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Articles de revues sur le sujet « Object decision »

Auteur : Grafiati

Publié le 9 mars 2023

Mis à jour le 31 juillet 2025

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1

Vernon, David, and Toby J. Lloyd-Jones. "The Role of Colour in Implicit and Explicit Memory Performance." Quarterly Journal of Experimental Psychology Section A 56, no. 5 (2003): 779–802. http://dx.doi.org/10.1080/02724980244000684.

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We present two experiments that examine the effects of colour transformation between study and test (from black and white to colour and vice versa, or from incorrectly coloured to correctly coloured and vice versa) on implicit and explicit measures of memory for diagnostically coloured natural objects (e.g., yellow banana). For naming and coloured-object decision (i.e., deciding whether an object is correctly coloured), there were shorter response times to correctly coloured-objects than to black-and-white and incorrectly coloured-objects. Repetition priming was equivalent for the different st

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SIREGAR, ELIDA TUTI. "DECISION SUPPORT SYSTEM FOR AUCTION OBJECT SELECTION WITH THE TOPSIS METHOD." Jurnal Sistem Informasi Kaputama (JSIK ) 4, no. 1 (2020): 1–6. http://dx.doi.org/10.59697/jsik.v4i1.752.

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The object of auction of mortgage rights is an immovable object as a collateral item that is guaranteed by the debtor to the creditor. In the auction process requires an auction object that has the potential to facilitate the execution of the auction object. Potential Auction Object selection will be a solution in determining which objects are more potential to be auctioned and provide space to more easily execute which objects must be done first. However, in selecting an auction object, it will certainly experience difficulties because each debtor has almost the same criteria as location, bui

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Cho, Yongkyun, and Seymour Ginsburg. "Decision problems of object histories." Information and Computation 83, no. 2 (1989): 245–63. http://dx.doi.org/10.1016/0890-5401(89)90060-6.

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Preston, Stephanie D., and Andrew D. MacMillan-Ladd. "Object attachment and decision-making." Current Opinion in Psychology 39 (June 2021): 31–37. http://dx.doi.org/10.1016/j.copsyc.2020.07.019.

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Carlson, Thomas A., J. Brendan Ritchie, Nikolaus Kriegeskorte, Samir Durvasula, and Junsheng Ma. "Reaction Time for Object Categorization Is Predicted by Representational Distance." Journal of Cognitive Neuroscience 26, no. 1 (2014): 132–42. http://dx.doi.org/10.1162/jocn_a_00476.

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How does the brain translate an internal representation of an object into a decision about the object's category? Recent studies have uncovered the structure of object representations in inferior temporal cortex (IT) using multivariate pattern analysis methods. These studies have shown that representations of individual object exemplars in IT occupy distinct locations in a high-dimensional activation space, with object exemplar representations clustering into distinguishable regions based on category (e.g., animate vs. inanimate objects). In this study, we hypothesized that a representational

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Biedrzycki, Jedrzej, and Robert Burduk. "Integration of Decision Trees Using Distance to Centroid and to Decision Boundary." JUCS - Journal of Universal Computer Science 26, no. 6 (2020): 720–33. http://dx.doi.org/10.3897/jucs.2020.038.

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Plethora of ensemble techniques have been implemented and studied in order to achieve better classification results than base classifiers. In this paper an algorithm for integration of decision trees is proposed, which means that homogeneous base classifiers will be used. The novelty of the presented approach is the usage of the simultaneous distance of the object from the decision boundary and the center of mass of objects belonging to one class label in order to determine the score functions of base classifiers. This means that the score function assigned to the class label by each classifie

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Biedrzycki, Jedrzej, and Robert Burduk. "Integration of Decision Trees Using Distance to Centroid and to Decision Boundary." JUCS - Journal of Universal Computer Science 26, no. (6) (2020): 720–33. https://doi.org/10.3897/jucs.2020.038.

