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Wyświetlanie 1-2 z 2
Tytuł:
Business risk and project management in civil costruction branch
Autorzy:
Winiarski, Marek
Urbański, Mariusz
Faizan, Riffat
Powiązania:
https://bibliotekanauki.pl/articles/88637.pdf
Data publikacji:
2019
Wydawca:
Stowarzyszenie Menedżerów Jakości i Produkcji
Tematy:
project management
construction project
project phases
business risk
zarządzanie projektami
projekt budowlany
fazy projektu
ryzyko biznesowe
Opis:
Project management is general planning, coordination and inspection of the project, from the initial stage all the way to final phase, its purpose is an accomplishment of the accepted task and creation of the functional final effect, without exceeding established costs, time-frames and fulfillment of required standards of the quality. The present article was devoted to the issue of the project management in the construction sector in order to reduce the business risk. The study is based on literature examinations with an own methodological solution for project management in the construction industry. After introducing a set of definitions of the project and describing the concept of project management, a characterization of the project management in the construction industry and its effects in the economic space were described.
Źródło:
System Safety : Human - Technical Facility - Environment; 2019, 1, 1; 324-331
2657-5450
Pojawia się w:
System Safety : Human - Technical Facility - Environment
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Random forest based power sustainability and cost optimization in smart grid
Autorzy:
Durairaj, Danalakshmi
Wróblewski, Łukasz
Sheela, A.
Hariharasudan, A.
Urbański, Mariusz
Powiązania:
https://bibliotekanauki.pl/articles/23966623.pdf
Data publikacji:
2022
Wydawca:
Stowarzyszenie Menedżerów Jakości i Produkcji
Tematy:
smart grid
las losowy
internet rzeczy
zarządzanie energią
uczenie maszynowe
licznik inteligentny
random forest
Internet of things
power management
machine learning
smart meter
priority power scheduling
Opis:
Presently power control and management play a vigorous role in information technology and power management. Instead of non-renewable power manufacturing, renewable power manufacturing is preferred by every organization for controlling resource consumption, price reduction and efficient power management. Smart grid efficiently satisfies these requirements with the integration of machine learning algorithms. Machine learning algorithms are used in a smart grid for power requirement prediction, power distribution, failure identification etc. The proposed Random Forest-based smart grid system classifies the power grid into different zones like high and low power utilization. The power zones are divided into number of sub-zones and map to random forest branches. The sub-zone and branch mapping process used to identify the quantity of power utilized and the non-utilized in a zone. The non-utilized power quantity and location of power availabilities are identified and distributed the required quantity of power to the requester in a minimal response time and price. The priority power scheduling algorithm collect request from consumer and send the request to producer based on priority. The producer analysed the requester existing power utilization quantity and availability of power for scheduling the power distribution to the requester based on priority. The proposed Random Forest based sustainability and price optimization technique in smart grid experimental results are compared to existing machine learning techniques like SVM, KNN and NB. The proposed random forest-based identification technique identifies the exact location of the power availability, which takes minimal processing time and quick responses to the requestor. Additionally, the smart meter based smart grid technique identifies the faults in short time duration than the conventional energy management technique is also proven in the experimental results.
Źródło:
Production Engineering Archives; 2022, 28, 1; 82--92
2353-5156
2353-7779
Pojawia się w:
Production Engineering Archives
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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