Advances in Intelligent Systems and Computing
The series “Advances in Intelligent Systems and Computing” contains publications on theory,
applications, and design methods of Intelligent Systems and Intelligent Computing. Virtually all
disciplines such as engineering, natural sciences, computer and information science, ICT, economics,
business, e-commerce, environment, healthcare, life science are covered. The list of topics spans all the
areas of modern intelligent systems and computing such as: computational intelligence, soft computing
including neural networks, fuzzy systems, evolutionary computing and the fusion of these paradigms,
social intelligence, ambient intelligence, computational neuroscience, artificial life, virtual worlds and
society, cognitive science and systems, Perception and Vision, DNA and immune based systems,
self-organizing and adaptive systems, e-Learning and teaching, human-centered and human-centric
computing, recommender systems, intelligent control, robotics and mechatronics including
human-machine teaming, knowledge-based paradigms, learning paradigms, machine ethics, intelligent
data analysis, knowledge management, intelligent agents, intelligent decision making and support,
intelligent network security, trust management, interactive entertainment, Web intelligence and multimedia.
The publications within “Advances in Intelligent Systems and Computing” are primarily proceedings
of important conferences, symposia and congresses. They cover significant recent developments in the
field, both of a foundational and applicable character. An important characteristic feature of the series is
the short publication time and world-wide distribution. This permits a rapid and broad dissemination of
This book contains a selection of papers accepted for the presentation and discussion
at the 2018 International Conference on Digital Science (DSIC’18). This
Conference had the support of the Institute of Certified Specialists, Russia, AISTI
(Iberian Association for Information Systems and Technologies), and Springer. It
will take place at Convention Centre, Budva, Montenegro, October 19–21, 2018.
DSIC’18 is an international forum for researchers and practitioners to present
and discuss the most recent innovations, trends, results, experiences, and concerns
in the several perspectives of Digital Science. The main idea of this Conference is
that the world of science is unified and united allowing all scientists/practitioners to
be able to think, analyze, and generalize their thoughts.
DSIC aims efficiently to disseminate original research results in natural, social,
art, and humanities sciences. An important characteristic feature of the Conference
should be the short publication time and worldwide distribution. This Conference
enables fast dissemination, so conference participants can publish their papers in
print and electronic format, which is then made available worldwide and accessible
by numerous researchers.
The Scientific Committee of DSIC’18 was composed of a multidisciplinary
group of 26 experts. One hundred and seven invited reviewers who are intimately
concerned with Digital Science have had the responsibility for evaluating, in a
“double-blind review” process, the papers received for each of the main themes
proposed for the Conference: Digital Art and Humanities; Digital Economics;
Digital Education; Digital Engineering; Digital Environmental Sciences; Digital
Finance, Business and Banking; Digital Media; Digital Medicine, Pharma and
Public Health; Digital Public Administration; Digital Technology and Applied
DSIC’18 received 88 contributions from 16 countries around the world. The
papers accepted for the presentation and discussion at the Conference are published
by Springer (this book) and will be submitted for indexing by ISI, SCOPUS, among
The article deals with the problem of creating a temperature regulator, which does not require preliminary tuning for a specific production plant. Authors proposed to use a matrix approach of fuzzy logic for this purpose. It allows engineers to apply the linguistic rules formulated in the most general form for industrial processes control. It also allows building simple control algorithms for complex nonlinear systems. To verify the correctness of the algorithm, authors assembled installation with heaters of various types, powers and inertia. The full-scale experiment shown that the developed prototype of the device allows controlling the temperature in various settings without initial tuning.
This article proposes a method of constructing dynamic neural network mathematical models that allow not only to diagnose the disease at the current time, but also to simulate the appearance and development of diseases in future periods of time, as well as to control their appearance and development by selecting the optimal lifestyle and optimal intake of drugs. It is assumed that the use of dynamic neural network medical systems, instead of static, allow doctors, before prescribing courses of treatment to patients, to test the effect of drugs not on patients, but on their virtual mathematical models. The action of the system is demonstrated by examples.
This article describes development experience of the neural network system for medical diagnostic of gastrointestinal diseases. There was used patient’s practical medical information for its creation. As input parameters were taken into consideration different factor groups, include demographic, patient’s complaints, life history, medical history and additional methods of research. Neural network model allowed making a significance assessment of factors, which have disease’s development influence. As a result, was designed neural network system of differential diagnosis, allowing diagnoses “gastritis”, “peptic ulcer”. In the future, developed diagnostic system can be used as a “provisional diagnosis of gastrointestinal diseases”.
This article is devoted to the method of creating an intelligent neural network system. Unlike existing similar systems, the proposed system does not require frequent updates, because it is able to adapt itself to the constantly changing state of the economy and to the peculiarities of a particular region. Besides, the proposed system allows performing scenario forecasting of regional real estate markets depending on virtually changing economic parameters such as the dollar rate, the market price of oil, gross domestic product and gross regional product, the volume of housing construction in the region, the parameters of the state’s credit policy, etc.