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Plethora of ensemble techniques have been implemented and studied in order to achieve better classification results than base classifiers. In this paper an algorithm for integration of decision trees is proposed, which means that homogeneous base classifiers will be used. The novelty of the presented approach is the usage of the simultaneous distance of the object from the decision boundary and the center of mass of objects belonging to one class label in order to determine the score functions of base classifiers. This means that the score function assigned to the class label by each classifie

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Huang, Zhili, Qiang He, Qinglan Chen, and Hongge Yue. "Hamming Similarity Programming Model for Multi-Attribute Decision-Making Objects with Attribute Values as Interval Numbers and Its Application." Symmetry 14, no. 10 (2022): 2203. http://dx.doi.org/10.3390/sym14102203.

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With regard to the interval number-based uncertain multi-attribute decision making problem, in which the attribute weights are unknown and there is no preference on decision-making alternative objects, this paper presents a new decision-making approach. In this method, Hamming distance firstly is used to define the Hamming similarity degree of normative interval numbers, and the Hamming similarity degree of decision-making alternative objects, and then the Hamming similarity superiority relation theory to the comparison of interval numbers is proposed and some relevant results are obtained. Th

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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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Arseniev, Vladimir, and Andrei Yadrenkin. "Selection of a given space object from the multitude observed by a specialized spacecraft." Information and Control Systems, no. 2 (May 11, 2022): 11–19. http://dx.doi.org/10.31799/1684-8853-2022-2-11-19.

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Introduction: For the detection of most dangerous artificial space objects (space junk) in near-earth space, it is planned to use specialized spacecraft equipped with optoelectronic devices. In relation to this a problem arose when selecting the most dangerous object from the observed multitude, based on the measurements of inhomogeneous selective features that characterize these objects. Purpose: To form a composite non-dimensional indicator that depends on the quantity and quality of measurement information about the observed space objects, and that determines the decision rule for selecting

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Hyacenth, Chineke Amaechi. "Optimizing Multiple Object Tracking and Decision making using neuro–fuzzy." International Journal of Trend in Scientific Research and Development Volume-3, Issue-3 (2019): 871–76. http://dx.doi.org/10.31142/ijtsrd23185.

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Chuandong, Gao, Wu Guoxiong, and Liu Guodong. "Highway Disaster Alignment Decision-making Model Under the Fragile Environment Condition in Mountain Area." Open Civil Engineering Journal 9, no. 1 (2015): 115–19. http://dx.doi.org/10.2174/1874149501509010115.

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Highway disaster alignment is a complex multi-object decision-making problem especially under frail environment conditions such as in mountainous areas. In addition, these objects do not have public characteristics. This paper established the multi-object functional decision making model from the topographic, geologic environmental aspect that may grow and become the cause of all kinds of highway disasters. Using the multi-object decision making theory, this model considered the multi-object forthe highway alignment from the qualitative and quantitative aspect, which has an important academic

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Sari, Dola Permata, Marwan Usman, and Rose Rahmidani. "PENGARUH BAURAN PEMASARAN JASA TERHADAP KEPUTUSAN BERKUNJUNG WISATAWAN PADA OBJEK WISATA WATERBOOM DI KOTA SAWAHLUNTO." Jurnal Ecogen 1, no. 4 (2018): 123. http://dx.doi.org/10.24036/jmpe.v1i1.4731.

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The purpose of this research is to know the influence of product, price, promotion, place, physical evidence, employee, process, productivity and quality to decision of tourist visiting at Waterboom tourist object. This type of research is causative. The population in this study is all tourists who visit the tourism object that is Waterboom in Sawahlunto city. The number of research samples was determined based on Cochran formula of 100 people and was chosen by using accidental sampling technique. The data that are used are the primary obtained through the distribution of questionnaires to sel

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Xin, Xianwei, Jihua Song, and Weiming Peng. "Intuitionistic Fuzzy Three-Way Decision Model Based on the Three-Way Granular Computing Method." Symmetry 12, no. 7 (2020): 1068. http://dx.doi.org/10.3390/sym12071068.

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Three-way decisions, as a general model for uncertain information processing and decisions, mainly utilize the threshold generated by the decision cost matrix to determine the decision category of the object. However, the determination of the threshold is usually accompanied by varying degrees of subjectivity. In addition, the potential symmetrical relationship between the advantages and disadvantages of the decision cost is also a problem worthy of attention. In this study, we propose a novel intuitionistic fuzzy three-way decision (IFTWD) model based on a three-way granular computing method.

