Trends in Data Engineering Methods for Intelligent Systems

This book briefly covers internationally contributed chapters with artificial intelligence and applied mathematics-oriented background-details. Nowadays, the world is under attack of intelligent systems covering all fields to make them practical and meaningful for humans. In this sense, this edited book provides the most recent research on use of engineering capabilities for developing intelligent systems. The chapters are a collection from the works presented at the 2nd International Conference on Artificial Intelligence and Applied Mathematics in Engineering held within 09-10-11 October 2020 at the Antalya, Manavgat (Turkey). The target audience of the book covers scientists, experts, M.Sc. and Ph.D. students, post-docs, and anyone interested in intelligent systems and their usage in different problem domains. The book is suitable to be used as a reference work in the courses associated with artificial intelligence and applied mathematics.

Discusses recent research on computational intelligence and applied mathematics in engineering problems Presents the proceedings of the 2nd International Conference on Artificial Intelligence and Applied Mathematics in Engineering (ICAIAME 2020), held in Antalya, Turkey, on April 1820, 2020 Focuses on technological innovations and trendsetting initiatives applicable for engineering-oriented stakeholders

Inhalt
Prediction of Liver Cancer by Artificial Neural Network.- Remarks on the limit-circle classification of Conformable Fractional Sturm-Liouville Operator.- Improving Search Relevance with Word Embedding Based Clusters.- Improving Search Relevance with Word Embedding Based Clusters.- Diagnosis of Parkinson's Disease with Acoustic Sounds by Rule Based Model.- Development of Face Recognition System by Using Deep Learning and FaceNet Algorithm in the Operations Processes.- Mobile Assisted Travel Planning Software: The Case of Burdur.- Optimal Coordination of Directional Overcurrent Relays Using Artificial Ecosystem-based Optimization.- The Effect of Auscultation Areas on Nonlinear Classifiers in Computerized Analysis of Chronic Obstructive Pulmonary Disease.