Free Delivery Over $100
|
|
|||
|
||||
OverviewThis book develops a new system of modeling and simulations based on intelligence system. As we are directly moving from Third Industrial Revolution (IR3.0) to Fourth Industrial Revolution (IR4.0), there are many emergence techniques and algorithm that appear in many sciences and engineering branches. Nowadays, most industries are using IR4.0 in their product development as well as to refine their products. These include simulation on oil rig drilling, big data analytics on consumer analytics, fastest algorithm for large-scale numerical simulations and many more. These will save millions of dollar in the operating costs. Without any doubt, mathematics, statistics and computing are well blended to form an intelligent system for simulation and modeling. Motivated by this rapid development, in this book, a total of 41 chapters are contributed by the respective experts. The main scope of the book is to develop a new system of modeling and simulations based on machine learning, neural networks, efficient numerical algorithm and statistical methods. This book is highly suitable for postgraduate students, researchers as well as scientists that have interest in intelligent numerical modeling and simulations. Full Product DetailsAuthor: Samsul Ariffin Abdul KarimPublisher: Springer International Publishing AG Imprint: Springer International Publishing AG Edition: 1st ed. 2022 Volume: 444 Weight: 1.238kg ISBN: 9783031040276ISBN 10: 3031040279 Pages: 695 Publication Date: 13 October 2022 Audience: Professional and scholarly , Professional & Vocational Format: Hardback Publisher's Status: Active Availability: Not yet available  This item is yet to be released. You can pre-order this item and we will dispatch it to you upon its release. Table of ContentsIntroduction.- Data-driven Ordinary Differential Equations Model for predicting missing data and forecasting Crude Oil Prices.- Efficient iterative approximation for nonlinear porous medium equation with drainage model.- The Performance of Logistic Regression and Discriminant Analysis in Spam E-mail Classification.- Detecting Structural Breaks and Outliers for Volatility Data via Impulse Indicator Saturation.- Index.ReviewsAuthor InformationSamsul Ariffin Bin Abdul Karim is an Associate Professor with Software Engineering Programme, Faculty of Computing and Informatics, Universiti Malaysia Sabah (UMS), Malaysia. He obtained his PhD in Mathematics from Universiti Sains Malaysia (USM). He is a Professional Technologists registered with Malaysia Board of Technologists (MBOT), No. Perakuan PT21030227. His research interest includes numerical analysis, machine learning, approximation theory, optimization, science, and engineering education as well as wavelets. He has published more than 140 papers in Journals and Conferences including three Edited Conferences Volume and 60 book chapters. He was the recipient of Effective Education Delivery Award and Publication Award (Journal & Conference Paper), UTP Quality Day 2010, 2011 and 2012, respectively. He was Certified WOLFRAM Technology Associate, Mathematica Student Level. He also has published ten books with Springer Publishing including five books with Studies in Systems, Decision and Control (SSDC) series, one book with Taylor and Francis/CRC Press, one book with IntechOpen and one book with UTP Press. Recently he has received Book Publication Award in UTP Quality Day 2020 for book Water Quality Index (WQI) Prediction Using Multiple Linear Fuzzy Regression: Case Study in Perak River, Malaysia, that was published by SpringerBriefs in Water Science and Technology in 2020. Tab Content 6Author Website:Countries AvailableAll regions |
||||
