Machine Learning Applications In Software Engineering

Using a problem-based quantitative approach, Striebig, Ogundipe, and Papadakis present a textbook on sustainable design and development that can be used in any field of engineering. The prerequisites

ENGINEERING APPLICATIONS IN SUSTAINABLE DESIGN AND DEVELOPMENT is an invaluable resource for today's engineering student. Focusing on pressing contemporary issues, the text puts product design in the

Agent-Based Software Systems explains how multi-agent systems improve collaborative networks to offer dynamic service changes, customization, improved quality and reliability, and flexible infrastruct

Are you curious about AI? All you need is a good understanding of the Scala programming language, a basic knowledge of statistics, a keen interest in Big Data processing, and this book!

Lasers can alter the surface composition and properties of materials in a highly controllable way, which makes them efficient and cost-effective tools for surface engineering. This book provides an ov

For both students and engineers in R&D, this book explains machine vision in a concise, hands-on way, using the Vision Development Module of the LabView software by National Instruments.Follow

Rapid advancement in electron-based computers or probable light-based computers in future; changes in electronics engineering from vacuum valves to very large scale microchips (VLSC); cement concrete

Industrial engineering originated in the United States, and although the popularity of this discipline has grown worldwide, there is still little information available outside of the US regarding its

Apply a fully test-driven approach to machine-learning algorithms, and save yourself the pain of missing mistakes in your analyses. Most data scientists have run an analysis and simply accepted any an

Building a simple but powerful recommendation system is much easier than you think. Approachable for all levels of expertise, this report explains innovations that make machine learning practical for

This book provides guidelines for practicing design science in the fields of information systems and software engineering research. A design process usually iterates over two activities: first designi

This work presents the most recent research in the mechanism and machine science field and its applications. The topics covered include: theoretical kinematics, computational kinematics, mechanism des

Master the principles of thermodynamics with this comprehensive undergraduate textbook, carefully developed to provide students of chemical engineering and chemistry with a deep and intuitive understanding of the practical applications of these fundamental ideas and principles. Logical and lucid explanations introduce core thermodynamic concepts in the context of their measurement and experimental origin, giving students a thorough understanding of how theoretical concepts apply to practical situations. A broad range of real-world applications relate key topics to contemporary issues, such as energy efficiency, environmental engineering and climate change, and further reinforce students' understanding of the core material. This is a carefully organized, highly pedagogical treatment, including over 500 open-ended study questions for discussion, over 150 varied homework problems, clear and objective standards for measuring student progress, and a password-protected solution manual for in

"This book examines the strengths and future potential of micro-scale technologies in a variety of industries, highlighting the benefits, shortcomings, and emerging perspectives in the application of

Metaheuristics exhibit desirable properties like simplicity, easy parallelizability and ready applicability to different types of optimization problems such as real parameter optimization, combinatori

Multi-Agent Machine Learning: A Reinforcement Learning Approach is a framework to understanding different methods and approaches in multi-agent machine learning. It also provides cohesive coverage of

Ocean Engineering Mechanics provides an introduction to water waves and wave-structure interactions for fixed and floating bodies. Linear and nonlinear regular waves are thoroughly discussed, and the methods of determining the averaged properties of random waves are presented. With this foundation in wave mechanics, applications to engineering situations in the coastal zone are then presented. This introduction to the coastal engineering aspects of wave mechanics includes an introduction to shore protection. Covered within are also the basics of wave-structure interactions for situations involving ridged structures, compliant structures, and floating bodies in regular and random seas. The final chapters deal with the various analytical methods available for the engineering analyses of wave-induced forces and motions of floating and compliant structures in regular and random seas. An introduction to the soil-structure interactions is also included. The book can be used for both introduc

"It is vitally important to meet or exceed previous quality and reliability standards while at the same time reducing resource consumption. This textbook addresses this critical imperative integrating

Nonlinear models of elastic and visco-elastic one-dimensional continuous structures (beams and cables) are formulated by the authors of this title. Several models of increasing complexity are presente

"Covering a progressive medical field, Tissue Engineering describes the innovative process of regenerating human cells to restore or establish normal function in defective organs. As pioneering indivi

Robert Gehl's timely critique, Reverse Engineering Social Media, rigorously analyzes the ideas of social media and software engineers, using these ideas to find contradictions and fissures beneath the

Robert Gehl's timely critique, Reverse Engineering Social Media, rigorously analyzes the ideas of social media and software engineers, using these ideas to find contradictions and fissures beneath the

