We use an effective global harmony search algorithm(EGHS)to solve two kinds of pressure vessel design *** general,the two problems are formulated as mixed-integer non-linear programming problems with several *** EGHS ...
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We use an effective global harmony search algorithm(EGHS)to solve two kinds of pressure vessel design *** general,the two problems are formulated as mixed-integer non-linear programming problems with several *** EGHS combines harmony search algorithm(HS)with concepts from the swarm intelligence of particle swarm optimization algorithm(PSO)to solve the two optimization *** EGHS algorithm has been applied to two typical problems with results better than previously *** results have demonstrated that the EGHS has strong convergence and capacity of space exploration on solving pressure vessel design problems.
In the north of China, the problem of wind abandonment is very serious. In order to improve the ability of wind power consumption, a cogeneration system with an electric boiler is proposed. First, the mathematical mod...
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In the north of China, the problem of wind abandonment is very serious. In order to improve the ability of wind power consumption, a cogeneration system with an electric boiler is proposed. First, the mathematical model of the minimum power generation cost of the traditional unit and the optimized model are established. Second, the model is solved by using the particle swarm optimization algorithm. In addition, a power structure of combined heat and power system（CHP） is constructed for simulation experiments. Through experimental analysis, proving the feasibility of the model. Finally, Simulation results show that making the electric boiler work in the period of wind abandonment can effectively alleviate the wind abandonment phenomenon. It also can provide more space for the wind power and enhance the wind power consumption.
Effective diagnosis of rotating machinery is difficult in view of the complex structure, weak early fault signals, non-stationary and non-linear vibration signals, and low signal-to-noise ratio. In this paper, a fault...
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Effective diagnosis of rotating machinery is difficult in view of the complex structure, weak early fault signals, non-stationary and non-linear vibration signals, and low signal-to-noise ratio. In this paper, a fault diagnosis method is proposed based on particleswarmoptimization(PSO) and variational modal decomposition(VMD). Firstly, wavelet packet threshold is denoised on the signal, VMD is decomposed on the reconstructed signal, and PSO is optimized on the inherent mode function(IMF) obtained from decomposition so as to determine the best IMF function. Then Hilbert transform and envelope spectrum analysis are carried out on the IMF function, and the envelope spectrum analysis result is compared with theoretical calculation frequency to finally determine the fault type. The results indicate that this method can effectively reduce noise components in signals, extract weak fault information and realize fault diagnosis.
Carmine is a widely used food pigment in various food and beverage additives. Excessive consumption of synthetic pigment shall do harm to body seriously. The food is generally associated with a variety of colors. Unde...
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ISBN:
(数字)9781510619784
ISBN:
(纸本)9781510619784
Carmine is a widely used food pigment in various food and beverage additives. Excessive consumption of synthetic pigment shall do harm to body seriously. The food is generally associated with a variety of colors. Under the simulation context of various food pigments' coexistence, we adopted the technology of fluorescence spectroscopy, together with the PSO-SVM algorithm, so that to establish a method for the determination of carmine content in mixed solution. After analyzing the prediction results of PSO-SVM, we collected a bunch of data: the carmine average recovery rate was 100.84%, the root mean square error of prediction (RMSEP) for 1.03e-04, 0.999 for the correlation coefficient between the model output and the real value of the forecast. Compared with the prediction results of reverse transmission, the correlation coefficient of PSO-SVM was 2.7% higher, the average recovery rate for 0.6%, and the root mean square error was nearly one order of magnitude lower. According to the analysis results, it can effectively avoid the interference caused by pigment with the combination of the fluorescence spectrum technique and PSO-SVM, accurately determining the content of carmine in mixed solution with an effect better than that of BP.
Ant colony algorithm is based on Ant System(AS) and it is a very important group intelligence algorithm,which is used in many fields,but there are also some *** classical ant colony algorithm is analyzed and studied,a...
