Download or read book A Generic Hyper Heuristic model using bio inspiration for solving combinatorial optimization problems written by Dr Sangeetha muthuraman, Dr V prasannavenkatesan and published by Archers & Elevators Publishing House. This book was released on with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Business Intelligence in Economic Forecasting Technologies and Techniques written by Wang, Jue and published by IGI Global. This book was released on 2010-06-30 with total page 405 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the rapid development of economic globalization and information technology, the field of economic forecasting continues its expeditious advancement, providing business and government with applicable technologies. This book discusses various business intelligence techniques including neural networks, support vector machine, genetic programming, clustering analysis, TEI@I, fuzzy systems, text mining, and many more. It serves as a valuable reference for professionals and researchers interested in BI technologies and their practical applications in economic forecasting, as well as policy makers in business organizations and governments.

Download or read book Corporate Bankruptcy Prediction written by Błażej Prusak and published by MDPI. This book was released on 2020-06-16 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bankruptcy prediction is one of the most important research areas in corporate finance. Bankruptcies are an indispensable element of the functioning of the market economy, and at the same time generate significant losses for stakeholders. Hence, this book was established to collect the results of research on the latest trends in predicting the bankruptcy of enterprises. It suggests models developed for different countries using both traditional and more advanced methods. Problems connected with predicting bankruptcy during periods of prosperity and recession, the selection of appropriate explanatory variables, as well as the dynamization of models are presented. The reliability of financial data and the validity of the audit are also referenced. Thus, I hope that this book will inspire you to undertake new research in the field of forecasting the risk of bankruptcy.

Download or read book Data Mining for Business Intelligence written by Galit Shmueli and published by John Wiley & Sons. This book was released on 2011-09-28 with total page 341 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the First Edition " full of vivid and thought-provoking anecdotes needs to be read by anyone with a serious interest in research and marketing." —Research magazine "Shmueli et al. have done a wonderful job in presenting the field of data mining a welcome addition to the literature." —computingreviews.com Incorporating a new focus on data visualization and time series forecasting, Data Mining for Business Intelligence, Second Edition continues to supply insightful, detailed guidance on fundamental data mining techniques. This new edition guides readers through the use of the Microsoft Office Excel add-in XLMiner for developing predictive models and techniques for describing and finding patterns in data. From clustering customers into market segments and finding the characteristics of frequent flyers to learning what items are purchased with other items, the authors use interesting, real-world examples to build a theoretical and practical understanding of key data mining methods, including classification, prediction, and affinity analysis as well as data reduction, exploration, and visualization. The Second Edition now features: Three new chapters on time series forecasting, introducing popular business forecasting methods including moving average, exponential smoothing methods; regression-based models; and topics such as explanatory vs. predictive modeling, two-level models, and ensembles A revised chapter on data visualization that now features interactive visualization principles and added assignments that demonstrate interactive visualization in practice Separate chapters that each treat k-nearest neighbors and Naïve Bayes methods Summaries at the start of each chapter that supply an outline of key topics The book includes access to XLMiner, allowing readers to work hands-on with the provided data. Throughout the book, applications of the discussed topics focus on the business problem as motivation and avoid unnecessary statistical theory. Each chapter concludes with exercises that allow readers to assess their comprehension of the presented material. The final chapter includes a set of cases that require use of the different data mining techniques, and a related Web site features data sets, exercise solutions, PowerPoint slides, and case solutions. Data Mining for Business Intelligence, Second Edition is an excellent book for courses on data mining, forecasting, and decision support systems at the upper-undergraduate and graduate levels. It is also a one-of-a-kind resource for analysts, researchers, and practitioners working with quantitative methods in the fields of business, finance, marketing, computer science, and information technology.

