Papers by Keyword: BP Neural Network (BPNN)

Abstract: Due to the complexity of the millimetre-wave indoor propagation environment, using the conventional methods to analyze propagation characteristics of radio wave leads to great error, and the computational complexity is high. In view of the above problems, the prediction method for propagation characteristics of the indoor millimetre wave based on BP neural network is proposed; using its function approximation to describe the millimetre wave propagation parameter, finding out the mathematical relationship between its corresponding external factors and the signal attenuation, the mathematical logic relationship is constructed through establishing the prediction model. Simulation results show that using this method can quickly and intuitively obtain the relationship between the propagation distance and field intensity or path loss, respectively, with advantages of taking short time and high computational efficiency.

Abstract: Teaching quality evaluation plays a key role for universities to improve its teaching quality and becomes a hot spot research field for related researchers. In this paper, we established the evaluation model of teaching quality based on BP neural network. Firstly an evaluation index system of teaching quality is designed. Then, according to the system we design the structure of BP neural network, determine the parameters and give the algorithm description. Finally, we program and verify the validity of the model in MATLAB environment. The experimental results show that the model can evaluate teaching quality practically by the evaluation index.

Abstract: The problem is solved that it is hard to provide analysis formulas about the maximum equivalent stress, the maximum shear stress and the structural geometric parameters for a ship. The finite element calculation is done with orthogonal experimental design under the most dangerous case. The data obtained are used as the training and test samples to establish BP neural network models of ship’s maximum equivalent stress and maximum shear stress. With the aid of Neural network toolbox in MATLAB, the topological structure of BP neural network mapping relationship between the whole ship performance indexes and design variables is established. The training and testing are completed with the data tested by the shipyard and the correctness of this network is verified. The neural network required for further optimization design is obtained. The neural network is helpful in reducing the ship mass without exceeding the allowable stress.

Abstract: Thin-walled aluminum alloy parts are widely used in the aviation industry. In order to predict the deformation of milling aluminum alloy 7075-T7451 thin-walled parts, a deformation prediction method based on BP artificial neural network is presented. Firstly, the orthogonal experiment is designed to acquire the experimental data. Secondly, the BP neural network model of deformation prediction based on the experimental data is established. The comparison of the simulated values with the experimental results is performed to validate the proposed model. Lastly, the result shows that the proposed deformation prediction model is reasonable and can be used to predict the milling deformation.

Abstract: Due to considerations limited for the current monitoring techniques and computational models and other reasons,the accuracy rate of line icing condition assessment is not high. Transmission line icing are affected by many factors, having greater relevance with micro-meteorological parameters. To improve the assessment accuracy of transmission line icing condition,multi-sensor information fusion method are put forward for a comprehensive assessment to Line icing state, based on online monitoring system,considering the equivalent ice thickness of monitoring system, micro-meteorological parameters and duration of ice cover.BP neural network convergence line icing membership value, the output state is cing probability. Then ,the probability of the state of uncertainty output line integrated assessmen through Fuzzy Reasoning

Abstract: Accurate assessment of the operational status of transmission line,and the line status timely warning, can protect the stable operation of the transmission line. Not high accuracy assessment for the current state of the transmission line,assessment model of transmission line state based on neural networks and fuzzy logic decisions are put forward,built on online monitoring system, Considering the conductor temperature, angle, tension and other parameters.Using BP neural network convergence line fault membership values, and the output state is line fault probability. Then ,the uncertainty of the state probability output line integrated assessmen through Fuzzy Reasoning.

Abstract: Electric power industry is a basic industry of national economy, the power plant production safety related to people's life safety and property of the state, the power of reform and social stability, safety evaluation of power generation enterprises is an important guarantee of safety production in power generation enterprises.The paper establishes the BP neural network model, utilize BP neural network optimization ability and good fitting ability, combining the index system build, carries on the appraisal to the power generation enterprise security.Now the instance verification results show that BP neural network is applied in safety evaluation of power generation enterprises, not only can accurately evaluate the safety situation of power generation enterprises, and the speed of convergence process is quickly.

Abstract: Traffic state index (TSI) is a quantitative indicator to evaluate the degree of traffic congestion. Accurate prediction of the TSI can effectively ease the traffic pressure. This paper presents a prediction model based on the hybrid intelligent method. Firstly, use the cross operator and mutation operator to generate the particles and use the simulated annealing algorithm (SA) to prevent the particles falling into local optimum for the basic particle swarm algorithm (PSO). Secondly, use the improved PSO algorithm to optimize the weights and thresholds of the BP neural network (BPNN). Finally, Train the BPNN to obtain the optimal solution. The hybrid intelligent methods prediction model, named IPSOBP, is verified by using the actual data. The results show that the prediction model has higher accuracy to predict TSI compared with BPNN improved by genetic algorithm (GA) and BPNN improved by PSO.

Abstract: During the course of building an innovative country and enhancing the independent innovation capability, universities are the main force and the important source of high-tech innovation. The evaluation on the university's innovation ability, not only may improve university's efficiency and level of scientific research, but also make a significant sense to perfect the china' scientific research innovation system. Based on Referring to the recent research achievements at home and abroad, research and design work was carried out in the following area. Firstly, the multi-university research innovation ability evaluating indicator system is designed in this paper. By the principle of science and justice, through questionnaires, expert opinion and reference to relevant research results. The paper designed the multi-university's research innovation ability evaluating indicator system. A variety of typical evaluation models and methods are studied. Then two evaluation models between PCA-BP and PCA-FNN are taken into comparison. And the results show that the research and application of PCA-FNN is proved to be a new method and made a significant attempt for the university’s evaluation of research innovation ability.

Abstract: The paper constructs an evaluation model for practical teaching quality based on Back Propagation (BP) neural network. It makes the indicators of evaluating practical teaching quality as input data, while practical teaching quality as output results. The empirical conclusion obtained from the use of Excel is that BP neural network is suitable for practical teaching quality evaluation and also makes a better analogy to the experts’ evaluation process. The results are satisfactory with wide application.