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Liu, Yue, Yang Xiao, Tieshan Li, and Yunjie Jia. "A Three-Way Acceleration Approach for Interval-Valued Multi-Attribute Decision-Making Problems." Applied Sciences 13, no. 13 (2023): 7879. http://dx.doi.org/10.3390/app13137879.

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As an essential part of modern intelligent decision-making science, multi-attribute decision-making problems can effectively select and rank all candidate schemes under multiple indicators. Because of the complexity of the real environment and the uncertainty of the decision-making problem, interval numbers are often used to represent the evaluation information of the object. The existing methods of the multi-attribute decision-making problems rarely use the object set but give the decision results by selection or ranking, which often have strong subjectivity. We propose a ranking method from

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Lee, Sujin, Sang-hyo Park, and Dongsan Jun. "Object-Cooperated Ternary Tree Partitioning Decision Method for Versatile Video Coding." Sensors 22, no. 17 (2022): 6328. http://dx.doi.org/10.3390/s22176328.

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In this paper, we propose an object-cooperated decision method for efficient ternary tree (TT) partitioning that reduces the encoding complexity of versatile video coding (VVC). In most previous studies, the VVC complexity was reduced using decision schemes based on the encoding context, which do not apply object detecion models. We assume that high-level objects are important for deciding whether complex TT partitioning is required because they can provide hints on the characteristics of a video. Herein, we apply an object detection model that discovers and extracts the high-level object feat

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Chineke, Amaechi Hyacenth. "Optimizing Multiple Object Tracking and Decision making using neuro-fuzzy." International Journal of Trend in Scientific Research and Development 3, no. 3 (2019): 871–76. https://doi.org/10.31142/ijtsrd23185.

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The problem of not tracking stolen items and some products that are not of quality standard in our companies and industries has liquidated some companies in our country. It has also made some of our graduates not to be employed. The tracking of a single object is difficult let alone tracking multiple object. This problem has arisen because intelligent agent was not incorporated in the design to enhance the efficiency of tracking multiple objects. This can be overcome by using Optimizing multiple object tracking and decision making using neuro -fuzzy. This is done by optimizing the parametric t

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Limbongan, Mey Enggane. "PENGARUH PELAYANAN, FASILITAS DAN DAYA TARIK WISATA TERHADAP KEPUTUSAN BERKUNJUNG (STUDI PADA PENGUNJUNG OBJEK WISATA SA’PAK BAYO BAYO)." JSSHA ADPERTISI JOURNAL 2, no. 1 (2023): 50–55. http://dx.doi.org/10.62728/jsshha.v2i1.422.

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This study aims to find out the effect of service, facility and tourist attraction on visit decision to visit Sa’pak Bayo Bayo Tourism Object in Sangalla, Tana Toraja. The result of t-test show that service variable does not have a significant effect on decision to visiting the tourism object. Otherwise, facilities and tourist attraction variables partially had a positive and significant effect on visit decision. The result of F-test show that all the independent variable simultaneously have a positive and significant effect on visit decision. The results of this study can be used by tourism o

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Soldan, Anja, H. John Hilton, and Yaakov Stern. "Bias effects in the possible/impossible object decision test with matching objects." Memory & Cognition 37, no. 2 (2009): 235–47. http://dx.doi.org/10.3758/mc.37.2.235.

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Sadeghnejad, Naser, Mehdi Ezoji, Reza Ebrahimpour, Mohamad Qodosi, and Sajjad Zabbah. "A fully spiking coupled model of a deep neural network and a recurrent attractor explains dynamics of decision making in an object recognition task." Journal of Neural Engineering 21, no. 2 (2024): 026011. http://dx.doi.org/10.1088/1741-2552/ad2d30.

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Abstract Objective. Object recognition and making a choice regarding the recognized object is pivotal for most animals. This process in the brain contains information representation and decision making steps which both take different amount of times for different objects. While dynamics of object recognition and decision making are usually ignored in object recognition models, here we proposed a fully spiking hierarchical model, explaining the process of object recognition from information representation to making decision. Approach. Coupling a deep neural network and a recurrent attractor bas

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Peralta, Billy, and Luis Alberto Caro. "Improved Object Recognition with Decision Trees Using Subspace Clustering." Journal of Advanced Computational Intelligence and Intelligent Informatics 20, no. 1 (2016): 41–48. http://dx.doi.org/10.20965/jaciii.2016.p0041.

