Optimization of impulse water turbine based on GA-BP neural network arithmetic

Tang, Lingdi; Yuan, Shouqi; Tang, Yiming; Qiu, Zhipeng

doi:10.1007/s12206-018-1224-3

Cited by 21 publications

(10 citation statements)

References 21 publications

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“…The AHP weight analysis reveals that the negative impacts on water environment mainly come from the hydrogeological conditions (Tang et al, 2019). In the target tunnel, the SK2 + 460~SK2 + 280 segment had the greatest negative impacts on water environment, followed by the SK2 + 280~SK1 + 909.9 segment and the SK3 + 726.7~SK3 + 400 segment.…”

Section: Figure 7 Ahp Analysis On Tunnel Water Environmentmentioning

confidence: 99%

Analysis and Prevention of the Impacts of Metro Construction on Groundwater Environment

Dai¹

2019

Appl. Ecol. Env. Res.

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Despite its positive impacts on traffic convenience and resource delivery, metro construction tilts the balance of groundwater resources and destabilizes the groundwater environment. This paper explores the impacts of shield tunnel construction on groundwater environment from the design and construction to an operating metro project, and verifies these impacts through an analysis on the tunnel project in Jinan Metro Line R3. The research shows that the grouting in shield tunneling has a local influence on the groundwater quality and pH, which attenuates with the increase of distance to the tunnel axis; the scope of influence is constrained by the formation lithology. Then, the backpropagation (BP) neural network was adopted to predict the ejection volume of groundwater, and the main influencing factors of water environment were disclosed by analytical hierarchy process (AHP). Finally, the author discussed the key techniques and prevention systems for prevention of the impacts of shield tunnel construction on water environment.

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Section: Figure 7 Ahp Analysis On Tunnel Water Environmentmentioning

confidence: 99%

Analysis and Prevention of the Impacts of Metro Construction on Groundwater Environment

Dai¹

2019

Appl. Ecol. Env. Res.

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“…By transmitting the output error back, the error is distributed to all units in the original layer, so as to further obtain the error signal of each layer unit and then correct the weight of each unit. Through repeated training, the weight of network samples and the offset value of samples are continuously modified until the predetermined error accuracy is reached [ 4 ]. From this point of view, it is very important to strengthen the application research of computer multimedia technology in web design, which is helpful to provide reference for the follow-up work.…”

Section: Introductionmentioning

confidence: 99%

Optimization of Computer Web Page Interface Based on BP Neural Network Algorithm and Multimedia

2022

Computational Intelligence and Neuroscience

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In web design, we need to make full use of computer multimedia technology, which can effectively improve the quality of web design and provide greater convenience. The neural network needs to calculate a large amount of training data in image optimization, and the calculation speed cannot keep up with real-time data processing, resulting in the problem of poor quality of optimized images. This paper analyzes the problems existing in the traditional optimized BP neural network algorithm and puts forward an optimized BP neural network image optimization method which combines the increase of momentum term with the adaptive adjustment of learning rate. This method can speed up the iteration speed and jump out of the situation of premature local minimum. The test results show that the user satisfaction of the text visual effect of the web interface optimized by this method is more than 98% and the user satisfaction of other methods is only about 90%. The visual satisfaction of the web interface optimized by this method is significantly higher than that of the comparative method. The web interface visual optimization effect of the method in this article is better, and it can meet the satisfaction requirements of most users.

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“…e literature [8] proposes to use the minimum cross-entropy criterion to implement the number of iterations of the PCNN feature segmentation algorithm and to realize the automatic selection of the optimal threshold for feature segmentation. e principle is to combine the cross-entropy algorithm with the PCNN algorithm to automate the setting of the number of iterations of the PCNN feature segmentation algorithm by judging the difference in the amount of information contained between the original features and the segmentation results and selecting the segmentation result with the minimum cross-entropy as the termination condition.…”

Section: Introductionmentioning

confidence: 99%

Construction of a Knowledge Map of Speech Emotion Features Based on Impulse-Coupled Neural Networks

Song

2022

Computational Intelligence and Neuroscience

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This paper constructs knowledge graphs of speech emotion feature to support the expression of rich semantic information due to their unique graphical structure and to provide new ideas for studying speech emotion recognition recommendations. Impulse-coupled neural networks, as a mathematical abstraction of the visual properties of the human eye, have been widely used in various fields of speech processing. In this paper, we take the classical impulse-coupled neural network model as the research object, aiming to explore, analyze, and study the method of constructing knowledge maps of speech emotion features based on the impulse-coupled neural network model, and propose several improved impulse-coupled neural network models, which are used in the fields of target detection, speech segmentation, and quantization compression. This paper further constructs various domain semantic concept maps and performs multidimensional semantic enhancement understanding of search text based on the concept maps and the constructed entity-relationship knowledge maps and proposes a knowledge-based interpretable recommendation method for cloud services and a generalized recommendation and sample enhancement method for cloud scenarios. The fusion algorithm based on multiscale analysis can decompose the source speech into subspeech at different scales and then fuse each subspeech separately, while typical objects in the real world are also composed of many components at different scales. Based on the factors of different degrees in the speech context, the imagery work ruler evaluation model is refined with the basic principles of risk perception and risk resolution in the context, and an exploratory design is carried out separately for the verbal description, graphics, text, color, animation, and sound signals in the audiovisual signal using the workshop format to obtain a large number of design samples and evaluate the important units in turn, finally integrating the context involved in the study. The perceptual design system is given as a specific contextual design method.

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Optimization of impulse water turbine based on GA-BP neural network arithmetic

Cited by 21 publications

References 21 publications

Analysis and Prevention of the Impacts of Metro Construction on Groundwater Environment

Analysis and Prevention of the Impacts of Metro Construction on Groundwater Environment

Optimization of Computer Web Page Interface Based on BP Neural Network Algorithm and Multimedia

Construction of a Knowledge Map of Speech Emotion Features Based on Impulse-Coupled Neural Networks

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