Preface

  • I. Jeena Jacob GITAM University
  • Badrul Hisham bin Ahmad Universiti Teknikal Malaysia Melaka
  • Z. Faizal Khan Shaqra University

Abstract

We are pleased to present this special issue of Computer Assisted Methods in Engineering and Science on Advanced Optimization Methods for Uncertainties in Intelligent Industrial Systems. It includes the state-of-the-art studies with extended research on the challenges encountered when computational intelligence meets industrial systems.


We hope that readers will enjoy this in-depth exploration of modern optimization and uncertainty handling approaches in different industrial environments.

Keywords

References

1. M.K. Kumar, A. Amalanathan, Automated Lung Nodule Detection in CT Images by Optimized CNN: Impact of Improved Whale Optimization Algorithm, Computer Assisted Method in Engineering and Science, 29(1–2): 7–31, 2022.
2. T. Mohanraj, R. Santhosh, Hybrid Encryption Algorithm for Big Data Security in the Hadoop Distributed File System, Computer Assisted Methods in Engineering and Science, 29(1–2): 33–48, 2022.
3. P.S. Prakash, D. Kavitha, P. Chenna Reddy, Multi-Objective Approach to Improve Network Lifetime and Congestion Control Routing for Wireless Sensor Networks, Computer Assisted Methods in Engineering and Science, 29(1–2): 49–69, 2022.
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7. Sunita Rawat, A Method to IntegrateWord Sense Disambiguation and Translation Memory for English to Hindi Machine Translation System, Computer Assisted Methods in Engineering and Science, 29(1–2): 125–144, 2022.
8. S. Kumar Chandar, Hitesh Punjabi, Cat Swarm Optimization Algorithm Tuned Multilayer Perceptron for Stock Price Prediction, Computer Assisted Methods in Engineering and Science, 29(1–2): 145–160, 2022.
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Published
May 13, 2022
How to Cite
JACOB, I. Jeena; BIN AHMAD, Badrul Hisham; KHAN, Z. Faizal. Preface. Computer Assisted Methods in Engineering and Science, [S.l.], v. 29, n. 1–2, p. 3–6, may 2022. ISSN 2956-5839. Available at: <https://cames.ippt.gov.pl/index.php/cames/article/view/618>. Date accessed: 21 nov. 2024.