To improve the product quality and production efficiency in industrial production, the industrial production process is explored. First, for the production state in industrial production, the radio frequency identific...
详细信息
To improve the product quality and production efficiency in industrial production, the industrial production process is explored. First, for the production state in industrial production, the radio frequency identification technology (RFID) is used to monitor the state of the nodes in the production process and collect data. Based on the problem of blind area in industrial production, an adaptive controller design based on uncertain nonlinear dynamic systems is introduced;second, based on this, for the problem that product quality is difficult to guarantee in the process flow, the improved multi-layer feedforward network (back propagation, bp) algorithm is used to predict it. Finally, the control diagnosis algorithm based on multi-order least squares support vector machine (LS-SVM) is used to analyze the abnormal cause of the product. The results show that the use of the RFID can monitor the production process in real time and obtain real-time product quality information data. The proposed adaptive controller based on uncertain nonlinear dynamic system has good applicability in solving the problem of blind area. The improved bp neural network algorithm improves the prediction accuracy in the process of product quality prediction and increases the convergence speed of the algorithm. The control diagnosis algorithm based on multi-order least squares that support vector machine (SVM) can classify and learn the historical data of products, as well as perform multi-order search and analysis on the causes of abnormal quality. It helps relevant personnel to carry out process improvement and control, thereby achieving the purpose of improving product quality. Through this investigation, it is found that the method proposed can monitor the state of industrial production in real time and help relevant personnel to control and predict product quality. It can be applied in actual processes.
Fluorescence spectroscopy attracted more and more attention in pesticide residue detection field because of its advantages of non-destructive, non-contact, high speed and no requirement of complex pre-process procedur...
详细信息
Fluorescence spectroscopy attracted more and more attention in pesticide residue detection field because of its advantages of non-destructive, non-contact, high speed and no requirement of complex pre-process procedure. However, given that the concentration of the pesticide detected via fluorescence spectroscopy is calculated in accordance with the Beer-Lambert law, this method can only be used to detect samples containing a single kind of pesticide or several kinds of pesticides with completely different fluorescence which is not in accordance with practical cases. In this article, to overcome this disadvantage, back-propagation (bp) neuralnetworkalgorithm was introduced to detect multiple kinds of pesticides via fluorescence spectroscopy. The results from four kinds of pesticides which are usually used for fruits and vegetables indicated the effectiveness of bp neural network algorithm.
The objective is to realize the early warning of disasters caused by mountain mass landslide. The probable causes of mountain mass landslide were predicted and analyzed in prior by constructing the back propagation (B...
详细信息
The objective is to realize the early warning of disasters caused by mountain mass landslide. The probable causes of mountain mass landslide were predicted and analyzed in prior by constructing the back propagation (bp) neuralnetworkalgorithm, which included earthquake, rainstorm, human activity, landslide displacement, slope gradient, and soil texture. In terms of the early warning of mountain mass landslide caused by earthquakes, rainstorm, or human activities, the accuracy of bp neural network algorithm was relatively high;especially, given the relevant data such as the free slope gradient, slide surface slope gradient, and soil texture of the mountain mass, the accuracy of bp neural network algorithm in the early warning of mountain mass landslide could reach 94.7%;the proposed algorithm could predict not only the occurrence possibility of mountain mass landslide but also the severity and possible range of mountain mass landslide. In addition, in terms of stability, the standard deviation of the proposed algorithm was 0.0062, which indicated the fairly good stability of the algorithm. The possible mountain mass landslide was predicted based on the comprehensive analysis of probable causes of mountain mass landslide and their proportions of weights by using the bp neural network algorithm;the accuracy and stability of the proposed algorithm were excellent, which also showed that the occurrence of mountain mass landslide was a comprehensive consequence caused by various factors and could never be predicted through singular factor analysis. Thus, the understanding of both bp neural network algorithm and mountain mass landslide was greatly improved.
In order to solve the relatively lack of research on the wind speed prediction of domestic transmission lines. In this paper, the time series analysis method is used to predict the wind speed of the transmission line,...
详细信息
In order to solve the relatively lack of research on the wind speed prediction of domestic transmission lines. In this paper, the time series analysis method is used to predict the wind speed of the transmission line, and the prediction accuracy is not high. By consulting related references, this paper proposes a combination of bp neural network algorithm and genetic algorithm GA-bp neural network algorithm combined with time series analysis method to obtain high-precision wind speed prediction algorithm. Finally, using the advantages of MapReduce distributed operation mechanism, the GA-bp neural network algorithm is implemented on MapReduce. The simulation results show that the algorithm has a great improvement in prediction accuracy compared with the time series analysis method.
