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Enriching Artificial Intelligence Explanations with Knowledge Fragments
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In: Future Internet; Volume 14; Issue 5; Pages: 134 (2022)
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Deep Learning XAI for Bus Passenger Forecasting: A Use Case in Spain
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In: Mathematics; Volume 10; Issue 9; Pages: 1428 (2022)
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A Stacking Ensemble Deep Learning Model for Bitcoin Price Prediction Using Twitter Comments on Bitcoin
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In: Mathematics; Volume 10; Issue 8; Pages: 1307 (2022)
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Library for forecasting time series data from industrial sources ; Creación de una librería para predicción de series temporales de señales industriales
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Murillo González, Miguel. - : Consejo Superior de Investigaciones Científicas (España), 2021. : Universidad de Cantabria, 2021. : Universidad Internacional Menéndez Pelayo, 2021. : CSIC-UC - Instituto de Física de Cantabria (IFCA), 2021
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| 7 |
Management of reproduction of the livestock branch as the basis of its innovation-and-investment development ...
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Adaptive Kompetenzen von Kindern mit Down-Syndrom – ein Follow-up über zehn Jahre ... : Adaptive competences of children with Down syndrome - a ten-year follow-up ...
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Adaptive Kompetenzen von Kindern mit Down-Syndrom – ein Follow-up über zehn Jahre ; Adaptive competences of children with Down syndrome - a ten-year follow-up
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In: Empirische Sonderpädagogik 13 (2021) 2, S. 100-109 (2021)
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NEURAL NETWORK MODELS AND METHODS IN THE TASKS OF PERSONNEL DEVELOPMENT MANAGEMENT IN COMPANIES ...
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| 11 |
Climate Risks and the Realized Volatility Oil and Gas Prices: Results of an Out-of-Sample Forecasting Experiment
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In: Energies; Volume 14; Issue 23; Pages: 8085 (2021)
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| 12 |
A Brief Taxonomy of Hybrid Intelligence
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In: Forecasting ; Volume 3 ; Issue 3 ; Pages 39-643 (2021)
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APPLICATION OF THE ECONOMETRIC APPROACH TO FORECASTING THE KEY INDICATORS IN RENTAL OPERATIONS ; ЗАСТОСУВАННЯ ЕКОНОМЕТРИЧНОГО ПІДХОДУ ДО ПРОГНОЗУВАННЯ КЛЮЧОВИХ ПОКАЗНИКІВ В ОРЕНДНИХ ОПЕРАЦІЯХ
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In: The Economic Discourse; No. 3 (2020); 106-116 ; Економічний дискурс; № 3 (2020); 106-116 ; 2410-7476 ; 2410-0919 ; 10.36742/2410-0919-2020-3 (2021)
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| 14 |
Подходы к стратегическому планированию в высшем образовании : магистерская диссертация ; Approaches to Strategic Planning in Higher Education
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ПРОГНОЗИРОВАНИЕ КАК НАЧАЛЬНЫЙ ЭТАП УПРАВЛЕНИЯ ПЕРСОНАЛОМ ...
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ЗНАЧЕНИЕ СОЦИАЛЬНОГО СТАТУСА И РОЛИ ЛИЧНОСТИ ДЛЯ ЦЕЛЕЙ КРИМИНОЛОГИЧЕСКОГО ПРОГНОЗИРОВАНИЯ ИНДИВИДУАЛЬНОГО ПРЕСТУПНОГО ПОВЕДЕНИЯ ...
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| 17 |
Exploring Grey Systems Theory-Based Methods and Applications in Sustainability Studies: A Systematic Review Approach
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In: Sustainability ; Volume 12 ; Issue 11 (2020)
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Abstract:
In recent years, there have been international movements advocating more sustainable societies, and as a result of such movements, a remarkably important sub-branch has been shaped in systems studies called sustainability. It would be vital to propose methods that could deal with inherent complexities and uncertainties in such systems. Grey systems theory (GST) represents a nascent method that could help to solve complexities in the face of multifaceted problems, uncertainty, and complexity in systems, and the theory could considerably contribute to sustainability studies. The present study sought to fill a gap and provide an updated review of the literature on the roles and impacts of GST-based methods in sustainability studies as one of the most significant areas of exploring economic, social and environmental systems. Primarily, the theoretical foundations of sustainability and GST were briefly reviewed. Next, by categorizing the studies conducted in the literature on sustainability studies, GST-based methods used in such studies were identified. Finally, the advantages, effects and functions of GST-based theories and their applications in sustainability studies were explicated. The papers found in this systematic review were searched on such databases as Scopus, Web of Science, and ScienceDirect, as published from 2010 up to the first three months of 2020, based on these keywords: grey relation or grey relational, grey model, grey system or grey systems, grey prediction, grey control, grey incidence, grey cluster, grey decision, grey input-output. The total number of publications found on all of the databases was 446, although (following a more meticulous investigation of the publications) 145 ones were used for the comprehensive analysis. The 10 different areas in which GST was used to explore sustainability in the publications were: sustainability assessment, industrial sustainability, urban sustainability, energy sustainability, sustainability development, businesses sustainability, agricultural sustainability, sustainable products, tourism sustainability, social sustainability. The results revealed that complexity, uncertainty, and inaccessibility of a large set of data and initial statistical distributions led researchers to rely on GST in sustainability studies, and that the applied areas of GST in terms of sustainability issues had some features in common, including linguistic variables, long-term projects, technological demands, conflicting goals, and uncertainty. Moreover, compared to other methods used to deal with uncertainty, GST did not require the formation of an extensive databank of classified rules and was more practical and efficient in sustainability calculations (as complex systems) with fewer numerical calculations. Ignoring systematic approaches, causal relations, cause-effect loops, and dynamic feedback was the missing link in the application of GST in sustainability studies as complex economic, social and environmental systems.
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Keyword:
grey decision making; grey forecasting; grey incidence; grey model; grey number; grey relational analysis (GRA); grey systems theory; sustainability; sustainability assessment
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URL: https://doi.org/10.3390/su12114437
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Hybrid predictive decision-making approach to emission reduction policies for sustainable energy industry
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In: Energies ; Volume 13 ; Issue 9 (2020)
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| 19 |
Forecasting Model for Stock Market Based on Probabilistic Linguistic Logical Relationship and Distance Measurement
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In: Symmetry ; Volume 12 ; Issue 6 (2020)
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Assessing the quality of international trade and economic relations in the agricultural sector ; Оцінювання якості міжнародних торговельно-економічних відносин в аграрному секторі
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In: Economies' Horizons; No. 1(12) (2020): Economies’ Horizons; 91-101 ; Економічні горизонти; № 1(12) (2020): Економічні горизонти; 91-101 ; 2616-5236 ; 2522-9273 (2020)
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