Computational Statistical Methodologies and Modeling for Artificial Intelligence  book cover
1st Edition

Computational Statistical Methodologies and Modeling for Artificial Intelligence



  • Available for pre-order. Item will ship after February 23, 2023
ISBN 9781032170800
February 23, 2023 Forthcoming by CRC Press
392 Pages 165 B/W Illustrations

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Book Description

This book covers computational statistics-based approaches for Artificial Intelligence. The aim of this book is to provide comprehensive coverage of the fundamentals through the applications of the different kinds of mathematical modelling and statistical techniques and describing their applications in different Artificial Intelligence systems. The primary users of this book will include researchers, academicians, postgraduate students, and specialists in the areas of data science, mathematical modelling and Artificial Intelligence, and will also serve as a valuable resource for many others in the fields of electrical, computer and optical engineering.

The key features of this book are:

  • Presents development of several real-world problems applications and experimental research in the field of computational statistics, mathematical modelling for Artificial Intelligence
  • Examines the evolution of fundamental research into industrialized research and the transformation of applied investigation into real-time applications
  • Examines the applications involving analytical and statistical solutions, and provides foundational and advanced concepts for beginners and industry professionals
  • Provides a dynamic perspective to the concept of computational statistics for analysis of data and applications in intelligent systems with an objective of ensuring sustainability issues for ease of different stakeholders in various fields
  • Integrates recent methodologies and challenges by employing mathematical modeling and statistical techniques for Artificial Intelligence.

Table of Contents

Chapter 1: A review of computational statistical and Artificial Intelligence methodologiesPriyanka Harjule, Azizur Rahman, Basant Agarwal and Vinita Tiwari

Chapter 2: An improved random forest for classification and regression using dynamic weighted schemeVikas Jain and Ashish Phophalia

Chapter 3: Study of Computational Statistical methodologies for modelling the evolution of COVID-19 in India during the second wave

Harshit, Anubhuti Mittal and Priyanka Harjule

Chapter 4: Distracted Driver Detection using Image Segmentation and Transfer LearningSanjit Kumar Dash, Aditya Prasad Tripathy, Sidhartha Bibekananda Dash, Debabrata Tripathy and Soumyajit Bal

Chapter 5: Review Analysis of Ride-Sharing Application Using Machine Learning Approaches - Bangladesh Perspective

Taminul Islam, Arindom Kundu, Rishalatun Jannat Lima, Most Hasna Hena, Omar Sharif, Azizur Rahman and Md Zobaer Hasan

Chapter 6: Nowcasting of selected imports and exports of Bangladesh: Comparison among traditional time series model and machine learning models

M. M. Hossain, F. Abdulla and A. Rahman

Chapter 7: An Intelligent Interview bot for candidate assessment by using facial expression recognition and speech recognition SystemSonal Yadav, Ayu Yaduvanshi, Shashank Shekhar, Lokesh Bansal, Prateek Meena and Amit kumar

Chapter 8: Analysis of Oversampling and Ensemble Learning Methods for Credit Card Fraud Detection

Ankit Kumar Singh, Rohit Bhaskar Rao Gurijala, Utkarsh Kumar Rai, Anupam Kumar, Basant Agarwal and Ashish Sharma

Chapter 9: Combining News with Time Series for Stock Trend Prediction

Ashish Sharma, Shashwat Singh, Basant Agarwal and Vinita Tiwari

Chapter 10: Influencing project success outcomes by utilising advanced statistical techniques and AI during the Project Initiating Process

J. Hayes, A. Rahman and C. Mendis

Chapter 11: Computational Statistical Methods For Uncertainty Assessment In Geoscience S. McManus, A Rahman, J Coombes and A Horta

Chapter 12: A comparison of geocomputational models for validating geospatial distribution of water quality index

Md Galal Uddin, Stephen Nash, Mir Talas Mahammad Diganta, Azizur Rahman and Agnieszka I. Olbert

 

Chapter 13: Mathematical Modeling for Socio-Economic Development: A Case from Palestine

J. Nour

Chapter 14: A computational study based on Tensor decomposition models applied to screen of autistic children: High order SVD, orthogonal iteration and discriminant analysis algorithms

J. A. Rad, H. R. Pouretemad, Kourosh Parand and Negar Sammaknejad

 

Chapter 15: Stress Level Detection using Smartphone SensorsRekha Pal, Rohith R. Vangal, Yashita Watchpillai, Pooja Jain and Tapan Kumar

 

Chapter 16: Antecedents and inhibitors for use of primary healthcare: A case study of Mohalla clinics in Delhi

Kaushal Kumar and Rahul Kumar

 

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Editor(s)

Biography

Dr. Priyanka Harjule is currently working as an Assistant Professor at the Indian Institute of Information Technology Kota (IIIT-Kota), India. She holds a Ph.D. from the Department of Mathematics, MNIT Jaipur under the Technical Education Quality Improvement Programme (TEQIP-II) fellowship. She has worked on text classification problems with different machine learning classifiers. Her recent research work includes the analysis of survey data on online education using various statistical techniques. Her research interests include Special functions, Fractional calculus, Mathematical and Statistical Modelling, Machine learning, and Image Processing.

Prof. Azizur Rahman is an applied statistician and data scientist with expertise in both developing and applying novel methodologies, models and technologies. He is the Leader of the "Statistics and Data Mining Research Group" at Charles Sturt University. Azizur earned his Ph.D. from UC and worked at several universities, including the University of Adelaide. He has more than 150 publications, including a few books. The Australian Federal and State Governments fund his research, and he serves on a range of editorial boards. His academic excellence has also been well recognised with several awards, including the best research award by the World Business Institute and research excellence and RED Achievement awards at CSU.

Dr. Basant Agarwal is an Assistant Professor at the Indian Institute of Information Technology Kota (IIIT-Kota), India. He holds a Ph.D. and M.Tech. from the Department of Computer Science and Engineering, Malaviya National Institute of Technology Jaipur, India. He has more than 9 years of experience in research and teaching. He has worked as a Postdoc Research Fellow at the Norwegian University of Science and Technology (NTNU), Norway, under the prestigious ERCIM (European Research Consortium for Informatics and Mathematics) fellowship in 2016. He has also worked as a Research Scientist at Temasek Laboratories, National University of Singapore (NUS), Singapore. His research interest is in Artificial Intelligence, Cyber-physical systems, Text mining, Natural Language Processing, Machine learning, Deep learning, Intelligent Systems, Expert Systems, and related areas.

Dr. Vinita Tiwari currently is an Assistant Professor in the Department of Electronics and Communication, the Indian Institute of Information Technology Kota (IIIT-Kota). She received her B.Tech degree in Electronics and Communication Engineering from M.B.M Engineering collage, Jodhpur followed by a Master’s and a Ph.D. degree in Communication Engineering and High-Speed Optical Communication respectively under the faculty development program of BITS-Pilani, Pilani Campus. She has almost fourteen years of experience in teaching and research. Her research interest includes high-speed optical link designs, advanced modulation techniques, Soliton communication, mathematical modeling, blockchain, etc.