Contents


Preface

Computers and machines were developed to reduce time consumption and manual human efforts to complete projects efficiently. With fast-growing technologies in the field, we have finally reached a stage where almost everyone in the world has access to these high technologies. However, this is just a starting phase because future development is taking a more advanced route in the shape of artificial intelligence (AI). Although AI is under the computer science umbrella, nowadays there

The overall aim of using intelligence learning methods is to train machines to think intelligently and make decisions in different situations the same as humans. Previously, machines were doing what they were programmed to do, but now with

High-tech giants like Apple, Google, Microsoft, Deloitte, and IBM are highly involved in research to develop the knowledge that has started to produce innovative transformation. Although it is going to form our future, we need to know how it is affecting our work and lifestyle. So, this book has been published to give you a

glimpse of the applications and advanced analytics of AI in different fields.

advanced readers to acquire more detailed technical information.

carry out the clustering of large groups of web services.

This book contains six applications of advanced analytics and AI in different industries. All the information is supported by practical examples and scientific detail. The chapters contain enough information for both beginners to become familiar with high technologies and science applications to solve business problems and

In Chapter 1, an introductory review briefly gives a background to advanced analytics and AI applications to help industries make better decisions to optimize

Chapter 2 is about using a bio-inspired hybrid algorithm for web services clustering. This chapter is written by researchers from the Autonomous Metropolitan University. In recent years, methods inspired by nature using biological analogies have been adapted for clustering problems, among which genetic algorithms, evolutionary strategies, and algorithms that imitate the behavior of some animal species have been implemented. In this chapter, researchers investigate how biologically inspired clustering methods can be applied to clustering web services and present a hybrid approach for web services clustering using the Artificial Bee Colony algorithm, K-Means, and Consensus. This hybrid algorithm was implemented and a series of experiments were conducted using three collections of web services. Results of the tests show that the solution approach is adequate and efficient to

is no field unaffected by this high technology.

**Structure of the book**

processes and reduce cost.

AI, devices can think and behave like a human being.
