Traffic Guidance Based on LSTM Neural Network and Dual Tracking Dijkstra Algorithm

Zhang, Zhenghua; Fang, Chongxin; Zhang, Jiafeng; Jin, Qian; Quan, Stella

doi:10.1109/iciscae51034.2020.9236823

Cited by 4 publications

(2 citation statements)

References 20 publications

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“…For the different types of ideological and political education, this problem is trained based on the LSTM network with adaptive excitation function as shown in Figure 7, and the data rows with low temporal dependence, such as students' ideological and political scores, are input into the MIFS network based on the elastic backpropagation algorithm for training, and the output results obtained from each network are linearly fitted with probability to realize the cascade of the network and finally obtain the students' ideological and political quality level [17]. The system uses an LSTM neural network for training, and the LSTM excitation function is improved for the special characteristics of the time-series data so that the network model is sensitive to time and data.…”

Section: Ideological and Political Teaching Resources Recommendation ...mentioning

confidence: 99%

Development of ideological and political education course field dimensions based on multi-data chain network

2023

Applied Mathematics and Nonlinear Sciences

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This paper firstly classifies the ideological and political education course field dimensions, studies the specific composition of the learning field in three dimensions: information, technology and emotion, and discusses the necessity of learning field optimization in secondary school Civics class. Secondly, on the multivariate data chain network, the MIFS model is proposed to extract the ideological and political teaching feature values, followed by the LSTM neural network to train the information related to students’ Civics classroom contents and the average function of adaptive excitation function is used to replace the excitation function in the LSTM neural network to achieve the effect of improving the output accuracy. Then, the characteristics of learners and learning resources are parametrically represented, followed by an experimental analysis of ideological and political education based on multivariate data chain networks using evaluation indexes based on the data set. The results show that there is no difference between the MAE values of CNN and LSTM except for sample one, but the MSE values of LSTM are both lower than CNN, and LSTM is more stable than CNN, indicating that it is reasonable to choose LSTM when ideological and political education based on multivariate data chain network. This study provides a reference and reference for future field optimization in ideology and political science classes.

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Section: Ideological and Political Teaching Resources Recommendation ...mentioning

confidence: 99%

Development of ideological and political education course field dimensions based on multi-data chain network

2023

Applied Mathematics and Nonlinear Sciences

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“…These two path search algorithms are two classical methods in the development history of path planning methods and have a profound influence on many subsequent research methods in this field. Currently, with the development of deep learning, more deep learning model encoders are constructed to guide the path search and the classic method of fusion research [115,116].…”

Section: Update(u V W I ) 10 Endmentioning

confidence: 99%

Techniques and Algorithms for Hepatic Vessel Skeletonization in Medical Images: A Survey

Zhang

Chang

et al. 2022

Entropy

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Hepatic vessel skeletonization serves as an important means of hepatic vascular analysis and vessel segmentation. This paper presents a survey of techniques and algorithms for hepatic vessel skeletonization in medical images. We summarized the latest developments and classical approaches in this field. These methods are classified into five categories according to their methodological characteristics. The overview and brief assessment of each category are provided in the corresponding chapters, respectively. We provide a comprehensive summary among the cited publications, image modalities and datasets from various aspects, which hope to reveal the pros and cons of every method, summarize its achievements and discuss the challenges and future trends.

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Delay-tolerant Load Balancing Routing Model for RSU-Assisted Distributed Vehicular Adhoc Networks

Rajendran,

Kumar,

Kavitha

et al. 2023

2023 International Conference on Innovative Computing, Intelligent Communication and Smart Electrical Systems (ICSES)

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Traffic Guidance Based on LSTM Neural Network and Dual Tracking Dijkstra Algorithm

Cited by 4 publications

References 20 publications

Development of ideological and political education course field dimensions based on multi-data chain network

Development of ideological and political education course field dimensions based on multi-data chain network

Techniques and Algorithms for Hepatic Vessel Skeletonization in Medical Images: A Survey

Delay-tolerant Load Balancing Routing Model for RSU-Assisted Distributed Vehicular Adhoc Networks

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