Comparison and Classification of Methods for Solving the Monge-Kantorovich Problem

Никифоров, С. А.; Yakupov, Z. Ya

doi:10.24153/2079-5920-2017-7-3-24-27

Cited by 2 publications

(3 citation statements)

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“…After normalization, the error decreases on average by 3% compared with the same model, which was only trained on abnormal data. Similar results were obtained in [24].…”

Section: Discussionsupporting

confidence: 90%

“…In the general case, for processing a sample of input data, we can use the following sequence of stages, which was formed empirically by the authors of this paper, using their own experience in creating neural models [21][22][23][24]:…”

Section: Processing a Sample Of Initial Data For Training A Neural Nementioning

confidence: 99%

“…The presence of conflicting samples in the training set may appear due to random errors or in the case of incorrect statement of the problem. The search for such conflicting samples can be carried out using special algorithms that search for matching training samples [24,31] or by carefully looking at the sample in search of repeated input vectors.…”

Section: Identifying Conflicting Samplesmentioning

confidence: 99%

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The paper presents the results of mathematical simulation of the characteristics of a vane diffuser of a centrifugal compressor intermediate stage, such as the loss coefficient and the deviation angle versus the outlet vane angle of the diffuser. The simulation of these characteristics was made on the basis of processing the results of studies performed by the Research Laboratory “Gas Dynamics of Turbomachines” of Peter the Great St.Petersburg Polytechnic University at the model characteristics of vane diffusers. Given the almost complete absence of recommendations in the literature, the paper describes the technology for constructing neural network models, which includes preparing a sample of input data and determining the optimal structure of the neural network. Based on the obtained mathematical models, a computational experiment was carried out in order to determine the influence of the main geometric and gas-dynamic parameters on the efficiency of vane diffusers. The results of the computational experiment on neural models of the efficiency of a vane diffuser are analyzed according to the existing ideas about the physics of the processes of energy conversion in a vane diffuser.

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“…After normalization, the error decreases on average by 3% compared with the same model, which was only trained on abnormal data. Similar results were obtained in [24].…”

Section: Discussionsupporting

confidence: 90%

Section: Processing a Sample Of Initial Data For Training A Neural Nementioning

confidence: 99%

Section: Identifying Conflicting Samplesmentioning

confidence: 99%

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Simulation of gas-dynamic characteristics of a centrifugal compressor vane diffuser using neural networks

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Modeling of the oil transportation process through pipelines and its optimization according to the cost criterion

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Shavkina

2024

E3S Web Conf.

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This article considers the problem of optimizing the process of oil transportation through oil pipelines from fields to oil collection and delivery points. The aim of the study is to build an effective logistics system for product transportation, which ensures the sustainable functioning of industrial production. The paper presents a mathematical model of the problem that takes into account the productivity of oil-producing enterprises and the needs of oil refineries, and represents a balanced transport problem. The optimization problem is solved on in the Python programming language, using imported libraries and modified program code. As a result of the software solution, the minimum cost of transportation and the optimal oil supply plan are determined, which allows providing all consumers with this energy resource with minimal costs. The proposed software product has a user-friendly and intuitive interface, which makes it accessible to a wide range of users when solving linear programming problems.

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Comparison and Classification of Methods for Solving the Monge-Kantorovich Problem

Cited by 2 publications

References 0 publications

Simulation of gas-dynamic characteristics of a centrifugal compressor vane diffuser using neural networks

Simulation of gas-dynamic characteristics of a centrifugal compressor vane diffuser using neural networks

Modeling of the oil transportation process through pipelines and its optimization according to the cost criterion

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