This book plays a significant role in improvising human life to a
great extent. The new applications of soft computing can be
regarded as an emerging field in computer science, automatic
control engineering, medicine, biology application, natural
environmental engineering, and pattern recognition. Now, the
exemplar model for soft computing is human brain. The use of
various techniques of soft computing is nowadays successfully
implemented in many domestic, commercial, and industrial
applications due to the low-cost and very high-performance digital
processors and also the decline price of the memory chips. This is
the main reason behind the wider expansion of soft computing
techniques and its application areas. These computing methods also
play a significant role in the design and optimization in diverse
engineering disciplines. With the influence and the development of
the Internet of things (IoT) concept, the need for using soft
computing techniques has become more significant than ever. In
general, soft computing methods are closely similar to biological
processes than traditional techniques, which are mostly based on
formal logical systems, such as sentential logic and predicate
logic, or rely heavily on computer-aided numerical analysis. Soft
computing techniques are anticipated to complement each other. The
aim of these techniques is to accept imprecision, uncertainties,
and approximations to get a rapid solution. However, recent
advancements in representation soft computing algorithms (fuzzy
logic,evolutionary computation, machine learning, and probabilistic
reasoning) generate a more intelligent and robust system providing
a human interpretable, low-cost, approximate solution. Soft
computing-based algorithms have demonstrated great performance to a
variety of areas including multimedia retrieval, fault tolerance,
system modelling, network architecture, Web semantics, big data
analytics, time series, biomedical and health informatics, etc.
Soft computing approaches such as genetic programming (GP), support
vector machine-firefly algorithm (SVM-FFA), artificial neural
network (ANN), and support vector machine-wavelet (SVM-Wavelet)
have emerged as powerful computational models. These have also
shown significant success in dealing with massive data analysis for
large number of applications. All the researchers and practitioners
will be highly benefited those who are working in field of computer
engineering, medicine, biology application, signal processing, and
mechanical engineering. This book is a good collection of
state-of-the-art approaches for soft computing-based applications
to various engineering fields. It is very beneficial for the new
researchers and practitioners working in the field to quickly know
the best performing methods. They would be able to compare
different approaches and can carry forward their research in the
most important area of research which has direct impact on
betterment of the human life and health. This book is very useful
because there is no book in the market which provides a good
collection of state-of-the-art methods of soft computing-based
models for multimedia retrieval, fault tolerance, system modelling,
network architecture, Web semantics, big data analytics, time
series, and biomedical and health informatics.
General
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