MATHEMATICAL FOUNDATIONS AND INTELLIGENT APPLICATIONS: FROM MACHINE LEARNING TO QUEUEING SYSTEMS : MATHEMATICAL FOUNDATIONS AND INTELLIGENT APPLICATIONS: FROM MACHINE LEARNING TO QUEUEING SYSTEMS: MATHEMATICAL FOUNDATIONS AND INTELLIGENT APPLICATIONS: FROM MACHINE LEARNING TO QUEUEING SYSTEMS

By Seenivasan, M.

Book Id: WPLBN0100750936
Format Type: PDF (eBook)
File Size: 17.02 MB.
Reproduction Date: 10/20/2025

Title:	MATHEMATICAL FOUNDATIONS AND INTELLIGENT APPLICATIONS: FROM MACHINE LEARNING TO QUEUEING SYSTEMS : MATHEMATICAL FOUNDATIONS AND INTELLIGENT APPLICATIONS: FROM MACHINE LEARNING TO QUEUEING SYSTEMS: MATHEMATICAL FOUNDATIONS AND INTELLIGENT APPLICATIONS: FROM MACHINE LEARNING TO QUEUEING SYSTEMS
Author:	Seenivasan, M.
Volume:
Language:	English
Subject:	Non Fiction, Science, Mathematical Foundations, Applied Mathematics, Machine Learning, Artificial Intelligence, Intelligent Systems, Queueing Theory, Queueing Systems, Stochastic Processes, Probability Theory, Optimization Methods, Computational Modeling, Data-Driven Applications, Algorithmic Analysis, Operations Research, System Performance Analysis, Statistical Learning, Predictive Modeling, Mathematical Modeling, In
Collections:	Authors Community, Technology
Historic Publication Date:	2025
Publisher:	BZT TURAN PUBLISHING HOUSE

Member Page:	ANIL CAN
Citation APA MLA Chicago Savaşaneril, N. B. (2025). MATHEMATICAL FOUNDATIONS AND INTELLIGENT APPLICATIONS: FROM MACHINE LEARNING TO QUEUEING SYSTEMS : MATHEMATICAL FOUNDATIONS AND INTELLIGENT APPLICATIONS: FROM MACHINE LEARNING TO QUEUEING SYSTEMS. Retrieved from https://self.gutenberg.org/

Description
Another study focuses on the role of mathematics in artificial intelligence, underscoring the indispensable importance of calculus, linear algebra, probability, and optimization. Through applications in neural networks, image processing, and dynamic systems, the mathematical backbone of AI is clearly articulated, revealing how abstract structures translate into real-world problem-solving. The volume also explores job recommendation systems using Wide & Deep Learning architectures enhanced with graph features. This contribution not only demonstrates the power of hybrid AI models in large-scale recommendation systems but also provides a systematic feature impact analysis, offering a roadmap for future research on data-driven human resource management.

Summary
The accelerating developments in artificial intelligence and computational sciences have transformed not only how we solve problems but also how we conceptualize them. Mathematics, as the universal language of science, lies at the heart of these transformations, providing both the theoretical foundation and the methodological tools for innovation across diverse fields. This book brings together a collection of interdisciplinary studies that exemplify the intersection of mathematics, artificial intelligence, and applied probability, offering insights into both theoretical advancements and practical implementations. The first chapter addresses the use of classical and fuzzy-based clustering algorithms in image segmentation for apple leaf disease detection, a timely example that combines machine learning with sustainable agriculture. By comparing different clustering methods and evaluating their performance, the study highlights how intelligent algorithms can enhance precision agriculture and contribute to food security.

Table of Contents
CHAPTER 1 Comparison of Classical and Fuzzy-based Clustering Algorithms in Image Segmentation: Apple Leaf Diseases Detection Example ............1 Beliz Özcan Mükerrem Bahar Başkır CHAPTER 2 On Mathematics in Artificial Intelligence......................................................21 Bekir Danış CHAPTER 3 Job Recommendati̇on Using Wide & Deep Learning With Graph Features: A Comprehensive Feature Impact Analysis.............................33 Kübra Karacan Uyar Yücel Batu Salman CHAPTER 4 Single Server Queueing System Featuring Working Vacations, Encouraged Arrivals, Reneging and Balking Customers ........................61 Seenivasan. M Anita. V Pandisaranya. S CHAPTER 5 Analysing M/M/1 Queuing Systems with Variant Server Vacations and Reneging Behaviour.....................................................................................69 M. Seenivasan S. Pandisaranya V. Anita