JICS

1. A Study on the Energy Usage Prediction and Energy Demand Shift Model to Increase Energy Efficiency

JaeHwan Kim, SeMo Yang, KangYoon Lee, Vol. 24, No. 2, pp. 57-66, Apr. 2023

10.7472/jksii.2023.24.2.57
Keywords: Energy, Energy usage fee, LSTM, clustering, Time Series K-means, shift of demand

2. A Study on Emotion Recognition of Chunk-Based Time Series Speech

Hyun-Sam Shin, Jun-Ki Hong, Sung-Chan Hong, Vol. 24, No. 2, pp. 11-18, Apr. 2023

10.7472/jksii.2023.24.2.11
Keywords:

3. Personal Driving Style based ADAS Customization using Machine Learning for Public Driving Safety

Giyoung Hwang, Dongjun Jung, Yunyeong Goh, Jong-Moon Chung, Vol. 24, No. 1, pp. 39-47, Feb. 2023

10.7472/jksii.2023.24.1.39
Keywords: autonomous vehicles, ADAS, Machine Learning, SVM, LSTM, GRU, Public Driving Safety

4. Bidirectional LSTM based light-weighted malware detection modelusing Windows PE format binary data

Kwang-Yun PARK, Soo-Jin LEE, Vol. 23, No. 1, pp. 87-93, Feb. 2022

10.7472/jksii.2022.23.1.87
Keywords: Bidirectional LSTM, Windows PE malware, Detection, EMBER2018

5. Deep Learning based Abnormal Vibration Prediction of Drone

Jun-Ki Hong, Yang-Kyoo Lee, Vol. 22, No. 3, pp. 67-73, Jun. 2021

10.7472/jksii.2021.22.3.67
Keywords: Deep Learning, RNN, LSTM, Drone, Motor, Vibration

6. Prediction of infectious diseases using multiple web data and LSTM

Yeongha Kim, Inhwan Kim, Beakcheol Jang, Vol. 21, No. 5, pp. 139-148, Oct. 2020

10.7472/jksii.2020.21.5.139
Keywords: Machine Learning, Predict infectious diseases, Web data, LSTM

7. An LSTM Neural Network Model for Forecasting Daily Peak Electric Load of EV Charging Stations

Haesung Lee, Byungsung Lee, Hyun Ahn, Vol. 21, No. 5, pp. 119-127, Oct. 2020

10.7472/jksii.2020.21.5.119
Keywords: EV, Peak electric load, Load forecasting, Deep Learning, LSTM

8. LSTM-based Business Process Remaining Time Prediction Model Featured in Activity-centric Normalization Techniques

Seong-Hun Ham, Hyun Ahn, Kwanghoon Pio Kim, Vol. 21, No. 3, pp. 83-92, Jun. 2020

10.7472/jksii.2020.21.3.83
Keywords: predictive process monitoring, remaining time prediction, LSTM model, Deep Learning, Process Mining

9. A Comparative Study on the Optimal Model for abnormal Detection event of Heart Rate Time Series Data Based on the Correlation between PPG and ECG

Jin-soo Kim, Kang-yoon Lee, Vol. 20, No. 6, pp. 137-142, Dec. 2019

10.7472/jksii.2019.20.6.137
Keywords: Photoplethysmography(PPG), Electrocardiogram(ECG), Abnormal event detection, SVM, LSTM

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