
This paper introduces a double multiagent architecture allowing the triage of victims in emergency scenarios and the automatic update of their medical condition. Gathering updated information about the medical conditi...
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ISBN:
(纸本)9783642198748
This paper introduces a double multiagent architecture allowing the triage of victims in emergency scenarios and the automatic update of their medical condition. Gathering updated information about the medical condition of victims is critical for designing an optimal evacuation strategy that minimizes the number of casualties in the aftermath of an emergency. The proposed scheme, currently under development, combines Wireless Sensor Networks, an Electronic Triage Tag and a double multiagent system (Agilla-JADE) to achieve a low cost, no infrastructure-based, efficient system.
Semantic Web and Onto logics has increased the interest in the use of Knowledge-based systems in order to allow automated processing of, and reasoning with, information on the Web. However, it is widely pointed out th...
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ISBN:
(数字)9783642180293
ISBN:
(纸本)9783642180286
Semantic Web and Onto logics has increased the interest in the use of Knowledge-based systems in order to allow automated processing of, and reasoning with, information on the Web. However, it is widely pointed out that standard ontologies are not sufficient to deal with imprecise and vague knowledge for some real world applications, but the fuzzy ontologies can effectively model data and knowledge with uncertainty. In particular, in this paper will be introduced a collection of real-world applications based on the integration of different web-oriented frameworks such as the ontology-based intelligent fuzzy agents (OIFAs) and the Fuzzy Markup Language (FML) capable of generating fuzzy inference mechanisms and semantic decision making systems for an efficient modeling of real scenarios. In detail, hereafter our web intelligence approach will be applied to medical semantic decision making systems, computer go framework and so on. The experimental results show that the proposed method is feasible for different real-word scenarios.
In this paper, we present an interactive fuzzy non-linear goal programming (FNLGP) model to evaluate Regional sustainability development (RSD under climate change in agriculture sector.. A solution methodology of the ...
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ISBN:
(纸本)9783642196430
In this paper, we present an interactive fuzzy non-linear goal programming (FNLGP) model to evaluate Regional sustainability development (RSD under climate change in agriculture sector.. A solution methodology of the FNLGP model is presented. A Differential Evolution (DE) algorithm with variable step length is designed and implemented to optimize the resulting FNLGP. The proposed FNLGP model is more flexible than conventional goal programming and it is capable of evaluating RSD under different climate change scenarios. It provides decision support tool to test different alternative policies based on the degree of uncertainty. Introducing fuzzy terms in the model provides an assessment to uncertainty associated with various climate change predictions and information ambiguity.
Best practices for the publication of Semantic Web data currently place an unacceptably high burden on the end-user, who is supposed to locate and embrace third-party ontological structures prior to publishing any inf...
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ISBN:
(数字)9783642180293
ISBN:
(纸本)9783642180286
Best practices for the publication of Semantic Web data currently place an unacceptably high burden on the end-user, who is supposed to locate and embrace third-party ontological structures prior to publishing any information. In this paper, I argue for a different publication paradigm where end-users are encouraged to publish potentially incomplete or conflicting information according to their own local context, and where heterogeneous data is consolidated a posteriori through bottom-up, decentralized processes. This approach simplifies both the publication and curation processes, while opening the door to pay-as-you-go knowledge integration and human-centered social semantics. However, it also profoundly alters the semantics of the overall resulting system.
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