Analysis, assessment, and data management are core competencies for operation research analysts. This volume addresses a number of issues and developed methods for improving those skills. It is an out

Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. The aim of this textbook is to introduce machine learning, and the algorithmic paradigms it offers, in a principled way. The book provides a theoretical account of the fundamentals underlying machine learning and the mathematical derivations that transform these principles into practical algorithms. Following a presentation of the basics, the book covers a wide array of central topics unaddressed by previous textbooks. These include a discussion of the computational complexity of learning and the concepts of convexity and stability; important algorithmic paradigms including stochastic gradient descent, neural networks, and structured output learning; and emerging theoretical concepts such as the PAC-Bayes approach and compression-based bounds. Designed for advanced undergraduates or beginning graduates, the text makes the fundamentals and algorithms of machine learning accessible t

This book offers a concise introduction to mathematical inequalities for graduate students and researchers in the fields of engineering and applied mathematics. It begins by reviewing essential facts

This book covers fundamental principles and computational approaches relevant to visual saliency computation. As an interdisciplinary problem, visual saliency computation is introduced in this book fr

* This book addresses the problem of writing applications in a multi-language environment in which interfacing with Excel plays a vital role* The goal is to show how to write code in C#, C++ and VBA t

Offering a fundamental basis in kernel-based learning theory, this book covers both statistical and algebraic principles. It provides over 30 major theorems for kernel-based supervised and unsupervised learning models. The first of the theorems establishes a condition, arguably necessary and sufficient, for the kernelization of learning models. In addition, several other theorems are devoted to proving mathematical equivalence between seemingly unrelated models. With over 25 closed-form and iterative algorithms, the book provides a step-by-step guide to algorithmic procedures and analysing which factors to consider in tackling a given problem, enabling readers to improve specifically designed learning algorithms, build models for new applications and develop efficient techniques suitable for green machine learning technologies. Numerous real-world examples and over 200 problems, several of which are Matlab-based simulation exercises, make this an essential resource for graduate student

Advanced approaches to software engineering and design are capable of solving complex computational problems and achieving standards of performance that were unheard of only decades ago. Handbook of R

Through extensive examples and case studies, Wavelet Neural Networks provides a step-by-step introduction to modeling, training, and forecasting using wavelet networks. The acclaimed authors present a

"This book combines recent advances and best practices to improve the curriculum of software engineering education, bridging the gap between industry expectations and what academia can provide in soft

The fast multipole method is one of the most important algorithms in computing developed in the 20th century. Along with the fast multipole method, the boundary element method (BEM) has also emerged as a powerful method for modeling large-scale problems. BEM models with millions of unknowns on the boundary can now be solved on desktop computers using the fast multipole BEM. This is the first book on the fast multipole BEM, which brings together the classical theories in BEM formulations and the recent development of the fast multipole method. Two- and three-dimensional potential, elastostatic, Stokes flow, and acoustic wave problems are covered, supplemented with exercise problems and computer source codes. Applications in modeling nanocomposite materials, bio-materials, fuel cells, acoustic waves, and image-based simulations are demonstrated to show the potential of the fast multipole BEM. Enables students, researchers, and engineers to learn the BEM and fast multipole method from a s

This book presents fundamentals of reliability engineering with its applications in evaluating reliability of multistage interconnection networks. In the first part of the book, it introduces the conc

This book provides comprehensive treatment of machine to machine (M2M) communication. It supplies an in-depth understanding of the various architectures for M2M systems and technologies that enable th

The Soft Computing techniques, which are based on the information processing of biological systems are now massively used in the area of pattern recognition, making prediction & planning, as well

This book describes the theoretical and practical aspects of solving complicated and coupled models in engineering with analytical and numerical methods. It covers analytical and numerical methods in

The book delivers and explains some of the best, industry-proven methods and tools for the easy and fast solution of complex electromagnetic phenomena, mostly in large power equipment and systems, due

Software quality stems from two distinctive, but associated, topics in software engineering: software functional quality and software structural quality. Software Quality Engineering studies the tenet

With applications ranging from medical diagnostics to environmental monitoring, molecular sensors (also known as biosensors, chemical sensors, or chemosensors), along with emerging nanotechnologies of

Reinforcement learning (RL) is a framework for decision making in unknown environments based on a large amount of data. Several practical RL applications for business intelligence, plant control, and