Differential Ant Stigmergy Algorithm (DASA) is a recent meta-heuristic method which represents an adaptation of Ant Colony Optimization (ACO) to continuous optimization problems. Other adaptations of ACO to continuous...
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A difficult challenge in hybrid electric vehicles (HEVs) and full electric vehicles (EVs) is the torque control of externally excited synchronous machines (EESMs). Effective torque control requires an efficient soluti...
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Expressing user's preferences in database querying is best achieved by fuzzy modeling of linguistic terms included in selection criteria. This paper deals with temporal criteria, for querying date/time columns in ...
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Due to the recent research advances on quantum computing, ideas from this field have been increasingly used as a source of inspiration for new variants of evolutionary algorithms. In this paper, the QIEA-SSEHC algorit...
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This paper describes a distributed control strategy for a hybrid electric vehicle, in order to reduce the fuel consumption, and to maintain a reasonable state of charge (SOC), at the end of the drive cycle. The vehicl...
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Operating in the proximity of humans has been a long-term challenge in robotics research. To achieve this objective, one of the main issues is to ensure safe and comfortable physical human-robot interaction (pHRI). In...
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Multimedia is one of the most important aspects of the information era. With the advent of the multimedia age and the spread of Internet, video storage and streaming has been gaining a lot of popularity. When transmit...
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Multimedia is one of the most important aspects of the information era. With the advent of the multimedia age and the spread of Internet, video storage and streaming has been gaining a lot of popularity. When transmitting compressed video over a data network channel errors affect the decoding process. Video transmission puts constraints on data rate, computational complexity and delay. Unreliable channels add more challenges to this task as compressed video is extremely vulnerable to transmission errors. Problems arising from imperfect transmission of block coded video frame sequence result in lost blocks. This paper presents and implements a set of decoder side spatio-temporal algorithms that aim to enhance the speed and quality of the error concealment process. The results obtained by these algorithms are much faster and achieve better performance compared to the existing algorithms, which make them more suitable for real-time applications.
This paper presents a single multiplicative neuron model based on a polynomial architecture. The proposed neuron model consists of a non-linear aggregation function based on the concept of generalized mean of all mult...
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This paper presents a single multiplicative neuron model based on a polynomial architecture. The proposed neuron model consists of a non-linear aggregation function based on the concept of generalized mean of all multiplicative inputs. This neuron model has the same number of parameters as the single multiplicative neuron model (SMN). The SMN model is a special case of the proposed generalized mean single multiplicative neuron (GMSMN) model. The structure of this model is simpler than higher-order neuron model. The simulation results show that the performance of the proposed neuron model is better than SMN model.
This paper presents a single multiplicative neuron model based on a polynomial architecture. The proposed neuron model consists of a non-linear aggregation function based on the concept of generalized mean of all mult...
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This paper presents a single multiplicative neuron model based on a polynomial architecture. The proposed neuron model consists of a non-linear aggregation function based on the concept of generalized mean of all multiplicative inputs. This neuron model has the same number of parameters as the single multiplicative neuron model (SMN). The SMN model is a special case of the proposed generalized mean single multiplicative neuron (GMSMN) model. The structure of this model is simpler than higher-order neuron model. The simulation results show that the performance of the proposed neuron model is better than SMN model.
This paper describes a distributed control strategy for a hybrid electric vehicle, in order to reduce the fuel consumption, and to maintain a reasonable state of charge (SOC), at the end of the drive cycle. The vehicl...
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This paper describes a distributed control strategy for a hybrid electric vehicle, in order to reduce the fuel consumption, and to maintain a reasonable state of charge (SOC), at the end of the drive cycle. The vehicle is like a system built from control nodes, every one of them having the same priority. The control laws are based on the dc-bus signaling, such way that every source of power (control node) is entering or leaving the network (dc-bus) depending on the voltage thresholds. The algorithm was tested using Matlab Simulink and ADVISOR interface. The results include statistical comparisons of the standard drive cycles using default model and the modified control strategy.
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