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Generic object recognition algorithms usually require complex classificationmodels because of intrinsic difficulties arising from problems such as changes in pose, lighting conditions, or partial occlusions. Decision trees present an inexpensive alternative for classification tasks and offer the advantage of being simple to understand. On the other hand, a common scheme for object recognition is given by the appearances of visual words, also known as the bag-of-words method. Although multiple co-occurrences of visual words are more informative regarding visual classes, a comprehensive evaluati

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Inuiguchi, Masahiro, and Keisuke Washimi. "Improving Rough Set Rule-Based Classification by Supplementary Rules." Journal of Advanced Computational Intelligence and Intelligent Informatics 19, no. 6 (2015): 747–58. http://dx.doi.org/10.20965/jaciii.2015.p0747.

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In rough set approaches, decision rules are induced from a given data set consisting of attribute values and a decision value. Induced rules are used to classify new objects, but this classification is not perfect, perhaps because the given data set does not include all possible patterns. No induced decision rules are matched totally for objects having missing patterns, and partially matched decision rules are used to estimate their classes. The classification accuracy of such an object is usually lower than that of an object totally matching decision rules. To improve the classification accur

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Syambas, Nana Rachmana. "An Approach for Predicting the Shape and Size of a Buried Basic Object on Surface Ground Penetrating Radar System." International Journal of Antennas and Propagation 2012 (2012): 1–13. http://dx.doi.org/10.1155/2012/919741.

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Surface ground-penetrating radar (GPR) is one of the radar technology that is widely used in many applications. It is nondestructive remote sensing method to detect underground buried objects. However, the output target is only hyperbolic representation. This research develops a system to identify a buried object on surface GPR based on decision tree method. GPR data of many basic objects (with circular, triangular, and rectangular cross-section) are classified and extracted to generate data training model as a unique template for each type of basic object. The pattern of object under test wil

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Jambunanda, Ahmad Jamaludin, Efa Laela Fakhriah, Renny Supriyatni, and Anita Afriana. "Marriage Law in Religious Court: Regulation and Decision on Marital Property in Sustainable Legal Development." Journal of Law and Sustainable Development 11, no. 10 (2023): e1759. http://dx.doi.org/10.55908/sdgs.v11i10.1759.

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Objective: The issue of divorce cases in family court has implications, resulting in the division of marital property. The object of the dispute is the house that wants to be divided equally. The case was in court decision No.205/Pdt.G/2016/PA.Ab for first instance, until the appeal process No.01/Pdt.G/2017/PTA.Ab second instance, and Supreme Court No.159K/Ag./2018 third instance and final decision at fourth instance namely review No.6PK/Ag./2019. The difference from all court decisions in the same case is due to avoid discrimination on children's rights.  Methods: Qualitative rese

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Mitchell, Jennifer A., and David W. Biers. "Decision Statistic Mapping and Number of Information Dimensions on Decision Making with Graphical Displays." Proceedings of the Human Factors Society Annual Meeting 36, no. 18 (1992): 1503–7. http://dx.doi.org/10.1177/154193129203601830.

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This study sought to: (1) analytically separate the components of a graphical display which contributed to performance on integrated and separable tasks; and (2) determine the effect of the number of dimensions of information which had to be integrated. To that end, the study employed a 7 × 3 mixed design with seven displays manipulated between-subjects and the number of information dimensions (three, six, and nine) manipulated within-subjects. The seven displays examined included two bar graphs (non-object and object formats), two midline displays (non-object and object formats), a direct gra

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Kaiyu, Fu. "Legal Object Control of Major Administrative Decisions." Economics, Law and Policy 7, no. 1 (2024): p87. http://dx.doi.org/10.22158/elp.v7n1p87.

