Extreme learning machine(ELM) is a simple and effective feedforward neural *** can be used in pattern *** its classification ability is not good *** order to solve this problem,this paper proposed an improved firefly ...
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ISBN:
(纸本)9781510835368
Extreme learning machine(ELM) is a simple and effective feedforward neural *** can be used in pattern *** its classification ability is not good *** order to solve this problem,this paper proposed an improved firefly algorithm and used it in the parameters selection of *** establishing the IFA-ELM model,we use UCI standard data set to verify its classification ***,the model is used in bearing fault diagnosis and obtains a good result.
Providing a powerful synchronization system is one of the most important goals to be pursued if an efficient utilization of WSN has to be addressed. This paper evaluates several classic time synchronization protocols ...
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Providing a powerful synchronization system is one of the most important goals to be pursued if an efficient utilization of WSN has to be addressed. This paper evaluates several classic time synchronization protocols based on clock model, and presents the sources of error on the basis of their elements. In detail, firefly algorithm achieves synchronization via a series of pulses emitted by pulse-coupled oscillators. The conclusions provide some reference for future study of improving the synchronization accuracy and efficiency.
Cloud computing has made it feasible to access various IT resources through a high speed network from anywhere in the world. Constant increasing demand of cloud computing is equally popular in consumers as well as pro...
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ISBN:
(纸本)9781467375429
Cloud computing has made it feasible to access various IT resources through a high speed network from anywhere in the world. Constant increasing demand of cloud computing is equally popular in consumers as well as providers. But along with advancement every technology is also associated with some ill effects. On same path, cloud computing also accompanies a serious issue with it and that issue is energy consumption. In this paper firefly algorithm has been selected as a proposed bio-inspired approach to perform load balancing to reduce energy consumption in cloud data center. Further, the results are compared with Particle Swarm optimization algorithm (PSO). The energy consumed in case of firefly algorithm is less than energy consumed in PSO algorithm.
This paper deals with an on-line identification of continuous-time nonlinear systems using a moving-window type Gaussian process (GP) model. The GP is a Gaussian random function and is completely described by its mean...
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ISBN:
(纸本)9781538626344;9781538626337
This paper deals with an on-line identification of continuous-time nonlinear systems using a moving-window type Gaussian process (GP) model. The GP is a Gaussian random function and is completely described by its mean function and covariance function. In order to track the time-varying system parameters and nonlinear function, the linear recursive least-squares (RLS) method is combined with firefly algorithm (FA) in a bootstrap manner. The hyperparameters of the covariance function are searched for by FA, while the system parameters of the linear terms and the weighting parameters of the mean function are updated by the RLS method. Numerical experiments are carried out to demonstrate the effectiveness of the proposed method.
In this paper, the problem of coverage and exploration of unknown and mined spaces is investigated using a team of robots. The goal is to propose a strategy capable to minimize the overall exploration and mine disarmi...
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ISBN:
(纸本)9781510810600
In this paper, the problem of coverage and exploration of unknown and mined spaces is investigated using a team of robots. The goal is to propose a strategy capable to minimize the overall exploration and mine disarming time, whileavoiding that robots pass many times through the same places. The key problem is that the robots simultaneously have to explore different regions of the environment and for this reason they should spread among the search areas. However, at the same time, when a mine is discovered, more robots are needed to be engaged in order to disarm the mine. Because the problem of the unknown lands with the constraint to disarm mine is a NP hard problem, we proposed a combined approach using two bio-inspired meta-heuristic approaches such as Ant Colony Optimization (ACO) and firefly algorithm (FA) to perform the coordination task among robots. We have compared the simulation results considering a common exploration task of the robot spreading and an ACO based robot recruiting (ATS-RR) and firefly inspired (FTS-RR) strategies to perform the mine disarming task. Performance has been evaluated in terms of both overall exploring time and mine disarming time and in terms of number of accesses distributed in the operative grid area. The results show that the combined approach provides a better tool for both exploration and disarmament.
This work focuses on proposing a new algorithm, referred as HMA (Hybrid Metaheuristic algorithm) for the solution of the WTO (Wind Turbine Optimization) problem. It is well documented that turbines located behind one ...
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This work focuses on proposing a new algorithm, referred as HMA (Hybrid Metaheuristic algorithm) for the solution of the WTO (Wind Turbine Optimization) problem. It is well documented that turbines located behind one another face a power loss due to the obstruction of the wind due to wake loss. It is required to reduce this wake loss by the effective placement of turbines using a new HMA. This HMA is derived from the two basic algorithms i.e. DEA (Differential Evolution algorithm) and the FA (firefly algorithm). The function of optimization is undertaken on the N.O. Jensen model. The blending of DEA and FA into HMA are discussed and the new algorithm HMA is implemented maximize power and minimize the cost in a WTO problem. The results by HMA have been compared with GA (Genetic algorithm) used in some previous studies. The successfully calculated total power produced and cost per unit turbine for a wind farm by using HMA and its comparison with past approaches using single algorithms have shown that there is a significant advantage of using the HMA as compared to the use of single algorithms. The first time implementation of a new algorithm by blending two single algorithms is a significant step towards learning the behavior of algorithms and their added advantages by using them together.
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