In this paper, the particle swarm optimization algorithm (PSO) for reservoir optimal operation is studied. A new algorithm which is suitable for reservoir optimal operation called multiple groups of gradient particle ...
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ISBN:
(纸本)9781479951512
In this paper, the particle swarm optimization algorithm (PSO) for reservoir optimal operation is studied. A new algorithm which is suitable for reservoir optimal operation called multiple groups of gradient particle swarm optimization algorithm (MGPSO) is proposed to avoid the shortcomings of PSO including premature convergence, poor search accuracy and easily falling into local optimal solution. The gradient searching strategy is introduced to improve the search accuracy of local optima. Grouping and randomly updating strategy are used to improve the searching ability of global optima. Simulation experiments and the example of reservoir optimal operation show that the new algorithm MGPSO obviously outperforms the standard PSO and shuffled frog leaping particleswarmoptimization (SFLPSO), and is effective in solving the optimal operation of hydropower station reservoir.
Polyphase coded radar signals is one of the most important and usually used in MIMO Radar systems. Polyphase coded radar signals with good orthogonal properties having low autocorrelation and a low crosscorrelation pr...
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ISBN:
(纸本)9781479940400
Polyphase coded radar signals is one of the most important and usually used in MIMO Radar systems. Polyphase coded radar signals with good orthogonal properties having low autocorrelation and a low crosscorrelation property is a nonlinear multivariable optimization problem. The proposed technique yield polyphase waveforms with orthogonal properties which effectively removes the interference issues faced by radars and also help in attaining high radar resolution. The oppositional concept is included in the initial population selection in the PSO algorithm and fractional calculus is used for modifying the velocity updation equation in PSO. Peak Sidelobe Ratio (PSLR) and Integrated Energy Sidelobe ratio (ISLR) of the polyphase waveforms are incorporated in the fitness function defined for the PSO. The experimental analysis based on different phases, different sequence lengths, different code set and different cost function are carried out. In all cases, the proposed technique has achieved good results.
A particle swarm optimization algorithm based on adaptive mutation and P systems is proposed to overcome trapping in local optimum solution and low optimization precision in this paper. At the same time, the proposed ...
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ISBN:
(纸本)9783662450482
A particle swarm optimization algorithm based on adaptive mutation and P systems is proposed to overcome trapping in local optimum solution and low optimization precision in this paper. At the same time, the proposed algorithm is investigated in experiments which are based on the function optimization of micro-grid's economic operation. Furthermore, the feasibility and effectiveness of the proposed algorithm are showed in the experimental results.
The paper presents a constrained optimization procedure to design a DC-DC converter with coupled inductors for minimizing the power losses. Two algorithms have been used, Genetic and particleswarmoptimization algori...
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ISBN:
(纸本)9781467388634
The paper presents a constrained optimization procedure to design a DC-DC converter with coupled inductors for minimizing the power losses. Two algorithms have been used, Genetic and particle swarm optimization algorithm, and the results have been compared. In particular, with the proposed technique, the electrical, magnetic and geometrical characteristics of the coupled inductors have been obtained and the values of duty cycle and frequency have been defined in order to obtain the maximum efficiency.
Designing DNA sequence sets is a fundamental issue in the fields of nanotechnology and nanocomputing. Not only quality but also quantity of DNA coding sequences affect the reliability of DNA computing. For this reason...
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Designing DNA sequence sets is a fundamental issue in the fields of nanotechnology and nanocomputing. Not only quality but also quantity of DNA coding sequences affect the reliability of DNA computing. For this reason, many researchers have paid their attentions to find more and better DNA sequences in DNA computing. In this paper we present particle swarm optimization algorithm (PSO) for the design of DNA sequence sets, namely sets of equal-length sequence over the nucleotides alphabet A,C,G,T that satisfy H-distance constraint. In our computational experiments, we succeed in generating better sequences sets. We give some practical values which satisfy H-distance constraint, and it has some directions for the theoretical lower bound in DNA computing.
