Neural Networks and Data Analytics for Sustainable Development
A special issue of Sustainability (ISSN 2071-1050).
Deadline for manuscript submissions: closed (31 December 2021) | Viewed by 13112
Special Issue Editors
Interests: neural networks; sustainability; information theory; metric topology; stochastic dynamics; statistical mechanics; machine learning; big data
Special Issues, Collections and Topics in MDPI journals
Interests: machine learning; sustainability; graph for neural networks
Special Issue Information
Dear Colleagues,
Neural networks (NNs) are biologically inspired computational tools which are able to learn, classify or forecast data. Since an NN is robust against a noisy environment and efficient enough to solve complex nonlinear problems, it has been applied to a broad range of sciences and technologies.
Thus, we expect it to also be suitable for application to achieve an equilibrium between targets of different disciplines, such as sociology, economy or ecology, and to enhance our understanding of this complex sustainability problem from a quantitative viewpoint.
Several NNs have been proposed, among them are feed-forward and recurrent NN, with supervised and unsupervised learning rules, with short or long range connections, some of them able to store and retrieve patterns, others to classify examples, or to predict time series. LSTM or deep learning has largely been used recently. Together with other machine learning models, such as the Bayesian Networks or the Genetic Algorithms, these techniques are useful to analyze massive data with complex behavior, the so called Big Data.
The present special issue aims to contribute to the theoretical and empirical improvement of our knowledge of climate change, environmental conservation, waste management, and other tasks of a sustainable world, by using NN.
a) Focus:
The present issue aims to produce an interplay between theoretical and empirical knowledge on neural networks and its applications for sustainable development. Interdisciplinary cooperation between researchers from the environmental sciences, economy, sociology, engineers or physicists is expected, as well as their exchanging of experiences.
b) Scope
We expect papers on any of the following subjects:
- NN applied to forecast deforestation.
- NN applied to the waste recycling.
- NN applied to the touristic impact problem.
- NN applications to the migration flows.
- Big Data for water and air pollution.
- Big Data for local vs global development.
- Big Data for renewable energy.
- Big Data for rural vs urban areas.
- Sustainability inspired NN models.
- Related NN theory and applications.
Supplement:
This issue should be related to publications found in journals from the Web of Science
categories, among others:
Computer Sciences – Artificial Inteligence, & Interdisciplinary Applications.
Ecology, Economics,
Engineering – Environmental, & Multidisciplinary
Green & Sustainable Science & Technology
Mathematics – Interdisciplinary Applications
Multidisciplinary Sciences
Physics – Multidisciplinary
Social Sciences – Interdisciplinary, & Mathematical Methods
Statistics & Probability
Prof. Dr. David Dominguez
Prof. Dr. Mario Gonzalez
Prof. Dr. Sara Cuenda
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- Neural Networks
- Sustainability
- Big Data
- Local vs Global development
- Renewable resources
- Climate change
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