Due to its complex application environment, hydraulic pile hammers are difficult to model and accurately grasp their motion laws in automation control. Therefore, to address the high-precision prediction problem of th...
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Due to its complex application environment, hydraulic pile hammers are difficult to model and accurately grasp their motion laws in automation control. Therefore, to address the high-precision prediction problem of the motion law of hydraulic pile hammer systems under complex working conditions, a knowledge embedding surrogate model based on a dual neural network is designed, which can be divided into two parts: feature extraction network and prediction network. On this basis, the model introduces physics knowledge embedding technology, adds inequality constraints based on physical laws to the loss function, and introduces transfer learning algorithms to maintain high accuracy of the model under limited data conditions. The results showed that the PSM (gamma = 0.5) model designed in the study had a median of -0.001 and a variance of 0.038 under undisturbed conditions, demonstrating high prediction stability. Under perturbation conditions, the median of the PSM (gamma = 1.5) model was -0.003, with a variance of 0.031, indicating the highest prediction accuracy. From this, the research model has good prediction accuracy under complex working conditions, which can lay a technical foundation for predicting the motion law of hydraulic pile hammers and automatic control.
To performance evaluating problem of transfer algorithms in opportunistic networks, real GPS data is used as experimental dataset in this paper. The performance of a fault-tolerant transfer algorithm based on principa...
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ISBN:
(纸本)9783642233449
To performance evaluating problem of transfer algorithms in opportunistic networks, real GPS data is used as experimental dataset in this paper. The performance of a fault-tolerant transfer algorithm based on principal component analysis is evaluated. According to the characteristic of algorithm, different ratio of lost data (10%, 20%, 30% and 40%) is tested in the experiments. Experimental results show that received track curve recovered by the algorithm is continuous and there is not gap, which can reflect the basic original information. Based on the experimental results, it is proved that the algorithm has good fault-tolerant performance and practicability.
Public transportation is not only a significant symbol of the urban modernization, but also an optimal approach of solving urban crowded traffic problem. The bus route search algorithm is the key technical query syste...
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ISBN:
(纸本)9781479942626
Public transportation is not only a significant symbol of the urban modernization, but also an optimal approach of solving urban crowded traffic problem. The bus route search algorithm is the key technical query system. This paper mainly discusses an algorithm based on set theory and proposes technological flow of transfer algorithm. An improved plan is presented. The algorithm is simple and effective, helping users select bus route quickly.
Partitioning methods, such as k-means, are popular and useful for clustering. Recently we proposed a new partitioning method for clustering categorical data: using the transfer algorithm to optimize an objective funct...
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ISBN:
(纸本)9783319133324;9783319133317
Partitioning methods, such as k-means, are popular and useful for clustering. Recently we proposed a new partitioning method for clustering categorical data: using the transfer algorithm to optimize an objective function called within-cluster dispersion. Preliminary experimental results showed that this method outperforms a standard method called k-modes, in terms of the average quality of clustering results. In this paper, we make more advanced efforts to compare the performance of objective functions for categorical data. First we analytically compare the quality of three objective functions: k-medoids, k-modes and within-cluster dispersion. Secondly we measure how well these objectives find true structures in real data sets, by finding their global optima, which we argue is a better measurement than average clustering results. The conclusion is that within-cluster dispersion is generally a better objective for discovering cluster structures. Moreover, we evaluate the performance of various distance measures on within-cluster dispersion, and give some useful observations.
This paper proposes a two-tier decision model and an algorithm for transferring between two different cities. In this model, the 1st tier makes the choice of the transfer between the cities considering the convenience...
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In many situations, one wishes to group objects into well-defined classes on the basis of one set of descriptor variables, and then predict the classes of new objects from a different set of variables. For example, a ...
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In many situations, one wishes to group objects into well-defined classes on the basis of one set of descriptor variables, and then predict the classes of new objects from a different set of variables. For example, a bank may categorise customers into distinct financial behaviour pattern classes by observing how they have behaved over a period of years, and then seek to assign new customers to future behaviour classes using information captured when they open an account. Such situations require the striking of a compromise between the compactness and integrity of the cluster structure, and the accuracy of the predictive assignment to clusters. We describe two algorithms for achieving such a compromise, discuss some of their features, and illustrate their performance in a simulation study and in a liver transplant problem.
transfer algorithms are usually used to optimize an objective function that is defined on the set of partitions of a finite set X . In this paper we define an equivalence relation ∾ on the set of fuzzy equivalence rel...
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transfer algorithms are usually used to optimize an objective function that is defined on the set of partitions of a finite set X . In this paper we define an equivalence relation ∾ on the set of fuzzy equivalence relations on X and establish a bijection from the set of hierarchies on X to the set of equivalence classes with respect to ∾. Thus, hierarchies can be identified with fuzzy equivalence relations and the transfer algorithm can be modified in order to optimize an objective function that is defined on the set of hierarchies on X .
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