Using particleswarmoptimization (PSO) has become a common heuristic technique in many fields of engineering. In this paper, we apply PSO to solve Joint Multiuser and Inter-symbol Interference (ISI) Suppression probl...
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ISBN:
(纸本)9781467356343
Using particleswarmoptimization (PSO) has become a common heuristic technique in many fields of engineering. In this paper, we apply PSO to solve Joint Multiuser and Inter-symbol Interference (ISI) Suppression problems in the code-division multiple-access (CDMA) systems over multipath Rayleigh fading channel, to reduce the computational complexity. In the proposed method, conventional detector (CD) is used as the first stage to initialize the PSO algorithm and time-varying acceleration coefficients (TVAC) are used in PSO algorithm. The simulation results show that the performance of PSO-based MUD with TVAC is promising and outperform the CD.
A multi-objective, multi-level, multi-product, multi-constraint batch planning problem is abstracted from production of diaphragm caustic soda, and the problem is formulated as a mathematic optimization model with con...
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ISBN:
(纸本)9781424427239
A multi-objective, multi-level, multi-product, multi-constraint batch planning problem is abstracted from production of diaphragm caustic soda, and the problem is formulated as a mathematic optimization model with constraints involved resources, work manufacture processes and production capacity etc. Some sub_objectives were considered in the problem model, such as total profit amount, profit margin, total energy wastage and wastage per ten thousand RMB.A modified particle swarm optimization algorithm with a percent-coding and dynamic-bounds coding scheme is proposed for the problem. The validity and flexibility of the model and algorithm are verified by calculating the data from production practices numerically.
Logistics is supposed to be the important source of profits for the enterprises besides reducing material consumption and improving labor productivity. Transportation costs, distribution center construction costs, ord...
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Logistics is supposed to be the important source of profits for the enterprises besides reducing material consumption and improving labor productivity. Transportation costs, distribution center construction costs, ordering costs, safe inventory costs and inventory holding costs are the important parts of the total logistics costs. In this paper, based on the research results of LMRP（ location model of risk pooling） location with fixed construction cost, the LMRPVCC （ location model of risk pooling based on variable construction cost） will be introduced. Applying particleswarmoptimization to several computational instances, the authors find the suboptimum solution of the model.
The efficiency of utilizing the satellite communications resource and system can be improved by optimizing the satellite broadcasting scheduling with genetic *** drawbacks such as complicated genetic operation, tardy ...
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The efficiency of utilizing the satellite communications resource and system can be improved by optimizing the satellite broadcasting scheduling with genetic *** drawbacks such as complicated genetic operation, tardy convergent speed and the aptness to sink into local minimum within the Genetic algorithm(GA) have encouraged a satellite broadcasting scheduling approach for resolving the scheduling *** approach was based on the particleswarmoptimization(PSO) algorithm which involved in processes such as constructing the model of satellite broadcasting scheduling,initialization of the particles and particle *** has been shown by simulation analysis that satellite broadcasting scheduling based on the PSO algorithm was feasible and its optimization result was significant.
This paper proposes an improved neural network adaptive sliding mode control method based on the neural network sliding mode control to improve the performance of the robot trajectory tracking control. This new scheme...
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This paper proposes an improved neural network adaptive sliding mode control method based on the neural network sliding mode control to improve the performance of the robot trajectory tracking control. This new scheme regards neural network as a controller and adopts robust control law to eliminate the approximation error which uses its nonlinear mapping ability to approximate various unknown nonlinear systems. Hidden layer units and network structure parameter have an effect on neural network mapping. So we will decrease chattering. We conduct experiments with three joints robot and give an example to verify this paper's scheme under the MATLAB platform. The results of experiments show that the new neural network adaptive sliding mode control has a good control accuracy and robustness than other control methods. The new scheme reduces the chattering effectively and also decreases the effect of hidden layer units and network structure parameter on neural network mapping. It will be a good choice for the robot trajectory tracking control.
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