This paper focus on multilayer feedforward neural networks, the most popular and widely-used paradigms in many applications, including energy forecasting Precisely, it provides a multilayer perceptron (MLP) architectu...
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One of the biggest problems in sensitive data wiping is to determine if a file is sensitive or not. Data wiping applications have improved a lot, but they cannot determine by themselves if a file is sensitive. The met...
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Kinesin nanomotor is a tiny vehicle that transports molecular cargoes within the cells. Many kinesin nanomotors can attach to a single cargo and coordinate their behaviors to transport the cargo. This behavioral coord...
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ISBN:
(纸本)9781467303408;9781467303422
Kinesin nanomotor is a tiny vehicle that transports molecular cargoes within the cells. Many kinesin nanomotors can attach to a single cargo and coordinate their behaviors to transport the cargo. This behavioral coordination of kinesin nanomotors can be defined through a communicational language that kinesin nanomotors follow to transport the cargo. This paper proposes a computational language for kinesin nanomotor which is inspired by the nanomotor's natural behavior. In this technique, we have used behavioral Deterministic Finite Automaton (DFA) model of kinesin nanomotor which indicated internal intelligent and autonomous decision-making process of the nanomotor in response to its cell. In addition, the behavioral responses of kinesin nanomotor to its cell, behavioral DFA model of the nanomotor, were mapped to a computational regular language for the nanomotor. The proposed computational language for kinesin nanomotor was acceptable by the behavioral DFA model and also in good agreement with the natural behavior of the nanomotor. The development of such computational languages among intelligent and autonomous nanoparticles in nature paves the way for constructing potential bio-inspired nanorobotic systems as well as designing of some computational languages for their controlling.
Heuristic reduction algorithm has got an extensive application in decision table;based on rough sets theory and partition of set, the attribute reduction of information systems without decision attributes is discussed...
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having a suitable model is one of the most important steps in active noise and vibration control systems. There are many applications in which the derived numerical model does not show the system behavior appropriatel...
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This paper focus on radial-basis function (RBF) neural networks, the most popular and widely-used paradigms in many applications, including renewable energy forecasting. It provides an analysis of short term load fore...
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ISBN:
(纸本)9789898425751
This paper focus on radial-basis function (RBF) neural networks, the most popular and widely-used paradigms in many applications, including renewable energy forecasting. It provides an analysis of short term load forecasting STLF performances of RBF neural networks. Precisely, the goal is to forecast the DPcg (difference between the electricity produced from renewable energy sources and consumed), for short-term horizon. The forecasting accuracy and precision, in capturing nonlinear interdependencies between the load and solar radiation of these neural networks are illustrated and discussed using a data based obtain from an experimental photovoltaic amphitheatre of minimum dimension 0.4kV/10kW.
The agent's decision mechanism should take into account only the events which can influence the agent's decision. That is way it is necessary to embed the event processing technology into multi-agent systems d...
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Electroencephalography is an important diagnostic tool for functional investigations of the human brain. Recent EEG measurement technologies provide high numbers of electrodes and sampling rates, which results in a co...
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This paper presents a novel approach of using unmanned vehicles for Automated Meter Reading (AMR) applications in rural areas where there are a few consumers scattered around a wide area. The proposed system does not ...
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