Download or read book Business Analytics and Business Intelligence Machine Learning Model to Predict Bank Loan Defaults written by dr. V.V.L.N. Sastry and published by Idea Publishing. This book was released on 2020-05-29 with total page 72 pages. Available in PDF, EPUB and Kindle. Book excerpt: Predictive Analytics offers a unique opportunity to identify future trends and allows organizations to act upon them. In this book we are dealing with ‘loan default’ which is always a threat to banks and financial institutions and should be predicted in advance based on various features of the borrowers or applicants. In this book we aim at applying machine learning models to classify the borrowers with and without loan default from a group of predicting variables and evaluate their performance. As a part of building a model to predict loan default, we have submitted in detail the introduction of the problem, exploratory data analysis (EDA), data cleaning and pre-processing, model building, interpretation, model tuning, model validation, and final interpretation & recommendations. Under the current project of loan default forming part of predictive analytics of business analytics and intelligence, we have studied research-based review parameters in detail which have also been annexed for ready reference as Annexure I. Data dictionary has been annexed as Annexure-2. R. Code for the same is provided at the URL which can be downloaded from www.drvvlnsastry.com/businessanalytics/data The study finds out that logistic regression is the best model to classify those applicants with loan default.

Download or read book Analyzing Risk through Probabilistic Modeling in Operations Research written by Jakóbczak, Dariusz Jacek and published by IGI Global. This book was released on 2015-11-03 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt: Probabilistic modeling represents a subject spanning many branches of mathematics, economics, and computer science to connect pure mathematics with applied sciences. Operational research also relies on this connection to enable the improvement of business functions and decision making. Analyzing Risk through Probabilistic Modeling in Operations Research is an authoritative reference publication discussing the various challenges in management and decision science. Featuring exhaustive coverage on a range of topics within operational research including, but not limited to, decision analysis, data mining, process modeling, probabilistic interpolation and extrapolation, and optimization methods, this book is an essential reference source for decision makers, academicians, researchers, advanced-level students, technology developers, and government officials interested in the implementation of probabilistic modeling in various business applications.

Download or read book Handbook of Research on Digital Transformation Industry Use Cases and the Impact of Disruptive Technologies written by Wynn, Martin George and published by IGI Global. This book was released on 2021-10-15 with total page 487 pages. Available in PDF, EPUB and Kindle. Book excerpt: Companies from various sectors of the economy are confronted with the new phenomenon of digital transformation and are faced with the challenge of formulating and implementing a company-wide strategy to incorporate what are often viewed as “disruptive” technologies. These technologies are sometimes associated with significant and extremely rapid change, in some cases with even the replacement of established business models. Many of these technologies have been deployed in unison by leading-edge companies acting as the catalyst for significant process change and people skills enhancement. The Handbook of Research on Digital Transformation, Industry Use Cases, and the Impact of Disruptive Technologies examines the phenomenon of digital transformation and the impact of disruptive technologies through the lens of industry case studies where different combinations of these new technologies have been deployed and incorporated into enterprise IT and business strategies. Covering topics including chatbot implementation, multinational companies, cloud computing, internet of things, artificial intelligence, big data and analytics, immersive technologies, and social media, this book is essential for senior management, IT managers, technologists, computer scientists, cybersecurity analysts, academicians, researchers, IT consultancies, professors, and students.

Download or read book Business Analytics with R and Python written by David L. Olson and published by Springer Nature. This book was released on with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Business Intelligence Techniques written by Murugan Anandarajan and published by Springer Science & Business Media. This book was released on 2012-11-02 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern businesses generate huge volumes of accounting data on a daily basis. The recent advancements in information technology have given organizations the ability to capture and store data in an efficient and effective manner. However, there is a widening gap between this data storage and usage of the data. Business intelligence techniques can help an organization obtain and process relevant accounting data quickly and cost efficiently. Such techniques include: query and reporting tools, online analytical processing (OLAP), statistical analysis, text mining, data mining, and visualization. Business Intelligence Techniques is a compilation of chapters written by experts in the various areas. While these chapters stand on their own, taken together they provide a comprehensive overview of how to exploit accounting data in the business environment.

