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ORCIDVadim V. Romanuke
Person information
- affiliation: Polish Naval Academy, Gdynia, Poland
- affiliation (former): Khmelnitskiy National University, Ukraine
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Journal Articles
- 2024
[j19]Vadim V. Romanuke:
Deep clustering of the traveling salesman problem to parallelize its solution. Comput. Oper. Res. 165: 106548 (2024)- [j18]Vadim V. Romanuke:
Pure strategy solutions of the progressive discrete silent duel with generalized identical quadratic accuracy functions. Discret. Appl. Math. 349: 215-232 (2024) - 2023
- [j17]Vadim V. Romanuke
:
Speedup of the k-Means Algorithm for Partitioning Large Datasets of Flat Points by a Preliminary Partition and Selecting Initial Centroids. Appl. Comput. Syst. 28(1): 1-12 (2023) - [j16]Vadim V. Romanuke:
Parallelization of the Traveling Salesman Problem by Clustering its Nodes and Finding the Best Route Passing through the Centroids. Appl. Comput. Syst. 28(2): 189-202 (2023) - 2022
- [j15]Vadim V. Romanuke:
Finite uniform approximation of two-person games defined on a product of staircase-function infinite spaces. Int. J. Approx. Reason. 145: 139-162 (2022) - [j14]Vadim V. Romanuke:
A Hyper-Heuristic for the Preemptive Single Machine Scheduling Problem to Minimize the Total Weighted Tardiness. Appl. Comput. Syst. 27(1): 1-12 (2022) - [j13]Vadim V. Romanuke:
Nine-Point Iterated Rectangle Dichotomy for Finding All Local Minima of Unknown Bounded Surface. Appl. Comput. Syst. 27(2): 89-100 (2022) - 2021
- [j12]Boris Goldengorin, Vadim V. Romanuke:
Online heuristic for the preemptive single machine scheduling problem to minimize the total weighted tardiness. Comput. Ind. Eng. 155: 107090 (2021) - [j11]Boris Goldengorin, Vadim V. Romanuke:
Experimental analysis of tardiness in preemptive single machine scheduling. Expert Syst. Appl. 186: 114947 (2021) - [j10]Vadim V. Romanuke:
Time Series Smoothing Improving Forecasting. Appl. Comput. Syst. 26(1): 60-70 (2021) - 2020
- [j9]Vadim V. Romanuke:
A Prototype Model for Semantic Segmentation of Curvilinear Meandering Regions by Deconvolutional Neural Networks. Appl. Comput. Syst. 25(1): 62-69 (2020) - 2019
- [j8]Vadim V. Romanuke:
An Improvement of the VDSR Network for Single Image Super-Resolution by Truncation and Adjustment of the Learning Rate Parameters. Appl. Comput. Syst. 24(1): 61-68 (2019) - [j7]Vadim V. Romanuke:
Minimal Total Weighted Tardiness in Tight-Tardy Single Machine Preemptive Idling-Free Scheduling. Appl. Comput. Syst. 24(2): 150-160 (2019) - 2018
- [j6]Vadim V. Romanuke:
Smooth Non-increasing Square Spatial Extents of Filters in Convolutional Layers of CNNs for Image Classification Problems. Appl. Comput. Syst. 23(1): 52-62 (2018) - [j5]Vadim V. Romanuke:
An Efficient Technique for Size Reduction of Convolutional Neural Networks after Transfer Learning for Scene Recognition Tasks. Appl. Comput. Syst. 23(2): 141-149 (2018) - 2017
- [j4]Vadim V. Romanuke:
Appropriateness of Dropout Layers and Allocation of Their 0.5 Rates across Convolutional Neural Networks for CIFAR-10, EEACL26, and NORB Datasets. Appl. Comput. Syst. 22(1): 54-63 (2017) - 2016
- [j3]Vadim V. Romanuke:
Optimal Pixel-to-Shift Standard Deviation Ratio for Training 2-Layer Perceptron on Shifted 60 × 80 Images with Pixel Distortion in Classifying Shifting-Distorted Objects. Appl. Comput. Syst. 19(1): 61 (2016) - [j2]Vadim V. Romanuke, Vladimir V. Kamburg:
Approximation of Isomorphic Infinite Two-Person Non-Cooperative Games by Variously Sampling the Players' Payoff Functions and Reshaping Payoff Matrices into Bimatrix Game. Appl. Comput. Syst. 20(1): 5 (2016) - 2013
- [j1]Vadim V. Romanuke:
Setting the Hidden Layer Neuron Number in Feedforward Neural Network for an Image Recognition Problem under Gaussian Noise of Distortion. Comput. Inf. Sci. 6(2): 38-54 (2013)
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