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Intelligent Computing Systems and Their Applications
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Intelligent Computing Systems and Their Applications

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: 30 March 2025 | Viewed by 4143

Special Issue Editor

Prof. Dr. Yongming Li

E-Mail Website
Guest Editor
Department of Microelectronics and Communication Engineering, Chongqing University, Chongqing 400044, China
Interests: Intelligent information processing and pattern recognition; data fusion and analysis; artificial intelligence and health informatics; artificial intelligence and mode identification; intelligent perception and human data science; biomedical signal and information processing

Special Issue Information

Dear Colleagues,

With lots of sensors applied into many fields, mass information, precise recognition, and flexibility have become integral to present intelligent computing. This poses new challenges in the advancement of intelligent computing systems, including intelligent algorithms, data processing, computing platform, and their applications. Therefore, this Special Issue intends to present new ideas and experimental results in the field of intelligent computing systems, relating to theory, algorithms, software, platforms, and their practical use.

Areas relevant to intelligent computing systems include, but are not limited to, artificial intelligence, big data analytics, complex networks, neural networks, fuzzy systems, machine learning, deep learning and real-world applications, self-organization, emerging or bio-inspired ssystems, global optimization, evolutionary algorithms meta-heuristics, fuzzy computing, and their application in various fields.

Prof. Dr. Yongming Li
Guest Editor

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. Applied Sciences 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

  • intelligent computing
  • artificial intelligence
  • machine learning
  • deep learning
  • intelligent system
  • computing technology and system
  • artificial intelligence
  • pattern recognition
  • machine vision
  • big data and knowledge discovery
  • applications in industry, agriculture, health, medicine, transportation, security, management, and so on
  • computer networks
  • mobile computing
  • embedded systems
  • distributed systems
  • intelligent learning systems, including algorithm/system design

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Published Papers (2 papers)

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Research

26 pages, 8628 KiB  
Article
Toward Smart SCADA Systems in the Hydropower Plants through Integrating Data Mining-Based Knowledge Discovery Modules
by Gheorghe Grigoras, Răzvan Gârbea and Bogdan-Constantin Neagu
Appl. Sci. 2024, 14(18), 8228; https://doi.org/10.3390/app14188228 - 12 Sep 2024
Viewed by 1099
Abstract
The increasing importance of hydropower generation has led to the development of new smart technologies and the need for reliable and efficient equipment in this field. As long as hydropower plants are more complex to build up than other power plants, the operation [...] Read more.
The increasing importance of hydropower generation has led to the development of new smart technologies and the need for reliable and efficient equipment in this field. As long as hydropower plants are more complex to build up than other power plants, the operation regimes and maintenance activities become essential for the hydropower companies to optimize their performance, such that including the data-driven approaches in the decision-making process represents a challenge. In this paper, a comprehensive and multi-task framework integrated into a Knowledge Discovery module based on Data Mining to support the decisions of the operators from the control rooms and facilitate the transition from the classical to smart Supervisory Control and Data Acquisition (SCADA) system in hydropower plants has been designed, developed, and tested. It integrates tasks related to detecting the outliers through advanced statistical procedures, identifying the operating regimes through the patterns associated with typical operating profiles, and developing strategies for loading the generation units that consider the number of operating hours and minimize the water amount used to satisfy the power required by the system. The proposed framework has been tested using the SCADA system’s database of a hydropower plant belonging to the Romanian HydroPower Company. The framework can offer the operators from the control room comparative information for a time horizon longer than one year. The tests demonstrated the utility of a Knowledge Discovery module to ensure the transition toward smart SCADA systems that will help the decision-makers improve the management of the hydropower plants. Full article
(This article belongs to the Special Issue Intelligent Computing Systems and Their Applications)
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17 pages, 660 KiB  
Article
Digitalization of Management Processes in Small and Medium-Sized Enterprises—An Overview of Low-Code and No-Code Platforms
by Roman Domański, Hubert Wojciechowski, Jacek Lewandowicz and Łukasz Hadaś
Appl. Sci. 2023, 13(24), 13078; https://doi.org/10.3390/app132413078 - 7 Dec 2023
Cited by 3 | Viewed by 2070
Abstract
The permanent digitization of management processes entails, among other things, a need for the automation of the process of making certain business decisions. The aim of the article is to review and evaluate low-code/no-code platforms used, for instance, in small and medium-sized enterprises, [...] Read more.
The permanent digitization of management processes entails, among other things, a need for the automation of the process of making certain business decisions. The aim of the article is to review and evaluate low-code/no-code platforms used, for instance, in small and medium-sized enterprises, available on the Polish IT market. Using a systematic literature review, an assessment of the scale of the discussed issue, involving the number of publications, detailed topics covered, etc., is provided in the theoretical part of the study. During our research, using grey incidence analysis, a ranking of low-code/no-code platforms is created based on the characteristics that they offer. The article highlights the benefits of using new technologies in the form of low-code/no-code platforms in the management of smaller organizations. Full article
(This article belongs to the Special Issue Intelligent Computing Systems and Their Applications)
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