Relevant bibliographies by topics / Multiattribute object

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  1. Journal articles
  2. Dissertations / Theses
  3. Conference papers

Academic literature on the topic 'Multiattribute object'

Author: Grafiati
Published: 30 May 2022
Last updated: 31 July 2025

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Journal articles on the topic "Multiattribute object"

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Zhang, Hongjun, Chengxiang Yin, Xiuli Qi, Rui Zhang, and Xingdang Kang. "Cognitive Best Worst Method for Multiattribute Decision-Making." Mathematical Problems in Engineering 2017 (2017): 1–11. http://dx.doi.org/10.1155/2017/1092925.

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Pairwise comparison based multiattribute decision-making (MADM) methods are widely used and studied in recent years. However, the perception and cognition towards the semantic representation for the linguistic rating scale and the way in which the pairwise comparisons are executed are still open to discuss. The commonly used ratio scale is likely to produce misapplications and the matrix based comparison style needs too many comparisons and is not able to guarantee the consistency of the matrix when the number of objects involved is large. This research proposes a new MADM method CBWM (Cogniti
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Ustinovichius, Leonas. "DETERMINATION OF EFFICIENCY OF INVESTMENTS IN CONSTRUCTION." International Journal of Strategic Property Management 8, no. 1 (2004): 25–43. http://dx.doi.org/10.3846/1648715x.2004.9637505.

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Decision making is associated with ranking problems aimed to obtain a set of preference order of solutions. People can make mistakes choosing the best object for investments. Due to high cost of such mistakes, such a choice should be well founded. A major goal of paper is to develop a theoretical basis for creating a decision support system aimed to increase building construction and reconstruction investment efficiency by applying multiattribute decision making approaches and mathematical modelling. To achieve the goal, the following problems have to be solved: to analyse new models currently
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Larichev, O. I., H. M. Moshkovich, and S. B. Rebrik. "Systematic research into human behavior in multiattribute object classification problems." Acta Psychologica 68, no. 1-3 (1988): 171–82. http://dx.doi.org/10.1016/0001-6918(88)90053-4.

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Qi, Jie, Tengfei Lin, Tao Zhao, Fangyu Li, and Kurt Marfurt. "Semisupervised multiattribute seismic facies analysis." Interpretation 4, no. 1 (2016): SB91—SB106. http://dx.doi.org/10.1190/int-2015-0098.1.

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One of the key components of traditional seismic interpretation is to associate or “label” a specific seismic amplitude package of reflectors with an appropriate seismic or geologic facies. The object of seismic clustering algorithms is to use a computer to accelerate this process, allowing one to generate interpreted facies for large 3D volumes. Determining which attributes best quantify a specific amplitude or morphology component seen by the human interpreter is critical to successful clustering. Unfortunately, many patterns, such as coherence images of salt domes, result in a salt-and-pepp
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Jin, Jing-Zhong, Yoshiteru Nakamori, and Andrzej P. Wierzbicki. "A Study on Multiattribute Aggregation Approaches to Product Recommendation." Advances in Fuzzy Systems 2013 (2013): 1–11. http://dx.doi.org/10.1155/2013/806749.

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In today’s increasingly competitive market, consumers usually have to face a huge number of products with different designs but having the same use. Therefore, an important problem for manufacturers is to attract consumers by special designs of the products. This paper aims at the improvement of a consumer-oriented approach in recommending products, and proposing a recommendation system for Japanese traditional crafts based on target-oriented fuzzy method and ontological engineering. Specifically, a target-oriented fuzzy method is used for measuring the fitness of a selected attribute to a cer
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Wu, Yanhui, Wei Wang, Guowei Zhu, and Peng Wang. "Application of seismic multiattribute machine learning to determine coal strata thickness." Journal of Geophysics and Engineering 18, no. 6 (2021): 834–44. http://dx.doi.org/10.1093/jge/gxab054.

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Abstract The coal mining industry is developing automated and intelligent coal mining processes. Accurate determination of the geological conditions of working faces is an important prerequisite for automated mining. The use of machine learning to extract comprehensive attributes from seismic data and the application of that data to determine the coal strata thickness has become an important area of research in recent years. Conventional coal strata thickness interpretation methods do not meet the application requirements of mines. Determining the coal strata thickness with machine learning so
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Ebuna, Daniel R., Jared W. Kluesner, Kevin J. Cunningham, and Joel H. Edwards. "Statistical approach to neural network imaging of karst systems in 3D seismic reflection data." Interpretation 6, no. 3 (2018): B15—B35. http://dx.doi.org/10.1190/int-2017-0197.1.

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The current lack of a robust standardized technique for geophysical mapping of karst systems can be attributed to the complexity of the environment and prior technological limitations. Abrupt lateral variations in physical properties that are inherent to karst systems generate significant geophysical noise, challenging conventional seismic signal processing and interpretation. The application of neural networks (NNs) to multiattribute seismic interpretation can provide a semiautomated method for identifying and leveraging the nonlinear relationships exhibited among seismic attributes. The ambi
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Huang, Zhili, Qinglan Chen, Liu Chen, and Qinyuan Liu. "Relative Similarity Programming Model for Uncertain Multiple Attribute Decision-Making Objects and Its Application." Mathematical Problems in Engineering 2021 (March 9, 2021): 1–16. http://dx.doi.org/10.1155/2021/6618333.

