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This new volume explores the computational intelligence techniques
necessary to carry out different software engineering tasks.
Software undergoes various stages before deployment, such as
requirements elicitation, software designing, software project
planning, software coding, and software testing and maintenance.
Every stage is bundled with a number of tasks or activities to be
performed. Due to the large and complex nature of software, these
tasks can become costly and error prone. This volume aims to help
meet these challenges by presenting new research and practical
applications in intelligent techniques in the field of software
engineering. Computational Intelligence Applications for Software
Engineering Problems discusses techniques and presents case studies
to solve engineering challenges using machine learning, deep
learning, fuzzy-logic-based computation, statistical modeling,
invasive weed meta-heuristic algorithms, artificial intelligence,
the DevOps model, time series forecasting models, and more.
The book presents a collection of peer-reviewed articles from the
International Conference on Advances and Applications of Artificial
Intelligence and Machine Learning - ICAAAIML 2020. The book covers
research in artificial intelligence, machine learning, and deep
learning applications in healthcare, agriculture, business, and
security. This volume contains research papers from academicians,
researchers as well as students. There are also papers on core
concepts of computer networks, intelligent system design and
deployment, real-time systems, wireless sensor networks, sensors
and sensor nodes, software engineering, and image processing. This
book will be a valuable resource for students, academics, and
practitioners in the industry working on AI applications.
The book presents a collection of peer-reviewed articles from the
International Conference on Advances and Applications of Artificial
Intelligence and Machine Learning - ICAAAIML 2020. The book covers
research in artificial intelligence, machine learning, and deep
learning applications in healthcare, agriculture, business, and
security. This volume contains research papers from academicians,
researchers as well as students. There are also papers on core
concepts of computer networks, intelligent system design and
deployment, real-time systems, wireless sensor networks, sensors
and sensor nodes, software engineering, and image processing. This
book will be a valuable resource for students, academics, and
practitioners in the industry working on AI applications.
This book provides an insight on the importance that Internet of
Vehicles (IoV) solutions can have in taking care of vehicular
safety through internetworking and automation. Key features of the
book are the inclusion and elaboration of recent and emerging
developments in various specializations of intelligent
transportation systems and their solutions by incorporating IoT
(Internet of Things) and IoV. This book presents to its readers
useful IoV applications and architectures that cater to their
improved driving requirements and lead towards autonomous driving.
The application domains have a large range in which vehicular
networking, communication technology, sensor devices, computing
materials and devices, IoT communication, vehicular and on-road
safety, data security and other topics are included.
This book provides an insight on the importance that Internet of
Vehicles (IoV) solutions can have in taking care of vehicular
safety through internetworking and automation. Key features of the
book are the inclusion and elaboration of recent and emerging
developments in various specializations of intelligent
transportation systems and their solutions by incorporating IoT
(Internet of Things) and IoV. This book presents to its readers
useful IoV applications and architectures that cater to their
improved driving requirements and lead towards autonomous driving.
The application domains have a large range in which vehicular
networking, communication technology, sensor devices, computing
materials and devices, IoT communication, vehicular and on-road
safety, data security and other topics are included.
This work is an effort to determine the Key performance Indicators
(KPIs) for Supply Chain Management in Manufacturing Industries.The
KPIs are integral part of Balance Score Card approach.By
implementing these KPIs, manufacturing firms can better manage
their forward and backward linkages of business resulting in
overall improvement in their performance and hence bottom line.Most
of KPIs seek to build co-ordination and integration in existing
supply chain for better organization of resources.More emphasis has
been given on adopting internet based functions, so that
organizations can rely on faster, efficient communication and
control.This work is very suitable for small and medium enterprises
in third world countries which face large number of physical
constraints such as lack of logistics infrastructure, large gap
between demand and supply just a few of them.Better Integration of
supply chains can overcome these challenges resulting in more
responsiveness to market dynami
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