ABSTRACT Currently, worldwide scientific community is doing a great effort of research in the are... more ABSTRACT Currently, worldwide scientific community is doing a great effort of research in the area of Smart Grids because energy production, distribution, and consumption play a critical role in the sustainability of the planet. In this context, electricity load forecasting methodologies with fast response is a key component for demand-side management and the emergence of prosumers in the electricity grid. In this research it is shown that the computational intelligence techniques presented can deal with real time forecast, cope with incomplete measurement data and forecast signals of great variability, when applied to three real locations, with distinctly different characteristics.
Proceedings 1995 Second New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems, 1995
This paper presents the architecture of a new confi-gurable parallel neurocomputer optimized for ... more This paper presents the architecture of a new confi-gurable parallel neurocomputer optimized for the high-speed simulation of neural networks. Its main system feature is the reconfigurability of a new arithmetical unit chip which supports several accuracies in all ty-pical neural ...
In this paper, we study the alternatives for the implementation of any topology through a fully c... more In this paper, we study the alternatives for the implementation of any topology through a fully connected neural network. This strategy is based in the fact that, by the moment, most of the programmable FLSI neural networks implement this topology although associated computations ...
This paper describes the construction of a system that recognizes vehicle license numbers using f... more This paper describes the construction of a system that recognizes vehicle license numbers using feed forward neural networks, once they have been extracted using classical methods. The system has been trained and tested on real-world data. In order to reduce the total amount of ...
Proceedings of Fifth International Conference on Microelectronics for Neural Networks, 1996
This paper presents a new parallel computer architecture for high-speed emulation of any neural n... more This paper presents a new parallel computer architecture for high-speed emulation of any neural network model. The system is based on a new ASIC (Application Specific Integrated Circuit) that performs all required arithmetical operations. The essential feature of this ASIC is its ability t o adapt the internal parallelism dynamically t o the data precision for achieving an optimal utilization of the available hardware resources. Four ASICs are installed on one board of the neurocomputer system and emulate in parallel a neural network in a synchronous operation mode (SIMD architecture). By additional boards the system performance and also the size of the neural networks that can be simulated is increased. The main advantage of the system architecture is the simplicity of the design allowing the construction of low cost neurocomputer systems with a high performance. The achieved performance depends on the data precision and the number of installed boards. In the case of 16 bit weights and only one board a performance of 480 MCPs and 120 MCUPs (using backpropagation) can be obtained.
This paper describes the construction of a system that recognizes vehicle license numbers using f... more This paper describes the construction of a system that recognizes vehicle license numbers using feed forward neural networks, once they have been extracted using classical methods. The system has been trained and tested on real-world data. In order to reduce the total amount of ...
In this paper, we study the alternatives for the implementation of any topology through a fully c... more In this paper, we study the alternatives for the implementation of any topology through a fully connected neural network. This strategy is based in the fact that, by the moment, most of the programmable FLSI neural networks implement this topology although associated computations ...
11th International Conference on the European Energy Market (EEM14), 2014
ABSTRACT In this paper we introduce a new decentralized digital currency, called NRGcoin. Prosume... more ABSTRACT In this paper we introduce a new decentralized digital currency, called NRGcoin. Prosumers in the smart grid trade locally produced renewable energy using NRGcoins, the value of which is determined on an open currency exchange market. Similar to Bitcoins, this currency offers numerous advantages over fiat currency, but unlike Bitcoins it is generated by injecting energy into the grid, rather than spending energy on computational power. In addition, we propose a novel trading paradigm for buying and selling green energy in the smart grid. Our mechanism achieves demand response by providing incentives to prosumers to balance their production and consumption out of their own self-interest. We study the advantages of our proposed currency over traditional money and environmental instruments, and explore its benefits for all parties in the smart grid.
IEEE International Conference on Neural Networks, 1993
Abstract - This paper describes the construction of a system that recognizes vehicle license numb... more Abstract - This paper describes the construction of a system that recognizes vehicle license numbers using feed forward neural networks, once they have been extracted using classical methods. The system bas &en trained and tested on real-world data. In order to reduce the total ...
