Decision Rules Construction: Algorithm Based on EAV Model

Żabiński, Krzysztof; Zielosko, Beata

doi:10.3390/e23010014

Cited by 8 publications

(5 citation statements)

References 46 publications

(45 reference statements)

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“…The most part of approaches for construction of decision rules, with the exception of brute force, Boolean reasoning [ 28 ], and dynamic programming [ 6 ], cannot guarantee the construction of optimal rules, i.e., rules with minimum length or maximum support. Consequently, different heuristic approaches have been proposed in the literature [ 26 , 27 , 29 , 30 ]. Among them, greedy algorithms, genetic algorithms, ant colony optimization algorithms, approaches based on a sequential covering procedure, and many others can be mentioned.…”

Section: Background Informationmentioning

confidence: 99%

Selected Data Mining Tools for Data Analysis in Distributed Environment

Moshkov

Zielosko

Tetteh

2022

Entropy

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In this paper, we deal with distributed data represented either as a finite set T of decision tables with equal sets of attributes or a finite set I of information systems with equal sets of attributes. In the former case, we discuss a way to the study decision trees common to all tables from the set T: building a decision table in which the set of decision trees coincides with the set of decision trees common to all tables from T. We show when we can build such a decision table and how to build it in a polynomial time. If we have such a table, we can apply various decision tree learning algorithms to it. We extend the considered approach to the study of test (reducts) and decision rules common to all tables from T. In the latter case, we discuss a way to study the association rules common to all information systems from the set I: building a joint information system for which the set of true association rules that are realizable for a given row ρ and have a given attribute a on the right-hand side coincides with the set of association rules that are true for all information systems from I, have the attribute a on the right-hand side, and are realizable for the row ρ. We then show how to build a joint information system in a polynomial time. When we build such an information system, we can apply various association rule learning algorithms to it.

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Section: Background Informationmentioning

confidence: 99%

Selected Data Mining Tools for Data Analysis in Distributed Environment

Moshkov

Zielosko

Tetteh

2022

Entropy

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“…There is a magnetic automatic stirring rod in the center of the barrel, which can ensure that the sand concentration in the barrel is basically uniform and unchanged during the calibration period. The measurement of sediment content adopts the drying method of water samples [17][18].…”

Section: Selection Of Experimental Equipmentmentioning

confidence: 99%

Sedimentation of Sediment Particles in the Ocean Based on Dynamic Programming Algorithm

2022

FOE

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It is an important subject of sediment production machinery to study the production development process and sediment transport law of cohesive fine-grained sediment flocculation. At present, many scholars have learned how to break out of the water under pressure on the basis of theory and practice, but there are still many unsolved problems. This paper aims to study the sedimentation of sediment particles in the ocean based on a dynamic programming algorithm. In this paper, the microscopic images of flocs are analyzed and studied by using Ipp graphics software and fractal method for the motion of offshore seawater such as beaches. The traditional calculation method is relatively simple to calculate the effective density of flocs. The fractal dimension of flocculation was calculated using the box dimension calculation method of two-dimensional digital images and MATLAB software. The changing laws of effective density, porosity, diameter and fractal dimension of flocs under different sediment content and electrolyte conditions were discussed from the microscopic point of view. From a macroscopic point of view, the flocculation and recrystallization processes of fine-grained viscous powders were experimentally evaluated. If you consider that most natural water contains cations, and cations have a great influence on the flocculation and distribution of fine sediments, for this reason, this paper develops the ion concentration parameter based on the principle of Goncharov, which is suitable for the flocculation rate formula. Experiments have shown that the floc density of different cationic valences changes significantly. There is a transitional stage, called transitional settlement stage.

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“…We have developed this algorithm to reduce the number of attributes under consideration while getting the same level of accuracy. In our previous article [28], we have compared results of our algorithm with the results provided by the use of dynamic programming approach.…”

Section: Eav Based Decision Making Algorithm To Create Knowledge Data...mentioning

confidence: 99%

Machine Vision in Autonomous Vehicles: Designing and Testing the Decision Making Algorithm Based on Entity Attribute Value Model

Shubenkova

Żabiński

2021

The Archives of Automotive Engineering – Archiwum Motoryzacji

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If we speak about the Smart City’s transport system, autonomous vehicles idea is the first thing that comes to mind. Today, it is strongly believed that the autonomous vehicles’ introduction into the traffic will increase the road safety. However, driverless cars are not the solution by itself. The road safety and, accordingly, sustainability will strongly depend on decision making algorithms inbuilt into the control module. Therefore, the goal of our research is to design and test the data mining algorithm based on Entity–Attribute–Value (EAV) model for decision making in the Intelligent System in the fully- or semi-autonomous vehicles. In this article, we describe the methodology to create 3 main modules of the designed Intelligent System: (1) an Object detection module; (2) a Data analysis module; (3) a Knowledge database built on decision rules generated with the help of our data mining algorithm. To build the Decision Table on the base of the real data, we have tested our algorithm on a simple collection of photos from a Polish two-lane road. Generated rules provide comparable classification results to the dynamic programming approach for optimization of decision rules relative to length or support. However, our decision making algorithm thanks to excluding the mistakes made on the object detection stage, works faster than existing ones with the same level of correctness.

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Decision Rules Construction: Algorithm Based on EAV Model

Cited by 8 publications

References 46 publications

Selected Data Mining Tools for Data Analysis in Distributed Environment

Selected Data Mining Tools for Data Analysis in Distributed Environment

Sedimentation of Sediment Particles in the Ocean Based on Dynamic Programming Algorithm

Machine Vision in Autonomous Vehicles: Designing and Testing the Decision Making Algorithm Based on Entity Attribute Value Model

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