The Experts below are selected from a list of 258 Experts worldwide ranked by ideXlab platform

Panagiota Tsarouchi - One of the best experts on this subject based on the ideXlab platform.

Andressa Pinto - One of the best experts on this subject based on the ideXlab platform.

User Unknown - One of the best experts on this subject based on the ideXlab platform.

Beverley F. Ronalds - One of the best experts on this subject based on the ideXlab platform.

  • Francis Ronalds (1788–1873): The First Electrical Engineer?
    2016
    Co-Authors: Beverley F. Ronalds
    Abstract:

    In this month’s article, the author takes a look at Francis Ronalds’ many contributions during his lifetime such as his documentation of important theoretical insights in Electrical science and generation of valuable data sets, and the creation of a world-leading observatory and a large Engineering institution. He was, in fact, a prolific inventor of Electrical, mechanical, and meteorological devices, but not much is known about him. The author contemplates whether Ronalds deserves to be credited as the first Electrical Engineer.

  • francis ronalds 1788 1873 the first Electrical Engineer
    Proceedings of the IEEE, 2016
    Co-Authors: Beverley F. Ronalds
    Abstract:

    In this month’s article, the author takes a look at Francis Ronalds’ many contributions during his lifetime such as his documentation of important theoretical insights in Electrical science and generation of valuable data sets, and the creation of a world-leading observatory and a large Engineering institution. He was, in fact, a prolific inventor of Electrical, mechanical, and meteorological devices, but not much is known about him. The author contemplates whether Ronalds deserves to be credited as the first Electrical Engineer.

  • francis ronalds 1788 1873 the first Electrical Engineer scanning our past
    Proceedings of the IEEE, 2016
    Co-Authors: Beverley F. Ronalds
    Abstract:

    In this month's article, the author takes a look at Francis Ronalds' many contributions during his lifetime such as his documentation of important theoretical insights in Electrical science and generation of valuable data sets, and the creation of a world-leading observatory and a large Engineering institution. He was, in fact, a prolific inventor of Electrical, mechanical, and meteorological devices, but not much is known about him. The author contemplates whether Ronalds deserves to be credited as the first Electrical Engineer.

  • Francis Ronalds (1788–1873): The First Electrical Engineer? [Scanning Our Past]
    Proceedings of the IEEE, 2016
    Co-Authors: Beverley F. Ronalds
    Abstract:

    In this month's article, the author takes a look at Francis Ronalds' many contributions during his lifetime such as his documentation of important theoretical insights in Electrical science and generation of valuable data sets, and the creation of a world-leading observatory and a large Engineering institution. He was, in fact, a prolific inventor of Electrical, mechanical, and meteorological devices, but not much is known about him. The author contemplates whether Ronalds deserves to be credited as the first Electrical Engineer.

F Bonanno - One of the best experts on this subject based on the ideXlab platform.

  • innovative second generation wavelets construction with recurrent neural networks for solar radiation forecasting
    IEEE Transactions on Neural Networks, 2012
    Co-Authors: Giacomo Capizzi, Christian Napoli, F Bonanno
    Abstract:

    Solar radiation prediction is an important challenge for the Electrical Engineer because it is used to estimate the power developed by commercial photovoltaic modules. This paper deals with the problem of solar radiation prediction based on observed meteorological data. A 2-day forecast is obtained by using novel wavelet recurrent neural networks (WRNNs). In fact, these WRNNS are used to exploit the correlation between solar radiation and timescale-related variations of wind speed, humidity, and temperature. The input to the selected WRNN is provided by timescale-related bands of wavelet coefficients obtained from meteorological time series. The experimental setup available at the University of Catania, Italy, provided this information. The novelty of this approach is that the proposed WRNN performs the prediction in the wavelet domain and, in addition, also performs the inverse wavelet transform, giving the predicted signal as output. The obtained simulation results show a very low root-mean-square error compared to the results of the solar radiation prediction approaches obtained by hybrid neural networks reported in the recent literature.