The Importance of Machine Learning in Intelligent Systems

被引:1
|
作者
Stupar, Savo [1 ]
Car, Mirha Bico [1 ]
Kurtovic, Emir [1 ]
Vico, Grujica [2 ]
机构
[1] Univ Sarajevo, Sch Econ & Business, Trg Oslobodenj 1, Sarajevo, Bosnia & Herceg
[2] Univ East Sarajevo, Fac Agr, Vuka Karadzica 30, East Sarajevo, Bosnia & Herceg
关键词
Artificial intelligence; Machine learning; Machine learning algorithms; Intelligent systems; Supervised learning; Unsupervised learning;
D O I
10.1007/978-3-030-75275-0_70
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
When it comes to the modern business environment, which is characterized by an extremely high degree of competition, and incredible speed and dynamics of business activities, it is almost impossible to imagine the business of a successful company without the support of the most sophisticated information technologies. One of these technologies is certainly intelligent systems, i.e. artificial intelligence systems. Conventional information systems support almost all business processes in companies, and the greatest importance is to support management in making business decisions. The biggest progress in the field of information support for decision-making was made by intelligent systems, which are the first of all known types of information support to the company's management trying, and to the greatest extent succeeding, to solve problems whose solution was possible only with human intelligence. A large number of intelligent systems, such as Artificial Neural Networks, Expert Systems and Genetic Algorithms, are intended to solve mostly unstructured problems of a very high level of complexity or more precisely problems of such a level of complexity, which cannot be solved by conventional programming methods. Unlike other intelligent systems, which are mostly limited to sequential processing and only to certain specific representations of knowledge and logic, these intelligent systems use a different approach, and that is processing that imitates certain processing abilities possessed by the human brain. One of the most important abilities of human intelligence is learning, both from one's own and someone else's experience, which results in recognizing patterns based on experiences. The technology, which enables this ability to be possessed by computers, i.e. computer programs, is called Machine Learning. The aim of this paper is to unify and systematize in one place some basic knowledge that is usually published in various articles and /or books, where the topic of Machine Learning is observed from different aspects, and to explain the concept of Machine Learning, generic algorithms it is based, the types of machine learning, and the importance of applying this technology in intelligent systems.
引用
收藏
页码:638 / 646
页数:9
相关论文
共 50 条
  • [1] Machine Learning Systems and Intelligent Applications
    Benton, William C.
    IEEE SOFTWARE, 2020, 37 (04) : 43 - 49
  • [2] The Importance of Generalizability in Machine Learning for Systems
    Gohil, Varun
    Dev, Sundar
    Upasani, Gaurang
    Lo, David
    Ranganathan, Parthasarathy
    Delimitrou, Christina
    IEEE COMPUTER ARCHITECTURE LETTERS, 2024, 23 (01) : 95 - 98
  • [3] Machine Learning Techniques for Protecting Intelligent Vehicles in Intelligent Transport Systems
    Chen, Yuan
    INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2024, 15 (08) : 250 - 258
  • [4] Human-Machine Learning for Intelligent Aircraft Systems
    Rubin, Stuart H.
    Lee, Gordon
    AUTONOMOUS AND INTELLIGENT SYSTEMS, 2011, 6752 : 331 - 342
  • [5] Computer Vision and Machine Learning for Intelligent Sensing Systems
    Tian, Jing
    SENSORS, 2023, 23 (09)
  • [6] Comparison of machine learning methods for intelligent tutoring systems
    Hamalainen, Wilhelmiina
    Vinni, Mikko
    INTELLIGENT TUTORING SYSTEMS, PROCEEDINGS, 2006, 4053 : 525 - 534
  • [7] Intelligent systems in obstetrics and midwifery: Applications of machine learning
    Barbounaki, Stavroula
    Vivilaki, Victoria G.
    EUROPEAN JOURNAL OF MIDWIFERY, 2021, 5
  • [8] Intelligent modeling of nonlinear dynamical systems by machine learning
    Chen, Ruilin
    Jin, Xiaowei
    Laima, Shujin
    Huang, Yong
    Li, Hui
    INTERNATIONAL JOURNAL OF NON-LINEAR MECHANICS, 2022, 142
  • [9] An intelligent learning machine
    Sayad, S
    Balke, ST
    Sayad, S
    DATA MINING IV, 2004, 7 : 639 - 649
  • [10] Machine learning towards intelligent systems: applications, challenges, and opportunities
    MohammadNoor Injadat
    Abdallah Moubayed
    Ali Bou Nassif
    Abdallah Shami
    Artificial Intelligence Review, 2021, 54 : 3299 - 3348