A hybrid PSO-ANFIS approach for short-term wind power prediction in Portugal

The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Wind power prediction plays a key role in tackling these challenges. The contribution of this paper is to propose a new hybrid approach, combining particle swarm optimization and adaptive-network-based fuzzy inference system, for short-term wind power prediction in Portugal. Significant improvements regarding forecasting accuracy are attainable using the proposed approach, in comparison with the results obtained with five other approaches.

An artificial neural network approach for short-term wind power forecasting in Portugal

This paper presents an artificial neural network approach for short-term wind power forecasting in Portugal. The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Hence, good forecasting tools play a key role in tackling these challenges. The accuracy of the wind power forecasting attained with the proposed approach is evaluated against persistence and ARIMA approaches, reporting the numerical results from a real-world case study.

Nonlinear optimization method for short-term hydro scheduling considering head-dependency

This paper is on the problem of short-term hydro scheduling, particularly concerning head-dependent reservoirs under competitive environment. We propose a new nonlinear optimization method to consider hydroelectric power generation as a function of water discharge and also of the head. Head-dependency is considered on short-term hydro scheduling in order to obtain more realistic and feasible results. The proposed method has been applied successfully to solve a case study based on one of the main Portuguese cascaded hydro systems, providing a higher profit at a negligible additional computation time in comparison with a linear optimization method that ignores head-dependency.

Enhanced short wavelength response in laser-scanned-photodiode image sensor using an a-SiC : H/a-Si : H tandem structure

We report in this paper the recent advances we obtained in optimizing a color image sensor based on the laser-scanned-photodiode (LSP) technique. A novel device structure based on a a-SiC:H/a-Si:H pin/pin tandem structure has been tested for a proper color separation process that takes advantage on the different filtering properties due to the different light penetration depth at different wavelengths a-SM and a-SiC:H. While the green and the red images give, in comparison with previous tested structures, a weak response, this structure shows a very good recognition of blue color under reverse bias, leaving a good margin for future device optimization in order to achieve a complete and satisfactory RGB image mapping. Experimental results about the spectral collection efficiency are presented and discussed from the point of view of the color sensor applications. The physics behind the device functioning is explained by recurring to a numerical simulation of the internal electrical configuration of the device.

Short-term electricity prices forecasting in a competitive market by a hybrid PSO-ANFIS approach

In this paper, a novel hybrid approach is proposed for electricity prices forecasting in a competitive market, considering a time horizon of 1 week. The proposed approach is based on the combination of particle swarm optimization and adaptive-network based fuzzy inference system. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications, to demonstrate its effectiveness regarding forecasting accuracy and computation time. Finally, conclusions are duly drawn. (C) 2012 Elsevier Ltd. All rights reserved.

Application of adaptive neuro-fuzzy inference for wind power short-term forecasting

The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Hence, good forecasting tools play a key role in tackling these challenges. In this paper, an adaptive neuro-fuzzy inference approach is proposed for short-term wind power forecasting. Results from a real-world case study are presented. A thorough comparison is carried out, taking into account the results obtained with other approaches. Numerical results are presented and conclusions are duly drawn. (C) 2011 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

Hybrid Wavelet-PSO-ANFIS Approach for Short-Term Electricity Prices Forecasting

A novel hybrid approach, combining wavelet transform, particle swarm optimization, and adaptive-network-based fuzzy inference system, is proposed in this paper for short-term electricity prices forecasting in a competitive market. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications. Finally, conclusions are duly drawn.

Microstrip antenna array for multiband dedicated short range communications systems

Dedicated Short Range Communications (DSRC) is the key enabling technology for the present and future vehicular communication for various applications, such as safety improvement and traffic jam mitigation. This paper describes the development of a microstrip antenna array for the roadside equipment of a DSRC system, whose characteristics are according with the vehicular communications standards. The proposed antenna, with circular polarization, has a wide bandwidth, enough to cover the current European DSRC 5.8 GHz band and the future 5.9 GHz band for next generation DSRC communications. (C) 2011 Wiley Periodicals, Inc. Microwave Opt Technol Lett 53: 2794-2796, 2011; View this article online at wileyonlinelibrary.com. DOI 10.1002/mop.26394

Semiconductor Device as Optical Demultiplexer for Short Range Optical Communications

In this paper we present results on the use of a multilayered a-SiC:H heterostructure as a wavelength-division demultiplexing device for the visible light spectrum. The proposed device is composed of two stacked p-i-n photodiodes with intrinsic absorber regions adjusted to short and long wavelength absorption and carrier collection. An optoelectronic characterisation of the device was performed in the visible spectrum. Demonstration of the device functionality for WDM applications was done with three different input channels covering the long, the medium and the short wavelengths in the visible range. The recovery of the input channels is explained using the photocurrent spectral dependence on the applied voltage. An electrical model of the WDM device is proposed and supported by the solution of the respective circuit equations. Short range optical communications constitute the major application field, however other applications are also foreseen.