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Major administrative decisions have the characteristics of wide scope of influence and long duration. Since the promulgation of the Interim Regulations on the Procedure of Major Administrative Decisions, the situation that decisions cannot be depended on has been initially solved. However, there are still certain difficulties regarding the object of the legal relationship of major administrative decisions. The scope of major administrative decisions is ambiguous, and the dynamic object is dominated by the participation of the public and experts, which cannot guarantee the scientific and democr

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Mezei, Ady-Daniel, Levente Tamás, and Lucian Buşoniu. "Sorting Objects from a Conveyor Belt Using POMDPs with Multiple-Object Observations and Information-Gain Rewards." Sensors 20, no. 9 (2020): 2481. http://dx.doi.org/10.3390/s20092481.

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We consider a robot that must sort objects transported by a conveyor belt into different classes. Multiple observations must be performed before taking a decision on the class of each object, because the imperfect sensing sometimes detects the incorrect object class. The objective is to sort the sequence of objects in a minimal number of observation and decision steps. We describe this task in the framework of partially observable Markov decision processes, and we propose a reward function that explicitly takes into account the information gain of the viewpoint selection actions applied. The D

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Marcus, B. "Joyce: an object-oriented decision tree builder." ACM SIGPLAN Notices 24, no. 5 (1989): 121–23. http://dx.doi.org/10.1145/66068.66081.

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Randolph, Bonnie J., and Barbara Winstead. "Sexual decision making and object relations theory." Archives of Sexual Behavior 17, no. 5 (1988): 389–409. http://dx.doi.org/10.1007/bf01542480.

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Sun, Jun. "Study on Mobile Object Tracking and Intercept Technology Research." Applied Mechanics and Materials 686 (October 2014): 241–45. http://dx.doi.org/10.4028/www.scientific.net/amm.686.241.

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Background difference method [1] is one of the effective paths of improving robot’s vision reaction ability, and robots use background difference method to find the moving object in vision range and conduct tracking monitoring of moving objects. Then it uses support vector to conduct learning fitting of moving object, which can effectively predict the moving trend of moving object, and then it fabricates corresponding decision programs to conduct intercept capture of moving objects.

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Wang, Hongkai, Yanyong Guan, Jilin Huang, and Jianting Shen. "Decision Rules Acquisition for Inconsistent Disjunctive Set-Valued Ordered Decision Information Systems." Mathematical Problems in Engineering 2015 (2015): 1–8. http://dx.doi.org/10.1155/2015/936340.

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Set-valued information system is an important formal framework for the development of decision support systems. We focus on the decision rules acquisition for the inconsistent disjunctive set-valued ordered decision information system in this paper. In order to derive optimal decision rules for an inconsistent disjunctive set-valued ordered decision information system, we define the concept of reduct of an object. By constructing the dominance discernibility function for an object, we compute reducts of the object via utilizing Boolean reasoning techniques, and then the corresponding optimal d

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Glukhikh, Igor N., and Dmitry V. Nikiforov. "Decision making for modeling of oil and gas fields by using case based reasoning." Tyumen State University Herald. Physical and Mathematical Modeling. Oil, Gas, Energy 5, no. 3 (2019): 147–63. http://dx.doi.org/10.21684/2411-7978-2019-5-3-147-163.

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This article describes a case-based reasoning (CBR) method as a decision-making tool in modeling oil and gas fields, its existing and potential application in the industry. The main direction for the application of the CBR method is the search for analogous objects for the design of oil and gas field development. The current engineering practice involves a vaguely formalized method of analogies, which does not allow defining the object as much as possible authentically the analogue that does not cause errors. The analogue object serves not only as a source of ready-made near optimal design sol

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Rosburg, Timm, Axel Mecklinger, and Christian Frings. "When the Brain Decides." Psychological Science 22, no. 12 (2011): 1527–34. http://dx.doi.org/10.1177/0956797611417454.

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Humans can make fast and highly efficient decisions by using simple heuristics that are assumed to exploit basic cognitive functions. In the study reported here, we used event-related potentials (ERPs) to disclose the psychological mechanisms underlying one of the most frugal decision rules, namely, the recognition heuristic. According to this heuristic, whenever two objects have to be ranked by a specific criterion and only one object is recognized, the recognized object is ranked higher than the unrecognized object. Using a standard recognition-heuristic paradigm, we predicted participants’

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Tran, ThanhHuyen, and Le Ba Dung. "A method for incremental updating three-way decision with incomplete information system." Journal of Military Science and Technology, no. 83 (November 18, 2022): 59–71. http://dx.doi.org/10.54939/1859-1043.j.mst.83.2022.59-71.

