Autor: Laktionov, Ivan - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Information technology for comprehensive monitoring and control of the microclimate in industrial greenhouses based on fuzzy logic
Autorzy:: Laktionov, Ivan
Vovna, Oleksandr
Kabanets, Maryna
Powiązania:: https://bibliotekanauki.pl/articles/2201317.pdf
Data publikacji:: 2023
Wydawca:: Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:: monitoring
control
information technology
greenhouse
fuzzy logic
Opis:: Nowadays, applied computer-oriented and information digitalization technologies are developing very dynamically and are widely used in various industries. One of the highest priority sectors of the economy of Ukraine and other countries around the world, the needs of which require intensive implementation of high-performance information technologies, is agriculture. The purpose of the article is to synthesise scientific and practical provisions to improve the information technology of the comprehensive monitoring and control of microclimate in industrial greenhouses. The object of research is nonstationary processes of aggregation and transformation of measurement data on soil and climatic conditions of the greenhouse microclimate. The subject of research is methods and models of computer-oriented analysis of measurement data on the soil and climatic state of the greenhouse microclimate. The main scientific and practical effect of the article is the development of the theory of intelligent information technologies for monitoring and control of greenhouse microclimate through the development of methods and models of distributed aggregation and intellectualised transformation of measurement data based on fuzzy logic.
Źródło:: Journal of Artificial Intelligence and Soft Computing Research; 2023, 13, 1; 19--35
2083-2567
2449-6499
Pojawia się w:: Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: A new approach to image-based recommender systems with the application of heatmaps maps
Autorzy:: Woldan, Piotr
Duda, Piotr
Cader, Andrzej
Laktionov, Ivan
Powiązania:: https://bibliotekanauki.pl/articles/2201330.pdf
Data publikacji:: 2023
Wydawca:: Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:: feature extraction
recommender system
heatmap
Opis:: One of the fundamental issues of modern society is access to interesting and useful content. As the amount of available content increases, this task becomes more and more challenging. Our needs are not always formulated in words; sometimes we have to use complex data types like images. In this paper, we consider the three approaches to creating recommender systems based on image data. The proposed systems are evaluated on a real-world dataset. Two case studies are presented. The first one presents the case of an item with many similar objects in a database, and the second one with only a few similar items
Źródło:: Journal of Artificial Intelligence and Soft Computing Research; 2023, 13, 2; 63--72
2083-2567
2449-6499
Pojawia się w:: Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: An explainable AI approach to agrotechnical monitoring and crop diseases prediction in Dnipro region of Ukraine
Autorzy:: Laktionov, Ivan
Diachenko, Grigorii
Rutkowska, Danuta
Kisiel-Dorohinicki, Marek
Powiązania:: https://bibliotekanauki.pl/articles/23944837.pdf
Data publikacji:: 2023
Wydawca:: Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:: IoT
ANFIS
explainable AI
agrotechnical monitoring
disease prediction
crop
Opis:: The proliferation of computer-oriented and information digitalisation technologies has become a hallmark across various sectors in today’s rapidly evolving environment. Among these, agriculture emerges as a pivotal sector in need of seamless incorporation of highperformance information technologies to address the pressing needs of national economies worldwide. The aim of the present article is to substantiate scientific and applied approaches to improving the efficiency of computer-oriented agrotechnical monitoring systems by developing an intelligent software component for predicting the probability of occurrence of corn diseases during the full cycle of its cultivation. The object of research is non-stationary processes of intelligent transformation and predictive analytics of soil and climatic data, which are factors of the occurrence and development of diseases in corn. The subject of the research is methods and explainable AI models of intelligent predictive analysis of measurement data on the soil and climatic condition of agricultural enterprises specialised in growing corn. The main scientific and practical effect of the research results is the development of IoT technologies for agrotechnical monitoring through the development of a computer-oriented model based on the ANFIS technique and the synthesis of structural and algorithmic provision for identifying and predicting the probability of occurrence of corn diseases during the full cycle of its cultivation.
Źródło:: Journal of Artificial Intelligence and Soft Computing Research; 2023, 13, 4; 247--272
2083-2567
2449-6499
Pojawia się w:: Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:: Biblioteka Nauki

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