A New SOM Algorithm for Electricity Load Forecasting

Martín-Merino, Manuel; Román, Jesús Ángel

doi:10.1007/11893028_111

Cited by 11 publications

(7 citation statements)

References 10 publications

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“…How (a)synchrony may relate to patterns of flowering as gleaned from these simple indices (peak, start, cessation, duration, overlap) is considered in this paper. A self-organising map (Kohonen 1995) approach adapted for time series (King et al 2006;Junker et al 2006) is proposed as a possibly alternative metric for synchronisation, for the concise visualisation and assessment of synchronisation of multidimensional phenological time series. This SOM-based methodology is compared to the traditional Moran (1953a, b) synchrony test.…”

Section: Introductionmentioning

confidence: 99%

Using Self-Organising Maps (SOMs) to assess synchronies: an application to historical eucalypt flowering records

2011

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Self-Organising Map (SOM) clustering methods applied to the monthly and seasonal averaged flowering intensity records of eight Eucalypt species are shown to successfully quantify, visualise and model synchronisation of multivariate time series. The SOM algorithm converts complex, nonlinear relationships between high-dimensional data into simple networks and a map based on the most likely patterns in the multiplicity of time series that it trains. Monthly- and seasonal-based SOMs identified three synchronous species groups (clusters): E. camaldulensis, E. melliodora, E. polyanthemos; E. goniocalyx, E. microcarpa, E. macrorhyncha; and E. leucoxylon, E. tricarpa. The main factor in synchronisation (clustering) appears to be the season in which flowering commences. SOMs also identified the asynchronous relationship among the eight species. Hence, the likelihood of the production, or not, of hybrids between sympatric species is also identified. The SOM pattern-based correlation values mirror earlier synchrony statistics gleaned from Moran correlations obtained from the raw flowering records. Synchronisation of flowering is shown to be a complex mechanism that incorporates all the flowering characteristics: flowering duration, timing of peak flowering, of start and finishing of flowering, as well as possibly specific climate drivers for flowering. SOMs can accommodate for all this complexity and we advocate their use by phenologists and ecologists as a powerful, accessible and interpretable tool for visualisation and clustering of multivariate time series and for synchrony studies.

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Section: Introductionmentioning

confidence: 99%

Using Self-Organising Maps (SOMs) to assess synchronies: an application to historical eucalypt flowering records

2011

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“…However, we must have in account that we need to make the setting of a series of parameters to address each problem in particular. This implies that transforms in a technique with a high computational cost, since the adjustment of the parameters is usually performed through cross-validation, where additionally, you must choose the criteria of this same (Martín-Merino & Román 2006a;Velásquez et al, 2010).…”

Section: Case Of Studymentioning

confidence: 99%

Improvement in the distribution of services in multi-agent systems with SCODA

Gallego

González

2016

ADCAIJ

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The distribution of services on multi-agent systems allows it to reduce to the agents their computational load. The functionality of the system does not reside in the agents themselves, however it is ubiquitously distributed so that allows you to perform tasks in parallel avoiding an additional computational cost to the elements in the system. The distribution of services that offers SCODA (Distrib-uted and Specialized Agent Communities) allows an intelligent management of these services provided by agents of the system and the parallel execution of threads that allow to respond to requests asynchronously, which implies an improvement in the performance of the system at both the computational level as the level of quality of service in the control of these services. The comparison carried out in the case of study that is presented in this paper demonstrates the existing improvement in the distribution of services on systems based on SCODA.

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“…There are various techniques used to predict time series, from traditional statistical models such as ARIMA and the transfer functions to nonlinear models based on artificial neural networks [30]. The prediction of values belonging to time series of various kinds is a widely discussed problem in the literature [1,7,8,13,14].…”

Section: Case Of Studymentioning

confidence: 99%

Improving the Distribution of Services in MAS

Román

Rodrı́guez

Prieta

2016

Highlights of Practical Applications of Scalable Multi-Agent Systems. The PAAMS Collection

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One way to reduce the computational load of the agents is the distribution of their services. To achieve this goal, the functionality of a MAS (multiagent system) should not reside in the agents themselves, but ubiquitously be distributed so that allows the system to perform tasks in parallel avoiding an additional computational cost. The distribution of services that offers SCODA (Distributed and Specialized Agent Communities) allows an intelligent management of these services provided by agents of the system and the parallel execution of threads that allow to respond to requests asynchronously, which implies an improvement in the performance of the system at both the computational level as the level of quality of service in the control of these services. The comparison carried out in the case of study that is presented in this paper demonstrates the existing improvement in the distribution of services on systems based on SCODA.

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A New SOM Algorithm for Electricity Load Forecasting

Cited by 11 publications

References 10 publications

Using Self-Organising Maps (SOMs) to assess synchronies: an application to historical eucalypt flowering records

Using Self-Organising Maps (SOMs) to assess synchronies: an application to historical eucalypt flowering records

Improvement in the distribution of services in multi-agent systems with SCODA

Improving the Distribution of Services in MAS

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