What is it about?
We have optimized the Bi-LSTM method with Komodo Mlipir Algorithm and Sliding Window to significantly improve the accuracy of Traffic Flow prediction at the rush hours in the big crowded city such as Semarang
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Why is it important?
Novel combination of Bi-LSTM and Komodo Mlipir Algorithm enhanced with Sliding Window Technique for real time connected prediction.
Perspectives
We hope this article will contribute in prediction the traffic flow for intelligent transportation system as a part of smart city development. The novelty is injection the sliding window technique to the Bi-LSTM for fast and accurate prediction which based on the short time data.
Wahyul Amien Syafei
Universitas Diponegoro
Read the Original
This page is a summary of: A Novel SW-KMA-Bi-LSTM Approach for Improving Traffic Flow Prediction, International Journal of Intelligent Engineering and Systems, August 2025, The Intelligent Networks and Systems Society,
DOI: 10.22266/ijies2025.0831.07.
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