Download or read book Intelligent Systems Concepts Methodologies Tools and Applications written by Management Association, Information Resources and published by IGI Global. This book was released on 2018-06-04 with total page 2390 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ongoing advancements in modern technology have led to significant developments in intelligent systems. With the numerous applications available, it becomes imperative to conduct research and make further progress in this field. Intelligent Systems: Concepts, Methodologies, Tools, and Applications contains a compendium of the latest academic material on the latest breakthroughs and recent progress in intelligent systems. Including innovative studies on information retrieval, artificial intelligence, and software engineering, this multi-volume book is an ideal source for researchers, professionals, academics, upper-level students, and practitioners interested in emerging perspectives in the field of intelligent systems.

Download or read book Encyclopedia of Business Analytics and Optimization written by Wang, John and published by IGI Global. This book was released on 2014-02-28 with total page 2862 pages. Available in PDF, EPUB and Kindle. Book excerpt: As the age of Big Data emerges, it becomes necessary to take the five dimensions of Big Data- volume, variety, velocity, volatility, and veracity- and focus these dimensions towards one critical emphasis - value. The Encyclopedia of Business Analytics and Optimization confronts the challenges of information retrieval in the age of Big Data by exploring recent advances in the areas of knowledge management, data visualization, interdisciplinary communication, and others. Through its critical approach and practical application, this book will be a must-have reference for any professional, leader, analyst, or manager interested in making the most of the knowledge resources at their disposal.

Download or read book Evolutionary Computation in Data Mining written by Ashish Ghosh and published by Springer. This book was released on 2006-06-22 with total page 279 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data mining (DM) consists of extracting interesting knowledge from re- world, large & complex data sets; and is the core step of a broader process, called the knowledge discovery from databases (KDD) process. In addition to the DM step, which actually extracts knowledge from data, the KDD process includes several preprocessing (or data preparation) and post-processing (or knowledge refinement) steps. The goal of data preprocessing methods is to transform the data to facilitate the application of a (or several) given DM algorithm(s), whereas the goal of knowledge refinement methods is to validate and refine discovered knowledge. Ideally, discovered knowledge should be not only accurate, but also comprehensible and interesting to the user. The total process is highly computation intensive. The idea of automatically discovering knowledge from databases is a very attractive and challenging task, both for academia and for industry. Hence, there has been a growing interest in data mining in several AI-related areas, including evolutionary algorithms (EAs). The main motivation for applying EAs to KDD tasks is that they are robust and adaptive search methods, which perform a global search in the space of candidate solutions (for instance, rules or another form of knowledge representation).

Download or read book Decision and Prediction Analysis Powered With Operations Research written by Bubevski, Vojo and published by IGI Global. This book was released on 2024-07-16 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: Organizations today face complex decisions and uncertainties that can have a profound impact on their financial stability and strategic direction. Traditional decision-making methods often fall short when it comes to addressing multifaceted issues like financing, product manufacturing, and facility location. These challenges demand a robust framework that quantifies factors, assesses risks, and provides optimal solutions. Without advanced tools and techniques, businesses are at risk of making uninformed decisions that could lead to significant financial losses and missed opportunities. The urgency to equip yourself with these tools is clear. Decision and Prediction Analysis Powered With Operations Research offers a comprehensive solution to these challenges. This book integrates operations research techniques to reframe and solve complex business problems. It provides a detailed exploration of decision analysis tools, such as influence diagrams and decision trees, which help visualize and assess various decision scenarios. By applying these tools, organizations can better understand uncertainties, evaluate risks, and make decisions that maximize expected utility and achieve strategic objectives.

Download or read book Advancement in Business Analytics Tools for Higher Financial Performance written by Gharoie Ahangar, Reza and published by IGI Global. This book was released on 2023-08-08 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: The relentless growth of data in financial markets has boosted the demand for more advanced analytical tools to facilitate and improve financial planning. The ability to constructively use this data is limited for managers and investors without the proper theoretical support. Within this context, there is an unmet demand for combining analytical finance methods with business analytics topics to inform better investment decisions. Advancement in Business Analytics Tools for Higher Financial Performance explores the financial applications of business analytics tools that can help financial managers and investors to better understand financial theory and improve institutional investment practices. This book explores the value extraction process using more accurate financial data via business analytical tools to help investors and portfolio managers develop more modern financial planning processes. Covering topics such as financial markets, investment analysis, and statistical tools, this book is ideal for accountants, data analysts, researchers, students, business professionals, academicians, and more.