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This paper is concerned with the uncertain multiattribute decision-making (UMADM) of which the attribute value is triangular fuzzy number. Firstly, the max-relative similarity degree and min-relative similarity degree of alternative decision-making objects are given based on the relative similarity degree of triangular fuzzy number, the advantage relation theories to comparative relative similarity degree of triangular fuzzy number are proposed, and some good properties, relations, and conclusions are derived. Secondly, in order to determine the attribute weight vector, a triangular fuzzy numb
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Paganelli, Federica, and David Parlanti. "A DHT-Based Discovery Service for the Internet of Things." Journal of Computer Networks and Communications 2012 (2012): 1–11. http://dx.doi.org/10.1155/2012/107041.

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Current trends towards the Future Internet are envisaging the conception of novel services endowed with context-aware and autonomic capabilities to improve end users’ quality of life. The Internet of Things paradigm is expected to contribute towards this ambitious vision by proposing models and mechanisms enabling the creation of networks of “smart things” on a large scale. It is widely recognized that efficient mechanisms for discovering available resources and capabilities are required to realize such vision. The contribution of this work consists in a novel discovery service for the Interne
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Riaz, Muhammad, Aurang Zeb, Fawad Ali, Muhammad Naeem, and Sama Arjika. "Fermatean Cubic Fuzzy Aggregation Operators and Their Application in Multiattribute Decision-Making Problems." Journal of Function Spaces 2022 (November 30, 2022): 1–18. http://dx.doi.org/10.1155/2022/3664302.

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The purpose of aggregation methods is to convert a list of objects of a set into a single object of the same set usually by an n -arry function, so-called aggregation operator. The key features of this work are the aggregation operators, because they are based on a novel set called Fermatean cubic fuzzy set (F-CFS). F-CFS has greater spatial scope and can deal with more ambiguous situations where other fuzzy set extensions fail to support them. For this purpose, the notion of F-CFS is defined. F-CFS is the transformation of intuitionistic cubic fuzzy set (I-CFS), Pythagorean cubic fuzzy set (P
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Dissertations / Theses on the topic "Multiattribute object"

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Лютенко, Ірина Вікторівна. "Моделі та інформаційні технології комплексного оцінювання багатоознакових об'єктів в задачах підтримки прийняття рішень". Thesis, НТУ "ХПІ", 2017. http://repository.kpi.kharkov.ua/handle/KhPI-Press/34232.

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Дисертація на здобуття наукового ступеня кандидата технічних наук (доктора філософії) за спеціальністю 05.13.06 "Інформаційні технології" (122 – Комп'ютерні науки). – Національний технічний університет "Харківський політехнічний інститут", Харків, 2017. Об'єкт дослідження – процес комплексного оцінювання багатоознакових об'єктів в задачах підтримки прийняття рішень. Предмет дослідження – моделі, методи та інформаційні технології комплексного оцінювання багатоознакових об'єктів в задачах підтримки прийняття рішень. Дисертацію присвячено вирішенню науково-практичної задачі – розробці моделей та
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Лютенко, Ірина Вікторівна. "Моделі та інформаційні технології комплексного оцінювання багатоознакових об'єктів в задачах підтримки прийняття рішень". Thesis, НТУ "ХПІ", 2018. http://repository.kpi.kharkov.ua/handle/KhPI-Press/34219.

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Дисертація на здобуття наукового ступеня кандидата технічних наук за спеціальністю 05.13.06 – інформаційні технології. – Національний технічний університет "Харківський політехнічний інститут", Харків, 2018. У дисертаційній роботі вирішена актуальна науково-практична задача розробки моделей та інформаційної технології комплексного оцінювання складних об'єктів багатоознакової природи для підвищення обґрунтованості процесу прийняття рішень. Проаналізовано існуючі інформаційні технології, моделі та методи оцінювання складних об'єктів та процесів і сформульовано основні вимоги до розробки інформ
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Conference papers on the topic "Multiattribute object"

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Kovacs, Ilona, Thomas V. Papathomas, and Bela Julesz. "Interaction of color and luminance in stereo perception." In OSA Annual Meeting. Optica Publishing Group, 1991. http://dx.doi.org/10.1364/oam.1991.fm4.

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Although it is well known that stereo perception is seriously impaired at equiluminance,1 the role of color in stereopsis and its interaction with other visual attributes cannot be studied adequately with equiluminant stimuli alone. The interaction of color and luminance signals in the perception of depth is of particular importance. We have developed a technique, based on multiattribute random-dot stereograms,2 which allows us to study such interactions in global stereopsis (see Ref. 3 for a study on the role of color in local stereopsis). Basically, the technique enables one to render a colo
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