Open Science Research Excellence

ICEML 2024 : International Conference on Evolutionary Machine Learning

Jerusalem, Israel
April 29 - 30, 2024

Conference Code: 24IL04ICEML

Conference Proceedings

All submitted conference papers will be blind peer reviewed by three competent reviewers. The peer-reviewed conference proceedings are indexed in the Open Science Index, Google Scholar, Semantic Scholar, Zenedo, OpenAIRE, BASE, WorldCAT, Sherpa/RoMEO, and other index databases. Impact Factor Indicators.

Special Journal Issues

ICEML 2024 has teamed up with the Special Journal Issue on Evolutionary Machine Learning. A number of selected high-impact full text papers will also be considered for the special journal issues. All submitted papers will have the opportunity to be considered for this Special Journal Issue. The paper selection will be carried out during the peer review process as well as at the conference presentation stage. Submitted papers must not be under consideration by any other journal or publication. The final decision for paper selection will be made based on peer review reports by the Guest Editors and the Editor-in-Chief jointly. Selected full-text papers will be published online free of charge.

Conference Sponsor and Exhibitor Opportunities

The Conference offers the opportunity to become a conference sponsor or exhibitor. To participate as a sponsor or exhibitor, please download and complete the Conference Sponsorship Request Form.

Important Dates

Abstracts/Full-Text Paper Submission Deadline   February 13, 2023
Notification of Acceptance/Rejection   February 27, 2023
Final Paper (Camera Ready) Submission & Early Bird Registration Deadline   March 29, 2024
Conference Dates   April 29 - 30, 2024

Important Notes

Please ensure your submission meets the conference's strict guidelines for accepting scholarly papers. Downloadable versions of the check list for Full-Text Papers and Abstract Papers.

Please refer to the Paper Submission GUIDE before submitting your paper.

Selected Conference Papers

1) Improving Fake News Detection Using K-means and Support Vector Machine Approaches
Kasra Majbouri Yazdi, Adel Majbouri Yazdi, Saeid Khodayi, Jingyu Hou, Wanlei Zhou, Saeed Saedy
2) Lung Cancer Detection and Multi Level Classification Using Discrete Wavelet Transform Approach
V. Veeraprathap, G. S. Harish, G. Narendra Kumar
3) The Forensic Swing of Things: The Current Legal and Technical Challenges of IoT Forensics
Pantaleon Lutta, Mohamed Sedky, Mohamed Hassan
4) Uplink Throughput Prediction in Cellular Mobile Networks
Engin Eyceyurt, Josko Zec
5) Convergence Analysis of Training Two-Hidden-Layer Partially Over-Parameterized ReLU Networks via Gradient Descent
Zhifeng Kong
6) Deep Learning Based Fall Detection Using Simplified Human Posture
Kripesh Adhikari, Hamid Bouchachia, Hammadi Nait-Charif
7) Consumer Load Profile Determination with Entropy-Based K-Means Algorithm
Ioannis P. Panapakidis, Marios N. Moschakis
8) Comparison of Machine Learning Models for the Prediction of System Marginal Price of Greek Energy Market
Ioannis P. Panapakidis, Marios N. Moschakis
9) An IM-COH Algorithm Neural Network Optimization with Cuckoo Search Algorithm for Time Series Samples
Wullapa Wongsinlatam
10) Performance Evaluation of Distributed Deep Learning Frameworks in Cloud Environment
Shuen-Tai Wang, Fang-An Kuo, Chau-Yi Chou, Yu-Bin Fang
11) Foot Recognition Using Deep Learning for Knee Rehabilitation
Rakkrit Duangsoithong, Jermphiphut Jaruenpunyasak, Alba Garcia
12) Optimizing the Probabilistic Neural Network Training Algorithm for Multi-Class Identification
Abdelhadi Lotfi, Abdelkader Benyettou
13) Classification of Health Risk Factors to Predict the Risk of Falling in Older Adults
L. Lindsay, S. A. Coleman, D. Kerr, B. J. Taylor, A. Moorhead
14) Predictive Semi-Empirical NOx Model for Diesel Engine
Saurabh Sharma, Yong Sun, Bruce Vernham
15) An Automated Stock Investment System Using Machine Learning Techniques: An Application in Australia
Carol Anne Hargreaves

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