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In recent years, the three-way decisions theory has been developed in both theoretical and practical applications. In fact, data are often incomplete and often change over time. To solve this problem, a method of updating the three-way decisions in the dynamic incomplete information system is proposed. First, we consider the relationship between the change of conditional probabilities for the change of the three regions. Then, we consider the change of conditional probability when objects and attribute values of the object change. From that change, we propose a method for updating three-way de

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Chacón-Gómez, Fernando, M. Eugenia Cornejo, and Jesús Medina. "Decision Making in Fuzzy Rough Set Theory." Mathematics 11, no. 19 (2023): 4187. http://dx.doi.org/10.3390/math11194187.

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Decision rules are powerful tools to manage information and to provide descriptions of data sets; as a consequence, they can acquire a useful role in decision-making processes where fuzzy rough set theory is applied. This paper focuses on the study of different methods to classify new objects, which are not considered in the starting data set, in order to determine the best possible decision for them. The classification methods are supported by the relevance indicators associated with decision rules, such as support, certainty, and credibility. Specifically, the first one is based on how the n

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Aleksandrov, I. V., R. M. Vivchar, and R. V. Kirichek. "Decision Functions Model for Metric Methods of Pattern Recognition." Proceedings of Telecommunication Universities 11, no. 2 (2025): 84–100. https://doi.org/10.31854/1813-324x-2025-11-2-84-100.

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Currently, data mining based on machine learning plays a key role in decision support in various industries. An important practical problem of machine learning is the implementation of object classification in real time, which can be achieved by parallelizing data processing algorithms both for input data and for decision function data. To improve the efficiency of parallelizing machine learning methods, a unified decision function model has been developed. The Relevance of this research is to present a unified decision function model in the framework of machine learning algorithms and functio

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Wang, Jing, and Kehan Chen. "Classification of ancient glassware based on K-means and decision trees." Highlights in Science, Engineering and Technology 58 (July 12, 2023): 94–104. http://dx.doi.org/10.54097/hset.v58i.10033.

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In this paper, the relation between the chemical composition of different types of glass objects was analyzed, and the differences between the chemical compositions were used to classify the glass objects, mainly by K-means, decision tree, and Euclidean distance analysis. For the classification of glass artifacts, this article analyzed the chemical composition of different types of glass artifacts and the changes of chemical composition before and after weathering, and then obtained the differences of chemical composition of different types of glass artifacts to obtain the classification law.

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Zhu, Hao Dong, and Hong Chan Li. "Attribute Reduction Algorithm for Fuzzy Decision Table with Membership Degrees and Weights." Applied Mechanics and Materials 198-199 (September 2012): 1367–71. http://dx.doi.org/10.4028/www.scientific.net/amm.198-199.1367.

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The classical rough set can not show the fuzziness and the importance of objects in decision procedure because it uses definite form to express each object. In order to solve this problem, this paper firstly introduces a special decision table in which each object has a membership degree to show its fuzziness and has been assigned a weight to show its importance in decision procedure. And then, the special decision table is studied and the relevant rough set model is provided. In the meantime, relevant definitions and theorems are proposed. On the above basis, an attribute reduction algorithm

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Hoseini, Pourya, Janelle Blankenburg, Mircea Nicolescu, Monica Nicolescu, and David Feil-Seifer. "Active Eye-in-Hand Data Management to Improve the Robotic Object Detection Performance." Computers 8, no. 4 (2019): 71. http://dx.doi.org/10.3390/computers8040071.