Highway construction project does not exist for its own, but also to meet the needs of the society. Its development strategy should be based on the overall goal of the society, not just for its own. Therefore, the sus...
详细信息
Highway construction project does not exist for its own, but also to meet the needs of the society. Its development strategy should be based on the overall goal of the society, not just for its own. Therefore, the sustainable evaluation of the highway construction should be considered from the two parts of sustainability of social needs and economic development. In this paper, using the bp neural network algorithm, through the analysis of sustainable development of the following four areas in road construction: economics, environmental resources, operations, management systems and policy, the author studies the sustainable development evaluation of highway construction project.
In order to realise the prediction of the diffusion trend of chemical gases under toxic, flammable, and explosive conditions, this article used a multiple regression model and a back propagation (bp) neuralnetwork mo...
详细信息
In order to realise the prediction of the diffusion trend of chemical gases under toxic, flammable, and explosive conditions, this article used a multiple regression model and a back propagation (bp) neuralnetwork model, established two kinds of leakage gas diffusion models based on Fluent simulation data. First, the multivariate function relation between multiple influencing factors and diffusion concentration is established by using linear fitting method, i.e. multivariate regression model. Second, according to the large number and non-linearity of Fluent simulation data of leakage gas, a three-layer bpneuralnetwork prediction model for leakage gas, wind speed, X-axis diffusion distance, and Y-axis diffusion distance was established by using bp neural network algorithm. Under the same data conditions, the prediction error of bpneuralnetwork prediction model is smaller than that of multivariate reversion model, and the fitting degree is high, but the stability of multiple linear regression is better.
Highway construction project does not exist for its own, but also to meet the needs of the society. Its development strategy should be based on the overall goal of the society, not just for its own. Therefore, the sus...
详细信息
Highway construction project does not exist for its own, but also to meet the needs of the society. Its development strategy should be based on the overall goal of the society, not just for its own. Therefore, the sustainable evaluation of the highway construction should be considered from the two parts of sustainability of social needs and economic development. In this paper, using the bp neural network algorithm, through the analysis of sustainable development of the following four areas in road construction: economics, environmental resources, operations, management systems and policy, the author studies the sustainable development evaluation of highway construction project.
Femtosecond laser processing has been extensively used in micromachining, especially for the precision processing of hard and brittle materials. However, the precision of the materials ablated by femtosecond laser is ...
详细信息
ISBN:
(数字)9781510630642
ISBN:
(纸本)9781510630642
Femtosecond laser processing has been extensively used in micromachining, especially for the precision processing of hard and brittle materials. However, the precision of the materials ablated by femtosecond laser is not easy to control. This paper reports an experimental and theoretical study on the ablation characteristics of fused silica using high repetition rate femtosecond laser. An experimental study of microchannels milling on the fused silica was carried out. The influence of pulse energy, repetition rate, scanning velocity, scanning times on the size and morphology of the microchannels was obtained. Simultaneously, the experimental data on the depth and width of microchannels under different parameter combinations were acquired through the orthogonal experiment. The prediction model of aspect ratio was obtained by bp neural network algorithm. Finally, the verification test was established and showed that the experimental results were consistent with the theoretical results. It would provide a theoretical basis for further study on the microchannels fabrication of femtosecond laser.
The output power of distributed photovoltaic power supply is mainly affected by environmental and meteorological conditions. The output power has great randomness and fluctuation. If the output power of photovoltaic c...
详细信息
ISBN:
(纸本)9781538681787
The output power of distributed photovoltaic power supply is mainly affected by environmental and meteorological conditions. The output power has great randomness and fluctuation. If the output power of photovoltaic cells can be accurately predicted, it will be of great significance to the optimal dispatch of distribution network. In this paper, based on the improved bp neural network algorithm, considering the correction of solar radiation intensity of photovoltaic cloud cover and the correction of output power fluctuation of similar day history, a comprehensive forecasting method of output power of photovoltaic power generation is established, and satisfactory forecasting results are obtained through simulation and analysis.
To improve the poor intelligence and personalized service of the learning system in current distance education and training, a personalized learning system model based on data mining technology was proposed. Then, the...
详细信息
To improve the poor intelligence and personalized service of the learning system in current distance education and training, a personalized learning system model based on data mining technology was proposed. Then, the method of applying the decision tree and bp neural network algorithm to design the system was described in detail. Finally, the core module of the personalized distance education system combined with Web was designed. The personalized function module introduced how the user operates the intelligent Web reasoning in the module according to the user input learning information and gave the most matching learning materials. Finally, the application results showed that the system greatly improved the personalized service module.
暂无评论