Intelligent Systems: Development and Issues

Pupkov, K.A.

doi:10.1016/j.procs.2017.01.069

Cited by 9 publications

(3 citation statements)

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“…Intelligent model should be a set of technical ways combined by informational process and interacting with one person (or group of people) or working independently, that is able to make a decision strongly based on information, knowledge and incentive to produce an objective and find a rational way to achieve the goal (Pupkov, 2017). For example, Cooperative Intelligent Transport System (C-ITS) is a promising technology/conception which aims to practically enhance road safety, upgrade traffic management and increase driver comfort (Javed et al, 2019).…”

Section: Theoretical Viewmentioning

confidence: 99%

An Extended Version of the Fuzzy-Euclidean Intelligent Fitness Model (FEIFM) Implementation for Selecting Personal Vehicle

Chang¹,

Edwin²,

Utama³

2019

Journal of Computer Science

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Indeed, intelligent model is a sub-domain in computer science that its purposes utilized in numerous pieces of reality. Particularly in case of automotive industry, to select the most appropriate personal vehicle is challenging for the customers. The challenge was taken as a main problem of this study. In this research, the reasonableness is characterized by the customer parameters which portray the customer's identity. By utilizing the mix technique for fuzzy-logic and Euclidean distance calculation, the customer's identities are fitted into the personal-vehicle parameters. At long last, the constructed model for choosing personal vehicle plays several customer's parameters; e.g., age, gender, education, income and job. The model designed thru utilizing the object-oriented methodology. The result of simulation of 66 purchasers and 44 conceivable vehicles are able to propose the most reasonable vehicle for every purchaser. As an extended version, the model successfully delivers the completed scheme due to added parameters and method. It is a truthful contribution provided by this research.

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Section: Theoretical Viewmentioning

confidence: 99%

An Extended Version of the Fuzzy-Euclidean Intelligent Fitness Model (FEIFM) Implementation for Selecting Personal Vehicle

Chang¹,

Edwin²,

Utama³

2019

Journal of Computer Science

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“…IS are based on two major approaches -artificial intelligence and soft computing which include a variety of different techniques, such as neural networks, expert systems, fuzzy logic and fuzzy systems, genetic algorithms and genetic programming, and others. All of this techniques operate together in order to improve strategic decision making and ensure flexible processing abilities of data and information for dealing with real world situations [21,22,23,24].…”

Section: Intelligent Systemsmentioning

confidence: 99%

“…Another advantage of intelligent systems over conventional systems is that IS recognizes the available data which might be incomplete, uncertain or fuzzy, where they can still make a reasonable solutions, while conventional systems can manipulate only with data which are complete or exact [26]. Moreover, automatic decision support, artificial evolution, parallel execution, virtual integration, intelligent search and optimization present unique abilities of intelligent systems which are not available in conventional information system [23,24].…”

Section: Intelligent Systemsmentioning

confidence: 99%

Predictive Manufacturing Systems in Industry 4.0: Trends, Benefits and Challenges

Nikolić¹,

Ignjatic²,

Suzić³

et al. 2017

DAAAM Proceedings

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The fourth industrial revolution, known as Industry 4.0, has tendency to push the boundaries of science and technology. This is especially true for the manufacturing industry. One of the biggest challenges facing the manufacturing industry today is how to make intelligent systems for production with "self-aware", "self-predict and "self-maintain" abilities. Predictive manufacturing systems (PMS) are new intelligent systems that provide these abilities in the production, processes and machines. The PMS combines different technologies and techniques: statistics, data mining, modelling and artificial intelligence methods. These technologies and techniques are used to convert data into information and make predictions about the observed system. This paper provides an overview of the various challenges, existing solutions and benefits of PMS, with a focus on success factors in Industry 4.0.

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Multidimensional Linguistic Variables and Their Application for Resolving the Tasks of Marshaling Processes Automation

Shabelnikov

Lyabakh

Malishevskaya

2018

Advances in Intelligent Systems and Computing

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Intelligent Systems: Development and Issues

Cited by 9 publications

References 0 publications

An Extended Version of the Fuzzy-Euclidean Intelligent Fitness Model (FEIFM) Implementation for Selecting Personal Vehicle

An Extended Version of the Fuzzy-Euclidean Intelligent Fitness Model (FEIFM) Implementation for Selecting Personal Vehicle

Predictive Manufacturing Systems in Industry 4.0: Trends, Benefits and Challenges

Multidimensional Linguistic Variables and Their Application for Resolving the Tasks of Marshaling Processes Automation

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