Download or read book Integration of Data Mining in Business Intelligence Systems written by Azevedo, Ana and published by IGI Global. This book was released on 2014-09-30 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: Uncovering and analyzing data associated with the current business environment is essential in maintaining a competitive edge. As such, making informed decisions based on this data is crucial to managers across industries. Integration of Data Mining in Business Intelligence Systems investigates the incorporation of data mining into business technologies used in the decision making process. Emphasizing cutting-edge research and relevant concepts in data discovery and analysis, this book is a comprehensive reference source for policymakers, academicians, researchers, students, technology developers, and professionals interested in the application of data mining techniques and practices in business information systems.

Download or read book Data Mining for Business Analytics written by Galit Shmueli and published by John Wiley & Sons. This book was released on 2016-04-22 with total page 549 pages. Available in PDF, EPUB and Kindle. Book excerpt: An applied approach to data mining and predictive analytics with clear exposition, hands-on exercises, and real-life case studies. Readers will work with all of the standard data mining methods using the Microsoft® Office Excel® add-in XLMiner® to develop predictive models and learn how to obtain business value from Big Data. Featuring updated topical coverage on text mining, social network analysis, collaborative filtering, ensemble methods, uplift modeling and more, the Third Edition also includes: Real-world examples to build a theoretical and practical understanding of key data mining methods End-of-chapter exercises that help readers better understand the presented material Data-rich case studies to illustrate various applications of data mining techniques Completely new chapters on social network analysis and text mining A companion site with additional data sets, instructors material that include solutions to exercises and case studies, and Microsoft PowerPoint® slides https://www.dataminingbook.com Free 140-day license to use XLMiner for Education software Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner®, Third Edition is an ideal textbook for upper-undergraduate and graduate-level courses as well as professional programs on data mining, predictive modeling, and Big Data analytics. The new edition is also a unique reference for analysts, researchers, and practitioners working with predictive analytics in the fields of business, finance, marketing, computer science, and information technology. Praise for the Second Edition "...full of vivid and thought-provoking anecdotes... needs to be read by anyone with a serious interest in research and marketing."– Research Magazine "Shmueli et al. have done a wonderful job in presenting the field of data mining - a welcome addition to the literature." – ComputingReviews.com "Excellent choice for business analysts...The book is a perfect fit for its intended audience." – Keith McCormick, Consultant and Author of SPSS Statistics For Dummies, Third Edition and SPSS Statistics for Data Analysis and Visualization Galit Shmueli, PhD, is Distinguished Professor at National Tsing Hua University’s Institute of Service Science. She has designed and instructed data mining courses since 2004 at University of Maryland, Statistics.com, The Indian School of Business, and National Tsing Hua University, Taiwan. Professor Shmueli is known for her research and teaching in business analytics, with a focus on statistical and data mining methods in information systems and healthcare. She has authored over 70 journal articles, books, textbooks and book chapters. Peter C. Bruce is President and Founder of the Institute for Statistics Education at www.statistics.com. He has written multiple journal articles and is the developer of Resampling Stats software. He is the author of Introductory Statistics and Analytics: A Resampling Perspective, also published by Wiley. Nitin R. Patel, PhD, is Chairman and cofounder of Cytel, Inc., based in Cambridge, Massachusetts. A Fellow of the American Statistical Association, Dr. Patel has also served as a Visiting Professor at the Massachusetts Institute of Technology and at Harvard University. He is a Fellow of the Computer Society of India and was a professor at the Indian Institute of Management, Ahmedabad for 15 years.

Download or read book Advances in Artificial Business Analytics and Quantum Machine Learning written by K. C. Santosh and published by Springer Nature. This book was released on with total page 810 pages. Available in PDF, EPUB and Kindle. Book excerpt: