The proceedings contain 266 papers. The topics discussed include: initial-boundary value existing problem in nonlinear elastic beam equations;modeling for heat-exchangers of heat-setting machine;models and algorithm o...
ISBN:
(纸本)9783642238864
The proceedings contain 266 papers. The topics discussed include: initial-boundary value existing problem in nonlinear elastic beam equations;modeling for heat-exchangers of heat-setting machine;models and algorithm of maximum flow problem in uncertain network;synchronization of the fractional order finance systems with activation feedback control;a novel artificial bee colony algorithm based on attraction pheromone for the multidimensional knapsack problems;intelligence optimization in parameter identification of the border irrigation model;power mean based crossover rate adaptive differential evolution;multi-objective path planning for space exploration robot based on chaos immune particle swarm optimization algorithm;an algorithm of determining the plane based on monocular vision and laser loop;a novel content-based image retrieval approach using fuzzy combination of color and texture;and obstacles detection in dust environment with a single image.
The proceedings contain 266 papers. The topics discussed include: initial-boundary value existing problem in nonlinear elastic beam equations;modeling for heat-exchangers of heat-setting machine;models and algorithm o...
ISBN:
(纸本)9783642238956
The proceedings contain 266 papers. The topics discussed include: initial-boundary value existing problem in nonlinear elastic beam equations;modeling for heat-exchangers of heat-setting machine;models and algorithm of maximum flow problem in uncertain network;synchronization of the fractional order finance systems with activation feedback control;a novel artificial bee colony algorithm based on attraction pheromone for the multidimensional knapsack problems;intelligence optimization in parameter identification of the border irrigation model;power mean based crossover rate adaptive differential evolution;multi-objective path planning for space exploration robot based on chaos immune particle swarm optimization algorithm;an algorithm of determining the plane based on monocular vision and laser loop;a novel content-based image retrieval approach using fuzzy combination of color and texture;and obstacles detection in dust environment with a single image.
The proceedings contain 266 papers. The topics discussed include: initial-boundary value existing problem in nonlinear elastic beam equations;modeling for heat-exchangers of heat-setting machine;models and algorithm o...
ISBN:
(纸本)9783642238802
The proceedings contain 266 papers. The topics discussed include: initial-boundary value existing problem in nonlinear elastic beam equations;modeling for heat-exchangers of heat-setting machine;models and algorithm of maximum flow problem in uncertain network;synchronization of the fractional order finance systems with activation feedback control;a novel artificial bee colony algorithm based on attraction pheromone for the multidimensional knapsack problems;intelligence optimization in parameter identification of the border irrigation model;power mean based crossover rate adaptive differential evolution;multi-objective path planning for space exploration robot based on chaos immune particle swarm optimization algorithm;an algorithm of determining the plane based on monocular vision and laser loop;a novel content-based image retrieval approach using fuzzy combination of color and texture;and obstacles detection in dust environment with a single image.
Extension of Ant Colony optimization (ACOR) had proposed by Dorigo in 2008, which could well solve optimization problems in continuous space. This paper combined Genetic Algorithm with ACOR to overcome ACOR's disa...
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Extension of Ant Colony optimization (ACOR) had proposed by Dorigo in 2008, which could well solve optimization problems in continuous space. This paper combined Genetic Algorithm with ACOR to overcome ACOR's disadvantages of slow convergence speed and great probability of converging to local optimum, as is proved by simulation analysis in neural network weights optimizing.
Particle swarm optimization (PSO) is one of swarm intelligence. It was modified by escape of the particle velocity, and a self-adaptive PSO (SAPSO) was proposed to overcome the PSO shortcomings of the premature conver...
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Particle swarm optimization (PSO) is one of swarm intelligence. It was modified by escape of the particle velocity, and a self-adaptive PSO (SAPSO) was proposed to overcome the PSO shortcomings of the premature convergence and the local optimization. The SAPSO is combined with radial basis function (RBF) neural network to form a SAPSON hybrid algorithm. Compared with radial basis function neural network, SAPSON has less adjustable parameters, faster convergence speed, global optimization and higher identification precision in the numerical experiment.
This work attempted on developing soft sensor for prediction of biopolymer molecular weight using neural network as the tool. Molecular weight is a parameter that cannot be measured online whereas it is difficult for ...
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This work attempted on developing soft sensor for prediction of biopolymer molecular weight using neural network as the tool. Molecular weight is a parameter that cannot be measured online whereas it is difficult for most of us to develop and control this particular parameter. Alternatively, the molecular weight is predicted by utilizing inferential estimation method based on neural network model. In this work, temperature of biopolymerization process is used to bring a mutual relation to biopolymer molecular weight. The process involved the development of neural network model for estimation of molecular weight based on various reaction temperatures. In this study, the results are convincing and the soft sensor developed from neural network is really reliable in forecasting the biopolymer molecular weight.
In a cognitive network, secondary users can coexist with primary users by opportunistically exploiting the frequency bands of primary users. However, secondary users should constrain themselves to avoid interferen...
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In a cognitive network, secondary users can coexist with primary users by opportunistically exploiting the frequency bands of primary users. However, secondary users should constrain themselves to avoid interference to primary users based on the sensing technology. This paper investigates the method of increasing the spectrum efficiency in cognitive network within external interference. We consider the practical scenario with external interference, in which the wireless node can be treated as secondary users and the external interference can be considered as a primary user. Nevertheless, the ordinary relationship between the primary user and secondary users has been changed. We consider the. spectrum resource allocation as a convex optimization problem which could obtain the optimal solution by adopting feasible direction method. Simulation results show that our algorithm could improve the overall throughput significantly.
For the characters of the City of Kunming' trunk road, this paper proposed a model of one-way green wave coordination control based on fuzzy neural network, from the optimization of the cycle, offset and split of ...
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ISBN:
(纸本)9781457708879
For the characters of the City of Kunming' trunk road, this paper proposed a model of one-way green wave coordination control based on fuzzy neural network, from the optimization of the cycle, offset and split of intersections. At last the simulation shows the proposed method can reduce the queue length and vehicle delay very well.
Topology control in wireless sensor networks tries to lower node energy consumption by reducing transmission power and by confining interference,collisions and consequently *** this paper,we analyze popular algorithms...
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ISBN:
(纸本)9781612842387
Topology control in wireless sensor networks tries to lower node energy consumption by reducing transmission power and by confining interference,collisions and consequently *** this paper,we analyze popular algorithms used for optimizing the power consumption in the sensor network and propose a novel technique wherein power consumption is traded with additional relay *** introduce additional relay nodes to make the network connected instead of increasing the *** proposed method reduces interference offered to each link and thereby results in improved BER or data *** design and analyze an algorithm that place an almost minimum number of additional sensors required to make network *** have implemented greedy version of this algorithm and demonstrated in simulation that is produces a high quality *** use InterAvg,InterMax(no of nodes that can offer interference)MinMax,and MinTotal as metrics to analyze and compare various algorithms.
Aimed at the characteristics of strong nonlinearity, uncertainty, time-variance and, strong coupling etc for AC electric arc furnace (EAF), and the traditional PID can not achieve desired control effect. The paper pro...
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Aimed at the characteristics of strong nonlinearity, uncertainty, time-variance and, strong coupling etc for AC electric arc furnace (EAF), and the traditional PID can not achieve desired control effect. The paper proposes a PID control algorithm based on optimized BP neural network using genetic algorithm, which is applied in electrode regulator systems of electric arc furnace to design the optimized controller. The algorithm optimizes the initial weights of BP neural network by using genetic algorithm firstly, and then adjusts the PID parameters by using BP neural network. The simulation indicates that the algorithm is feasible, and unit with intelligent PID controller has better accuracy and dynamic characteristics.
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