Hybrid spiking neural network for sleep electroencephalogram signals

We propose a logistics optimization method based on improved graph convolutional networks to address the current problem of low product delivery rate and untimely product delivery during the peak period of e-commerce activities. Our method can learn excellent planning strategies from previous data and can give the best logistics strategy in time during the peak logistics period, which improves the product delivery rate and delivery time of logistics and greatly enhances the return on investment. First, we add a tensor rotation module to the graph convolution layer to better capture the global features of logistics nodes. Then we add inception structures in the temporal convolution layer to build multiscale temporal convolution filters to obtain temporal information of logistics nodes in different time-aware domains and reduce arithmetic power. Finally, we cooperate with e-commerce platforms to adopt logistics data as the experimental database. The experimental results show that our method greatly accelerates the logistics planning speed, improves the product delivery rate, ensures the timely delivery of products, and increases the return on investment.

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“…The proposed method is a general model. In the future, the proposed method can be applied to the fields of time series analysis [ 35 – 37 ].…”

Section: Discussionmentioning

confidence: 99%

Logistics Optimization Strategy Based on Deep Neural Framework

Liu

Zhu

2022

Computational Intelligence and Neuroscience

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“…It improves the classification efficiency and increases the reliability of the classification results. In addition, with the development of time-series analysis [ 24 – 28 ], some researchers combine time-series analysis methods to analyze.…”

Section: Research Progress Of Remote Sensing Classification Based On ...mentioning

confidence: 99%

Research on Land Use Planning Based on Multisource Remote Sensing Data

Wang

Pei

Lei

2022

Computational Intelligence and Neuroscience

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Land use changes are analyzed correctly, a series of improvements according to the changes are carried out appropriately, the relationship between land use development and economic and human survival is handled correctly, and the healthy and orderly development of the entire society is promoted. Aiming at the combination of multisource remote sensing data and monitoring changes in land planning, this study uses CBERS data and ASAR data as multisource remote sensing data sources to conduct in-depth research and discussion on the land use change in this area and uses the HPF pixel-level fusion method for data fusion to generate HPF. The data are integrated, and then, the CBERS data and HPF fusion data are used to extract the land use type information of Zhenning County, respectively, and a confusion matrix is built based on the field sample points to verify the accuracy, compare and analyze the relative error of the land use type information extraction before and after data fusion, and evaluate the CBERS data. Regarding the extraction effect of land use type information of fusion data with HPF, the results show that the two kinds of remote sensing data have good effects in extracting water body type information, and the accuracy has reached 100%. Using multisource remote sensing image processing can well summarize and analyze land use changes and make the changes in various indicators in the study area. Accurate statistics is obtained.

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“…technology has been developing in many fields [21][22][23][24][25][26]. Analytic hierarchy process (AHP), as a typical method of data analysis [27], was formally proposed in the mid-1970s.…”

Section: Construction Of Analytic Hierarchy Process Model For Evaluat...mentioning

confidence: 99%

Evaluation Method of Ideological and Political Classroom Teaching Quality Based on Analytic Hierarchy Process

Cheng

2022

Scientific Programming

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Constructing a scientific evaluation system of curriculum education quality is an important content to improve the effectiveness of curriculum ideological and political education. Starting from the practical significance of exploring the effectiveness evaluation system of curriculum ideological and political education, supported by analytic hierarchy process, this paper constructs the evaluation model of curriculum educational quality through the five dimensions of curriculum design, teaching staff, student cognition, development evaluation, and system design, clarifies the hierarchical relationship between the implementation elements of curriculum ideological and political education from the micro level, and defines the basic responsibilities, in order to provide reference for curriculum teaching reform and educational quality evaluation.

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Hybrid spiking neural network for sleep electroencephalogram signals

Cited by 41 publications

References 23 publications

Logistics Optimization Strategy Based on Deep Neural Framework

Logistics Optimization Strategy Based on Deep Neural Framework

Research on Land Use Planning Based on Multisource Remote Sensing Data

Evaluation Method of Ideological and Political Classroom Teaching Quality Based on Analytic Hierarchy Process

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