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Ant colony algorithm is based on Ant System(AS) and it is a very important group intelligence algorithm,which is used in many fields,but there are also some *** classical ant colony algorithm is analyzed and studied,and an improved P-ACS algorithm is proposed based on ACS algorithm in this *** analysis and experiment,it is found that although the performance of ACS algorithm is higher than AS algorithm,there are still some problems,such as:falling into local optimal solution,search stagnation,and slow initial *** important reason for the above problems is that the pheromone update can not accurately reflect the actual situation of the *** at this problem,a P-ACS ant colony algorithm is proposed based on particle swarm optimization algorithm(PSO).The algorithm optimizes the pheromone update strategy from three aspects:pheromone concentration range setting,initial pheromone setting and global update strategy improvement.
When the power system subjected to disturbances, stability is a challenging task. The Power System Stabilizer plays an important role to reduce the low frequency oscillation (LFO) and enhance the performance. This is ...
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ISBN:
(纸本)9781479974566
When the power system subjected to disturbances, stability is a challenging task. The Power System Stabilizer plays an important role to reduce the low frequency oscillation (LFO) and enhance the performance. This is because, the PSS is low cost, flexible and easy to implement. In this work the problem is designed as a single objective optimization technique to tune the PSS parameters with Eigenvalue analysis. Here the Invasive Weed optimizationalgorithm which is found suitable for these types of problems is selected as a tool to find optimal solutions. Simulations are executed on a 4-machine power system for different operating conditions such as heavy load, light load and capacitive load. The results are obtained under different fault conditions with Invasive Weed optimization technique and compared the same with PSO. At last it is observed that the IWO technique performs better in damping overshoot and settling time.
To find out the position of the rod with its shadow, a model for determining the position of the straight rod with the objective function of minimizing the error value is established. Some results had been obtained by...
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To find out the position of the rod with its shadow, a model for determining the position of the straight rod with the objective function of minimizing the error value is established. Some results had been obtained by particle swarm optimization algorithm, and were classified by the system cluster analysis to achieve the optimal results. After that, the optimal results were tested.
Grid task scheduling(GTS)is a NP-hard *** paper proposes an optimized GTS algorithm which combines with the advantages of cloud model based on the particleswarmoptimization *** algorithm iterates tasks utilizing the...
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Grid task scheduling(GTS)is a NP-hard *** paper proposes an optimized GTS algorithm which combines with the advantages of cloud model based on the particleswarmoptimization *** algorithm iterates tasks utilizing the advantages of particle swarm optimization algorithm and then gets a set of candidate solutions *** addition,this algorithm modifies the value of entropy and excess entropy using the characteristics of cloud model and implements the transformation between qualitative variables and quantity of uncertain *** this algorithm makes particles fly to the global optimal solutions by exact searching in local areas. Theoretical analysis and simulation results show that this algorithm makes load balance of resource *** also avoids the problems of genetic algorithm and basic particle swarm optimization algorithm,which would easily fall into local optimal solutions and premature convergence caused by too much selected *** algorithm has the advantages of high precision and faster convergence and can be applied in task scheduling on computing grid.
Accurate cancer diagnosis can be achieved by performing microarray expression data classification. Various technology, including Support Vector Machines (SVMs), K Nearest Neighbor method (KNN), Neuro-Fuzzy models(NF),...
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Accurate cancer diagnosis can be achieved by performing microarray expression data classification. Various technology, including Support Vector Machines (SVMs), K Nearest Neighbor method (KNN), Neuro-Fuzzy models(NF), Neural Network (NN), etc. have been applied to analyze microarray expression data. In this paper, Complex Network based on genetic programming and particleswarmoptimization is proposed for analyzing microarray expression data. We propose an automatic method for constructing and evolving our complex network model. The structure of complex network is evolved using genetic programming, and the fine tuning of the parameters encoded in the structure is accomplished using particle swarm optimization algorithm. The relative performances of our model are reported. The results are comparable to those previously obtain.
With the rapid development of artificial intelligence, intelligent processing systems have slowly entered our lives. The control of intelligent machines through computers can improve the efficiency of work. The RGV is...
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With the rapid development of artificial intelligence, intelligent processing systems have slowly entered our lives. The control of intelligent machines through computers can improve the efficiency of work. The RGV is an unmanned, smart car that can run freely on a fixed track. According to the working conditions of RGV, the corresponding model is established, and three sets of data are given for specific analysis and calculation.
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