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Adding to the number of sources of sensory information can be efficacious in enhancing the object detection capability of robots. In the realm of vision-based object detection, in addition to improving the general detection performance, observing objects of interest from different points of view can be central to handling occlusions. In this paper, a robotic vision system is proposed that constantly uses a 3D camera, while actively switching to make use of a second RGB camera in cases where it is necessary. The proposed system detects objects in the view seen by the 3D camera, which is mounted

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Ravinder M., Arunima Jaiswal, and Shivani Gulati. "Deep Learning-Based Object Detection in Diverse Weather Conditions." International Journal of Intelligent Information Technologies 18, no. 1 (2022): 1–14. http://dx.doi.org/10.4018/ijiit.296236.

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The number of different types of composite images has grown very rapidly in current years, making Object Detection, an extremely critical task that requires a deeper understanding of various deep learning strategies that help to detect objects with higher accuracy in less amount of time. A brief description of object detection strategies under various weather conditions is discussed in this paper with their advantages and disadvantages. So, to overcome this transfer learning has been used and implementation has been done with two Pretrained Models i.e., YOLO and Resnet50 with denoising which d

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Chen, Xiaozhi, and Ligeng Zou. "Three-Way Decision Models Based on Ideal Relations in Multi-Attribute Decision-Making." Entropy 24, no. 7 (2022): 986. http://dx.doi.org/10.3390/e24070986.

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In recent years, research on applications of three-way decision (e.g., TWD) has attracted the attention of many scholars. In this paper, we combine TWD with multi-attribute decision-making (MADM). First, we utilize the essential idea of TOPSIS in MADM theory to propose a pair of new ideal relation models based on TWD, namely, the three-way ideal superiority model and the three-way ideal inferiority model. Second, in order to reduce errors caused by the subjectivity of decision-makers, we develop two new methods to calculate the state sets for the two proposed ideal relation models. Third, we e

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R., Ronald R., Zhishuai Yin, Yingzi Lin, and Sagar Kamarthi. "Communications and Decisions of Autonomous Vehicles in Virtual Environments." International Journal of Virtual Reality 9, no. 2 (2010): 53–61. http://dx.doi.org/10.20870/ijvr.2010.9.2.2770.

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In many virtual environments, autonomous objects, such as people and vehicles, are essential to increase the feeling of presence. A goal is to have autonomous objects behave as humans, or in the case of vehicles, as if humans controlled them. Such objects are known as intelligent autonomous objects. We present a combination of a communication model and a decisionmaking model to achieve the goal of modeling autonomous objects that behave intelligently. Both models are attached to autonomous objects that represent people and vehicles in a virtual environment. This enables such an autonomous obje

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Tambuann, Bertua Putra. "Perlindungan Hukum terhadap Kreditur Pasca Putusan Mahkamah Konstitusi Nomor 18/PUU-XVII/2019." Wajah Hukum 8, no. 1 (2024): 187. http://dx.doi.org/10.33087/wjh.v8i1.1396.

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After the Constitutional Court decision Number 18/PUU-XVII/2019, the execution of fiduciary collateral created a sense of injustice and lack of legal certainty for creditors as money lenders. This decision eliminates the Creditor's authority to execute fiduciary collateral objects, as previously stated in article 15 paragraph 3 of the fiduciary law. As a result, the Creditor experienced problems in executing the fiduciary guarantee object after the Debtor failed to fulfil its obligations. The purpose of this writing is to find out what the ideal form of legal protection for Creditors is after

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Li, Jingzheng, Xiangjian Chen, Pingxin Wang, and Xibei Yang. "Local view based cost-sensitive attribute reduction." Filomat 32, no. 5 (2018): 1817–22. http://dx.doi.org/10.2298/fil1805817l.

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In traditional cost-sensitive attribute reduction, the variation of decision cost is referred to as a global difference of costs because the considered decision cost is the variation of sum of decision costs over all objects. However, such reduction does not take the variation of decision costs of each object into account. To solve this problem, a local view based cost-sensitive attribute reduction is introduced. Firstly, through considering the variation of decision costs of single object if the used attributes change, a local difference of costs is presented. Secondly, on the basis of the fu

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Jiang, Ming-xin, Chao Deng, Zhi-geng Pan, Lan-fang Wang, and Xing Sun. "Multiobject Tracking in Videos Based on LSTM and Deep Reinforcement Learning." Complexity 2018 (November 19, 2018): 1–12. http://dx.doi.org/10.1155/2018/4695890.