Short-term electricity prices forecasting in a competitive market by a hybrid intelligent approach

In this paper, a hybrid intelligent approach is proposed for short-term electricity prices forecasting in a competitive market. The proposed approach is based on the wavelet transform and a hybrid of neural networks and fuzzy logic. Results from a case study based on the electricity market of mainland Spain are presented. A thorough comparison is carried out, taking into account the results of previous publications. Conclusions are duly drawn. (C) 2010 Elsevier Ltd. All rights reserved.

Short-term Feature Space and Music Genre Classification

In music genre classification, most approaches rely on statistical characteristics of low-level features computed on short audio frames. In these methods, it is implicitly considered that frames carry equally relevant information loads and that either individual frames, or distributions thereof, somehow capture the specificities of each genre. In this paper we study the representation space defined by short-term audio features with respect to class boundaries, and compare different processing techniques to partition this space. These partitions are evaluated in terms of accuracy on two genre classification tasks, with several types of classifiers. Experiments show that a randomized and unsupervised partition of the space, used in conjunction with a Markov Model classifier lead to accuracies comparable to the state of the art. We also show that unsupervised partitions of the space tend to create less hubs.

Short-term wind power forecasting in Portugal by neural networks and wavelet transform

This paper proposes artificial neural networks in combination with wavelet transform for short-term wind power forecasting in Portugal. The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Hence, good forecasting tools play a key role in tackling these challenges. Results from a real-world case study are presented. A comparison is carried out, taking into account the results obtained with other approaches. Finally, conclusions are duly drawn. (C) 2010 Elsevier Ltd. All rights reserved.

Sequencing of a 9.9 kb segment on the right arm of yeast chromosome VII reveals four open reading frames, including PFK1, the gene coding for succinyl-CoA synthetase (beta-chain) and two ORFs sharing homology with ORFs of the yeast chromosome VIII

A 9.9 kb DNA fragment from the right arm of chromosome VII of Saccharomyces cerevisiae has been sequenced and analysed. The sequence contains four open reading frames (ORFs) longer than 100 amino acids. One gene, PFK1, has already been cloned and sequenced and the other one is the probable yeast gene coding for the beta-subunit of the succinyl-CoA synthetase. The two remaining ORFs share homology with the deduced amino acid sequence (and their physical arrangement is similar to that) of the YHR161c and YHR162w ORFs from chromosome VIII.

Sequencing of a 17.6 kb segment on the right arm of yeast chromosome VII reveals 12 ORFs, including CCT, ADE3 and TR-I genes, homologues of the yeast PMT and EF1G genes, of the human and bacterial electron-transferring flavoproteins (beta-chain) and of the Escherichia coli phosphoserine phosphohydrolase, and five new ORFs.

A 17.6 kb DNA fragment from the right arm of chromosome VII of Saccharomyces cerevisiae has been sequenced and analysed. The sequence contains twelve open reading frames (ORFs) longer than 100 amino acids. Three genes had already been cloned and sequenced: CCT, ADE3 and TR-I. Two ORFs are similar to other yeast genes: G7722 with the YAL023 (PMT2) and PMT1 genes, encoding two integral membrane proteins, and G7727 with the first half of the genes encoding elongation factors 1gamma, TEF3 and TEF4. Two other ORFs, G7742 and G7744, are most probably yeast orthologues of the human and Paracoccus denitrificans electron-transferring flavoproteins (beta chain) and of the Escherichia coli phosphoserine phosphohydrolase. The five remaining identified ORFs do not show detectable homology with other protein sequences deposited in data banks. The sequence has been deposited in the EMBL data library under Accession Number Z49133.

The complete sequence of a 9000 bp fragment of the right arm of Saccharomyces cerevisiae chromosome VII contains four previously unknown open reading frames

We report the sequence of a 9000 bp fragment from the right arm of Saccharomyces cerevisiae chromosome VII. Analysis of the sequence revealed four complete previously unknown open reading frames, which were named G7587, G7589, G7591 and G7594 following standard rules for provisional nomenclature. Outstanding features of some of these proteins were the homology of the putative protein coded by G7589 with proteins involved in transcription regulation and the transmembrane domains predicted in the putative protein coded by G7591.