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Handwritten Bangla digit recognition is one of the most attractive area for researchers who have interest in image processing and pattern recognition field. In our everyday activities like bank check identification, passport and document analysis, number plate identification and especially in our postal automation service, recognition of handwritten digits plays a significant role. That's why a rich...
License plate detection and character recognition have unveiled new possibilities and challenges in the field of intelligent transport system. Numerous algorithms have been proposed regarding license plate localization and tracking, character segmentation and character recognition. License plate character recognition is still an active area of research specially in terms of processing complexity....
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...
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...
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...
Face is a complex multidimensional visual model and developing a computational model for face recognition is difficult. The paper presents a methodology for face recognition based on information theory approach of coding and decoding the face image. Proposed methodology is connection of two stages - Feature extraction using Principle Component Analysis and recognition using the feed forward back propagation...
Local minimum is incorporated problem in neural network (NN) training. To alleviate this problem, a modification of standard backpropagation (BP) algorithm, called BPCL for training NN is proposed. When local minimum arrives in the training, the weights of NN become idle. If the chaotic variation of learning rate (LR) is included during training, the weight update may be accelerated in the local minimum...
Aiming at the disadvantages of prediction model of single BP neural network, a prediction model was presented by combining AdaBoost algorithm and BP neural network for improving the forecasting accuracy of single BP neural network. A new updating method is proposed for the characters of ensemble BP neural network based on AdaBoost. The new method can update the model effectively and overcome the disadvantage...
Combining the intelligent algorithm such as BP neural network and support vector maching (SVM) with traditional chemical method, this paper models the relationship between plant surface color and its pigment. Using the neural network model constructed above, people can figure out the content of plant pigments by getting the corresponding plant surface color information. Compared with the traditional...
The goal of this project is thus to experiment with ANNs and to evaluate performance of ANN models in studying stock price patterns in time by attempting to predict future results of a time-series by simply studying patterns in the time-series of stock prices. In this project we have instantiated the proposed Neural Network using the stock prices of Iran Tractor Manufacturing Company during two years...
This paper focused on experimental data and study for the testing of the material mechanical properties using vibration technique. By applying vibration analysis and testing on the material, we could determine the natural frequencies, the damping ratio and mode shapes of the structure. However, in this study, we only considering the natural frequencies of the material as the input data needed for...
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