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Multiple-object tracking is a challenging issue in the computer vision community. In this paper, we propose a multiobject tracking algorithm in videos based on long short-term memory (LSTM) and deep reinforcement learning. Firstly, the multiple objects are detected by the object detector YOLO V2. Secondly, the problem of single-object tracking is considered as a Markov decision process (MDP) since this setting provides a formal strategy to model an agent that makes sequence decisions. The single-object tracker is composed of a network that includes a CNN followed by an LSTM unit. Each tracker,

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Kohut, Yurii, and Iryna Yurchak. "Recommendation System for Purchasing Goods Based on the Decision Tree Algorithm." Advances in Cyber-Physical Systems 6, no. 2 (2021): 121–27. http://dx.doi.org/10.23939/acps2021.02.121.

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Over the past few years, interest in applications related to recommendation systems has increased significantly. Many modern services create recommendation systems that, based on user profile information and his behavior. This services determine which objects or products may be interesting to users. Recommendation systems are a modern tool for understanding customer needs. The main methods of constructing recommendation systems are the content-based filtering method and the collaborative filtering method. This article presents the implementation of these methods based on decision trees. The co

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Shevchenko, Victor Dmitrievich, Anna Alekseevna Khanova, Julia Dmitrievna Shevchenko, and Alexander Aleksandrovich Evstratov. "Conceptual structure of a decision support system for situational video analytics for multi-object recognition." Vestnik of Astrakhan State Technical University. Series: Management, computer science and informatics 2025, no. 1 (2025): 69–79. https://doi.org/10.24143/2072-9502-2025-1-69-79.

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Information is provided on the growing interest in situational video analytics (SVA) technologies in various fields of activity. The paper describes a trend towards the implementation of SVA systems based on cognitive artificial intelligence technologies, which make it possible to detect an object and its location in a video stream in real time with a high degree of accuracy. The architecture of a decision support system (DSS) with the possibility of multi-object recognition is proposed. The key logical components of the DSS in the field of SVA are highlighted, as well as the functions and pur

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Sotnikov, Alexander, Valeriia Tiurina, Konstantin Petrov, et al. "Using the set of informative features of a binding object to construct a decision function by the system of technical vision when localizing mobile robots." Information and controlling system 3, no. 9 (129) (2024): 60–69. http://dx.doi.org/10.15587/1729-4061.2024.303989.

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The object of this study is the process of constructing a decision function by the optical-electronic system of technical vision under the conditions of the influence of obstacles on the current image, which is formed in the process of localization of a mobile robot. The paper reports the results of solving the problem of constructing a decision function when reducing the signal-to-noise ratio of the current image by using a set of informative features for the selection of the binding object, namely, brightness, contrast, and its area. The selection of the binding object is proposed to be carr

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Xu, Xiao Lin, Guang Lin Xu, and Jia Li Feng. "Research on Ranking Model Based on Multi-User Attribute Comprehensive Evaluation Method." Applied Mechanics and Materials 644-650 (September 2014): 2399–402. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.2399.

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In evaluation and decision-making, for an object system with multiple attributes and indicators, it is a typical pattern to calculate an assessment value on each object using some methods to get the ranking of objects, so as to choose the best according to sorting result of the values.The paper establishes the evaluation ranking model on the basis of multi-user attribute comprehensive evaluation method which focuses on how to give a comprehensive evaluation on objects taking the users’ preferences on different attributes in an evaluation group into account,and thereby produce evaluation values

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Paraschiv, S., S. Onoprienko, and I. Spasenko. "As for decision making rules based on research results while forensic science activities." Theory and Practice of Forensic Science and Criminalistics 23, no. 1 (2021): 99–106. http://dx.doi.org/10.32353/khrife.1.2021.07.

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While forensic research, obtained results should be evaluated in order to ensure adoption of correct conclusion regarding the research object. For this purpose forensic experts should use established decision rules to substantiate a statement about conformity of an object or certain requirements, or parameters, or characteristics. Currently, the need to ensure that a decision is made based on results of forensic examination using the concept of decision rules is constantly increasing. Therefore, consideration of the issue of establishing rules for making decisions while forensic science activi

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