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  1. 481

    A survey of research on demand responsive transit and its route optimization by Shuai FENG, Xiaoming LIU

    Published 2021-06-01
    “…With the widespread application of new infrastructure and other technologies, demand responsive transit (DRT) is becoming the trend of urban traffic development in the future.In order to further clarify the research status of DRT at home and abroad, firstly, the classification of DRT and the operational production factors were analyzed.Secondly, the production process and operation practice of DRT mode were described.Thirdly, the DRT optimization problem was summarized and analyzed from the three dimensions including optimization objectives, constraint selection and solving algorithm, especially the meta heuristic algorithm.Finally, the prospect of DRT scenarios, model construction, algorithm solution, and the collaborative optimization were proposed.Several hotspots and possible directions of future research were suggested.…”
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    Research on Vehicle Path Planning Method with Time Windows in Uncertain Environments by Ying Cong, Kai Zhu

    Published 2024-12-01
    “…Numerical experiments demonstrate the superior performance of the hybrid algorithm, achieving lower total costs compared to standalone ant colony, zebra optimization, genetic algorithm, and particle swarm optimization algorithms. …”
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  11. 491

    Research on the application of government big data platform based on federated learning by Jianping WU, Chaochao CHEN, Jiahe JIN, Chunming WU

    Published 2024-05-01
    “…At present, the construction of digital government has entered a deepwater area.The government big data platform, as a data base, supports various government information applications.The security and compliance of its private data has been widely concerned by the industry.Federated learning is an important method to effectively solve data silos, and the application of government big data platforms based on federated learning has high research value.Firstly, the current status of government big data platforms and its federated learning application were introduced.Then this paper analyzed three major management challenges involved in the collection, classification and grading and sharing of privacy data on government big data platforms.Further, the problem-solving methods of federated learning based recommendation algorithms and privacy intersection techniques were explored.Finally, summaries and prospects were made for the future application of privacy data on government big data platforms.…”
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