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Journal : Journal of Applied Data Sciences

Optimizing LSTM with Grid Search and Regularization Techniques to Enhance Accuracy in Human Activity Recognition Budiarso, Zuly; Listiyono, Hersatoto; Karim, Abdul
Journal of Applied Data Sciences Vol 5, No 4: DECEMBER 2024
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jads.v5i4.433

Abstract

This study aims to enhance the accuracy of Long Short-Term Memory (LSTM) models for human activity recognition using the UCI Human Activity Recognition (HAR) dataset. The dataset comprises time-series data from accelerometer and gyroscope sensors on smartphones worn by 30 volunteers as they performed everyday activities such as walking, climbing stairs, descending stairs, sitting, standing, and lying down. Optimization was carried out using Grid Search for hyperparameter tuning and L2 regularization to prevent overfitting. The results show that the optimized LSTM model improved accuracy from 92.33% to 94.50%, precision from 93.12% to 94.61%, recall from 92.33% to 94.50%, and F1-score from 92.32% to 94.51% compared to the standard LSTM model. Despite these improvements, the study encountered several challenges, particularly in tuning hyperparameters, which required significant computational resources and time due to the complexity of the search space. Additionally, balancing regularization to prevent both underfitting and overfitting proved to be a delicate process. Further limitations include the model's performance variability with different sensor placements and potential overfitting to specific activity patterns. However, the implementation of hyperparameter optimization and regularization proved effective in improving the model's ability to recognize human activity patterns from complex sensor data. Therefore, this approach holds significant potential for broader applications in sensor-based human activity recognition systems, though further research is needed to address these limitations and generalize the findings.
Co-Authors Abdul Karim Adelia Aura Diva Zainanda Agus Budi Santosa Agus Perdana Windarto Agus Prasetyo Agus Prasetyo Utomo Agus Prasetyo Utomo Alana Sharfina Wedaningsih Ali Maskur Alif Budi Santoso Anak Agung Istri Sri Wiadnyani Anisa Istiqomah Antono Adhi Askar Yunianto Budiarso, Zuly Budiarso Daniswara, Alfreda Khansa Diah Laila Sani Dwi Agus Diartono Eddy Nurraharjo Eddy Nurraharjo Edi Supriyanto, Edi Edy Supriyanto Edy Winarno Eko Nur Wahyudi Eri Zuliarso Ferdiansyah, Alif Hari Murti Heribertus Yulianton Herny Februariyanti Herny Februariyanti Ibrahim, A. F. Indriani, Vanyariska Isworo Nugroho Isworo Nugroho Jati Sasongko Wibowo Jeffri Alfa Razaq Liana Rahmaziana Muhammad A.R. Hidayat Muji Sukur Novita Mariana P Purwatiningtyas Priambodo, Ilyas Purwadi, Dimas Indra Purwatiningtyas Purwatiningtyas Purwatiningtyas Purwatiningtyas Purwatiningtyas, P R. Soelistijadi Raharjo, Eddy Nur Ramadhan, Guntur Rani, R.P.S. Retnowati Retnowati Retnowati Retnowati Retnowati Rizal Adi Saputro Rosyida, Elviana S Sunardi S Sunardi Saefurrahman, Saefurrahman Sariyun Naja Anwar Sekar Ayu Ningtyas Sri Mulyani Sri Mulyani Sri Mulyani Sri Yulianto Fajar Pradapa Sugiyamto Sugiyamto Sugiyamto Sugiyamto Sugiyamto Sugiyamto, Sugiyamto Sunardi Sunardi Sunardi sunardi sunardi Sunardi Sunardi Sunardi Sunardi Susi Susilowati, Susi Syamsul Arifin Teguh Khristianto Teguh Kristianto Vici Tiara Anjarsari Widiyanto Tri Handoko Yunus Anis Yunus Anis, Yunus Yunus Anis, Yunus Anis Ziana, Liana Rahma Zuly Budiarso Zuly Budiharso