Combining case-based reasoning systems and support vector regression to evaluate the atmosphere–ocean interaction

Paz, Juan F. De; Bajo, Javier; González, Angélica; Rodrı́guez, Sara; Corchado, Juan M.

doi:10.1007/s10115-010-0368-y

Cited by 36 publications

(9 citation statements)

References 56 publications

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“…Constraints regarding the monitoring, design, and selection phases are defined according the application requirements. Since several agents may participate in the monitoring, design, and selection phases, different mechanisms can be used to provide heterogeneous design solutions and also to select these solutions, such as case-based reasoning, learning, negotiation, etc (Aamodt & Plaza, 1994;de Paz et al, 2012). However, this flexibility can become a drawback since specific methods are not provided by the adaptation approach itself to carry out these phases.…”

Section: Discussionmentioning

confidence: 99%

Challenges for adaptation in agent societies

2012

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Abstract. Adaptation in Multiagent Systems societies provides a paradign for allowing these societies to change dynamically in order to satisfy the current requirements of the system. This support is especially required for the next generation of systems that focus on open, dynamic, and adaptive applications. In this paper, we analyze the current state of the art regarding approaches that tackle the adaptation issue in these agent societies. We survey the most relevant works up to now in order to highlight the most remarkable feautures according to what they support and how this support is provided. In order to compare these approaches, we also identify different characteristics of the adaptation process that are grouped in different phases. Finally, we discuss some of the most important considerations about the analyzed approaches and we provide some interesting guidelines as open issues that should be required in future developments.

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Section: Discussionmentioning

confidence: 99%

Challenges for adaptation in agent societies

2012

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“…In addition to neural networks, there are other models that can be applied in prediction systems such as Support Vector Regression (SVR) or different linear and nonlinear models. Although these models do not work in general, they are applicable in certain case studies [35] [1]. In this work we opt for handling a multi-sensor perceptron since, according to Kolmogorv, any function can be accurately approximated by a single hidden layer.…”

Section: Complementary Technologiesmentioning

confidence: 99%

Agent-based tool to reduce the maintenance cost of energy distribution networks

et al. 2017

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There has been continuous research in the energy distribution sector because of its huge impact on modern societies. Nonetheless, aerial high voltage power lines are still supported by old transmission towers which involve some serious risks. Those risks may be avoided with periodic and expensive reviews. The main objective of this work is to reduce the number of these periodic reviews so that the maintenance cost of power lines is also reduced. More specifically, the work is focused on reducing the number of periodic reviews of transmission towers to avoid step and touch potentials, which are very dangerous for humans. A virtual organization-based multi-agent system is proposed in conjunction with different artificial intelligence methods and algorithms. The developed system is able to propose a sample of transmission towers from a selected set to be reviewed. The system ensures that the whole set will have similar values without needing to review all the transmission towers. As a result of this work, a website application is provided to manage all the review processes and all the transmission towers of Spain. It allows the companies that review the transmission towers to initiate a new review process for a whole line or area, while the system indicates the transmission towers to review. The system is also able to recommend the best place to locate a new transmission tower or the best type of structure to use when a new transmission tower must be used.

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“…This section presents a cases study with the objective of experimenting and validating the proposed approach to forecast the electricity consumption. Besides the proposed method, forecasts are also performed using a Support Vector Regression (SVR) method, which has been presented in [25], and using a Linear Regression Method (LM). The inputs and outputs are defined in the same manner as in the case of MLP.…”

Section: Experimental Findingsmentioning

confidence: 99%

Intelligent energy forecasting based on the correlation between solar radiation and consumption patterns

Vinagre

Paz

Pinto

et al. 2016

2016 IEEE Symposium Series on Computational Intelligence (SSCI)

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The increasing penetration of renewable generation brings a significant escalation of intermittency to the power and energy system. This variability requires a new degree of flexibility from the whole system. The active participation of small and medium players becomes essential in this context. This is only possible by using adequate forecasting techniques applied both to the consumption and to generation. However, the large number of incontrollable factors, such as the presence of consumers in the building, the luminosity, or external temperature, makes the forecasting of energy consumption an arduous task. This paper addresses the electrical energy consumption forecasting problem, by studying the correlation between the solar radiation and the electrical consumption of lights. This study is performed by means of three forecasting methods, namely a multi-layer perceptron artificial neural network, a support vector regression method, and a linear regression method. The performed studies are analyzed using data gathered from a real installationcampus of the Polytechnic of Porto, in real time.

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Combining case-based reasoning systems and support vector regression to evaluate the atmosphere–ocean interaction

Cited by 36 publications

References 56 publications

Challenges for adaptation in agent societies

Challenges for adaptation in agent societies

Agent-based tool to reduce the maintenance cost of energy distribution networks

Intelligent energy forecasting based on the correlation between solar radiation and consumption patterns

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