ABSTRACT Currently, worldwide scientific community is doing a great effort of research in the are... more ABSTRACT Currently, worldwide scientific community is doing a great effort of research in the area of Smart Grids because energy production, distribution, and consumption play a critical role in the sustainability of the planet. In this context, electricity load forecasting methodologies with fast response is a key component for demand-side management and the emergence of prosumers in the electricity grid. In this research it is shown that the computational intelligence techniques presented can deal with real time forecast, cope with incomplete measurement data and forecast signals of great variability, when applied to three real locations, with distinctly different characteristics.
Proceedings 1995 Second New Zealand International Two-Stream Conference on Artificial Neural Networks and Expert Systems, 1995
This paper presents the architecture of a new confi-gurable parallel neurocomputer optimized for ... more This paper presents the architecture of a new confi-gurable parallel neurocomputer optimized for the high-speed simulation of neural networks. Its main system feature is the reconfigurability of a new arithmetical unit chip which supports several accuracies in all ty-pical neural ...
In this paper, we study the alternatives for the implementation of any topology through a fully c... more In this paper, we study the alternatives for the implementation of any topology through a fully connected neural network. This strategy is based in the fact that, by the moment, most of the programmable FLSI neural networks implement this topology although associated computations ...
This paper describes the construction of a system that recognizes vehicle license numbers using f... more This paper describes the construction of a system that recognizes vehicle license numbers using feed forward neural networks, once they have been extracted using classical methods. The system has been trained and tested on real-world data. In order to reduce the total amount of ...
Proceedings of Fifth International Conference on Microelectronics for Neural Networks, 1996
This paper presents a new parallel computer architecture for high-speed emulation of any neural n... more This paper presents a new parallel computer architecture for high-speed emulation of any neural network model. The system is based on a new ASIC (Application Specific Integrated Circuit) that performs all required arithmetical operations. The essential feature of this ASIC is its ability t o adapt the internal parallelism dynamically t o the data precision for achieving an optimal utilization of the available hardware resources. Four ASICs are installed on one board of the neurocomputer system and emulate in parallel a neural network in a synchronous operation mode (SIMD architecture). By additional boards the system performance and also the size of the neural networks that can be simulated is increased. The main advantage of the system architecture is the simplicity of the design allowing the construction of low cost neurocomputer systems with a high performance. The achieved performance depends on the data precision and the number of installed boards. In the case of 16 bit weights and only one board a performance of 480 MCPs and 120 MCUPs (using backpropagation) can be obtained.
This paper describes the construction of a system that recognizes vehicle license numbers using f... more This paper describes the construction of a system that recognizes vehicle license numbers using feed forward neural networks, once they have been extracted using classical methods. The system has been trained and tested on real-world data. In order to reduce the total amount of ...
In this paper, we study the alternatives for the implementation of any topology through a fully c... more In this paper, we study the alternatives for the implementation of any topology through a fully connected neural network. This strategy is based in the fact that, by the moment, most of the programmable FLSI neural networks implement this topology although associated computations ...
11th International Conference on the European Energy Market (EEM14), 2014
ABSTRACT In this paper we introduce a new decentralized digital currency, called NRGcoin. Prosume... more ABSTRACT In this paper we introduce a new decentralized digital currency, called NRGcoin. Prosumers in the smart grid trade locally produced renewable energy using NRGcoins, the value of which is determined on an open currency exchange market. Similar to Bitcoins, this currency offers numerous advantages over fiat currency, but unlike Bitcoins it is generated by injecting energy into the grid, rather than spending energy on computational power. In addition, we propose a novel trading paradigm for buying and selling green energy in the smart grid. Our mechanism achieves demand response by providing incentives to prosumers to balance their production and consumption out of their own self-interest. We study the advantages of our proposed currency over traditional money and environmental instruments, and explore its benefits for all parties in the smart grid.
IEEE International Conference on Neural Networks, 1993
Abstract - This paper describes the construction of a system that recognizes vehicle license numb... more Abstract - This paper describes the construction of a system that recognizes vehicle license numbers using feed forward neural networks, once they have been extracted using classical methods. The system bas &en trained and tested on real-world data. In order to reduce the total ...
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Papers by N. Avellana