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The increasing growth in the use of DC Servomotors for multiple industrial applications in the last few decades have made them one of the most important system's drives. Therefore, developing an intelligent DC Servomotor position control scheme and, in particular, a DC Servomotor Neural Model based on a well-defined mathematical model that can be used for off-line simulation are very important tools...
At present, the backward dissemination Algorithm of nerve network is applied widely in the field of rule extraction and knowledge discovery. This paper analyzed the function characteristics of nerve network and backward dissemination classification Algorithm, and introduced a few method which extracts rule knowledge in previously-feed nerve network.
The operation principles of proton exchange membrane (PEM) fuel cell system relate to thermodynamics, electrochemistry, hydrodynamics, mass transfer theory, which form a complex nonlinear system, and it is different to establish its mathematical model. This paper utilizes the approach and self-study ability of artificial neural network to build a model of nonlinear system, and adapts the modified...
The ever increasing need for energy efficient systems has led to various ingenious ideas about energy management. A major offshoot of this search for energy efficient solutions is demand management in power systems. The goal of any demand management program is to control the demand for electric power among customers thereby creating load relief for electric utilities and improving system security...
BP neural network (back propagation neural network) is a mathematical model for machine learning. It has a strong advantage in terms of prediction of the future events, and taking into account the different applications, its impact factors are different, which makes the model complex and diverse. A general modeling approach is proposed, which creates and stores BP neural network model dynamically,...
The prestressed loss of group anchor in rock slope increase with time, which leads to the compression belt of structure plane in group anchor area was weakened, deformation of rock surface toward the free surface direction increase gradually, as a result, the slope stability was drastically reduced. Based on the group anchor layout of the abutment rock slope of an arch dam, the anchor-hold monitoring...
Firstly, according to the Beijing urban rail transit network characteristics and based on the data of the historical passenger flow, the passenger flow in sections is distributed and the referenced passenger flow in sections is gotten on the theoretical basis of the shortest path distribution of static unbalanced distribution model. Then through a lot of BP neural network modeling experiments, a reasonable...
The paper presents the design of three types of neural networks with different features, including traditional backpropagation networks, radial basis function networks and counterpropagation networks. Traditional backpropagation networks require very complex training process before being applied for classification or approximation. Radial basis function networks simplify the training process by the...
Biometric technology is used in several security applications at present. The biometric information and classification have large impact in efficiency of the application. Teeth are chosen as a characteristic for biometric system in this research since teeth are difficult to be reshaped by intent surgery like well-known features such as face, palmprint and fingerprint. In this paper, appropriate features...
We present several modifications of the original recurrent neural network language model (RNN LM).While this model has been shown to significantly outperform many competitive language modeling techniques in terms of accuracy, the remaining problem is the computational complexity. In this work, we show approaches that lead to more than 15 times speedup for both training and testing phases. Next, we...
High voltage submersible motor works in deep water all the year around, and its operating insulation performance deteriorates influenced by the complex environment. Due to the special installed circumstances, the motor can not be readily maintained. Because of the losses caused by motor deterioration, the prediction of the insulation life-expectancy has a great significance. This paper analyzes the...
The basic principle of Artificial Neural Networks and BP algorithm was introduced in this paper. The application of BP algorithm Artificial Neural Networks in fault diagnosis of 40TM liquid-gas hammer was studied. The superiority of BP algorithm Artificial Neural Networks in fault diagnosis was proved by the MATLAB simulation and the training. The causes of faults were determined by BP algorithm Artificial...
This paper introduces a method for the fault diagnosis of a rotor system. For a vibration signal of a rotor system fault, an AR model is established first, and then the related parameter and amplitude spectrum of this mode can be obtained, etc. The experiments show the above-mentioned method can effectively diagnose the fault of a rotor system.
The cost of experimental setup during an assembly process development of a chipset, particularly the under-fill process, can often result in insufficient data samples. In INTEL Malaysia, for example, the historical chipset data from an under fill process consists of only a few samples. As a result, existing machine learning algorithms for predictive modeling cannot be applied to this setting. Despite...
Today's advanced muscular sensing and processing technologies have made the acquisition of electromyography (EMG) signal which is valuable. EMG signal is the measurement of electrical potentials generated by muscle cells which is an indicator of muscle activity. Other than rehabilitation engineering and clinical applications, EMG signals can also be employed in the field of human computer interaction...
The demand of power and the size and complexity of the power system is increasing. Wide area monitoring and control is an integral part in transitioning from the traditional power system to a Smart Grid. However, wide area monitoring becomes challenging as the size of the electric power grid, and consequently the number of components to be monitored, grows. Wide area monitor (WAM) designed using feed-forward...
In this paper, we present an application of artificial neural networks to the real-world problem of predicting forest fire. The neural network used for this application is a multilayer perceptron whose architectural parameters, i.e., the number of hidden layers and the number of neurons per layer were heuristically determined. The synaptic weights of this architecture were adjusted using the backpropagation...
A novel overlapping swarm intelligence algorithm is introduced to train the weights of an artificial neural network. Training a neural network is a difficult task that requires an effective search methodology to compute the weights along the edges of a network. The backpropagation algorithm, a gradient based method, is frequently used to train multilayer feed-forward networks. Gradient based methods...
This paper uses generalized congruence function instead of transfer function of classical BP neural network, and improve convergence rate of neural network. We introduce the subsection generalized derivation, error back propagation derivation mechanism of classical BP algorithm to adjust weight vector in generalized congruence neural network, and modify generalized congruence neural network, and then...
After studying the disadvantage of BP neural network which has low convergent speed and trap into local minima easily, an idea of designing a new hybrid neural network model. By using Artificial Bee Colony Algorithm (ABC) to expand the updated space of weight and using the fitness functions to decide the better weight. On the basis, make the acquired better value as the weight of BP neural network...
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