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Publications - 6374

Using Tensor-Type Formalism in Causal Networks

Claudiu Radu Pozna Áron Ballagi Radu Emil Precup

Publication Name: Acta Polytechnica Hungarica

Publication Date: 2024-01-01

Volume: 21

Issue: 10

Page Range: 75-91

Description:

The causal network is a possible description of complex phenomena, and several domains, for example, Machine Learning, Social Science, and Artificial Intelligence. Although a successful solution is referred to in this paper, the field inherently faces challenges. Among these, the work identified that the formalism used is time-consuming and difficult to understand. Consequently, the approach proposed in this paper consists in transcribing this formalism in a tensor form. This goal is accomplished in three steps: first common tensor formulas are proposed for direct and inverse models; second these formulas are adapted for the network primitives; in the end the primitive and consequently the formula composition is analysed. To facilitate the understanding of the proposed formalism, the paper describes several examples. This paper is dedicated to Prof. Imre J. Rudas, to celebrate his 75th anniversary.

Open Access: Yes

DOI: 10.12700/APH.21.10.2024.10.5

Preface

Rafal Wisniewski Janusz Kacprzyk Piotr Kulczycki Radko Mesiar Ĺaszĺo T. Ḱoczy

Publication Name: Advances in Intelligent Systems and Computing

Publication Date: 2020-01-01

Volume: 945

Issue: Unknown

Page Range: v-vii

Description:

No description provided

Open Access: Yes

DOI: DOI not available

The Spiral Discovery Network as an Automated General-Purpose Optimization Tool

Adam Csapo

Publication Name: Complexity

Publication Date: 2018-01-01

Volume: 2018

Issue: Unknown

Page Range: Unknown

Description:

The Spiral Discovery Method (SDM) was originally proposed as a cognitive artifact for dealing with black-box models that are dependent on multiple inputs with nonlinear and/or multiplicative interaction effects. Besides directly helping to identify functional patterns in such systems, SDM also simplifies their control through its characteristic spiral structure. In this paper, a neural network-based formulation of SDM is proposed together with a set of automatic update rules that makes it suitable for both semiautomated and automated forms of optimization. The behavior of the generalized SDM model, referred to as the Spiral Discovery Network (SDN), and its applicability to nondifferentiable nonconvex optimization problems are elucidated through simulation. Based on the simulation, the case is made that its applicability would be worth investigating in all areas where the default approach of gradient-based backpropagation is used today.

Open Access: Yes

DOI: 10.1155/2018/1947250

An Efficient Tour Construction Heuristic for Generating the Candidate Set of the Traveling Salesman Problem with Large Sizes

Peter Foldesi Boldizsar Tuu-Szabo Ĺaszĺo T. Ḱoczy

Publication Name: Mathematics

Publication Date: 2024-10-01

Volume: 12

Issue: 19

Page Range: Unknown

Description:

In this paper, we address the challenge of creating candidate sets for large-scale Traveling Salesman Problem (TSP) instances, where choosing a subset of edges is crucial for efficiency. Traditional methods for improving tours, such as local searches and heuristics, depend greatly on the quality of these candidate sets but often struggle in large-scale situations due to insufficient edge coverage or high time complexity. We present a new heuristic based on fuzzy clustering, designed to produce high-quality candidate sets with nearly linear time complexity. Thoroughly tested on benchmark instances, including VLSI and Euclidean types with up to 316,000 nodes, our method consistently outperforms traditional and current leading techniques for large TSPs. Our heuristic’s tours encompass nearly all edges of optimal or best-known solutions, and its candidate sets are significantly smaller than those produced with the POPMUSIC heuristic. This results in faster execution of subsequent improvement methods, such as Helsgaun’s Lin–Kernighan heuristic and evolutionary algorithms. This substantial enhancement in computation time and solution quality establishes our method as a promising approach for effectively solving large-scale TSP instances.

Open Access: Yes

DOI: 10.3390/math12192960

Identification of the nonlinear steering dynamics of an autonomous vehicle

Gábor Rödönyi R. Toth M. Schoukens Péter Korös Dániel Pup Ádám Kisari G. I. Beintema Zsombor Vigh Alexandros Soumelidis József Bokor

Publication Name: IFAC Papersonline

Publication Date: 2021-07-01

Volume: 54

Issue: 7

Page Range: 708-713

Description:

Automated driving applications require accurate vehicle specific models to precisely predict and control the motion dynamics. However, modern vehicles have a wide array of digital and mechatronic components that are difficult to model, manufactures do not disclose all details required for modelling and even existing models of subcomponents require coefficient estimation to match the specific characteristics of each vehicle and their change over time. Hence, it is attractive to use data-driven modelling to capture the relevant vehicle dynamics and synthesise model-based control solutions. In this paper, we address identification of the steering system of an autonomous car based on measured data. We show that the underlying dynamics are highly nonlinear and challenging to be captured, necessitating the use of data-driven methods that fuse the approximation capabilities of learning and the efficiency of dynamic system identification. We demonstrate that such a neural network based subspace-encoder method can successfully capture the underlying dynamics while other methods fall short to provide reliable results.

Open Access: Yes

DOI: 10.1016/j.ifacol.2021.08.444

Creating and using key network-performance indicators to support the design of change of enterprise infocommunication infrastructure

No authors available

Publication Name: Proceedings of the 2012 International Symposium on Performance Evaluation of Computer and Telecommunication Systems, SPECTS'12 - Part of SummerSim 2012 Multiconference

Publication Date: 2012-10-08

Volume:

Issue:

Page Range: Unknown

Description:

Nowadays, an increasing number of organisations have to make decisions about the change and optimization of their enterprise infocommunication infrastructure. The usual approach of performance (using QoS, SLA) is not user (enterprise) centred and complex enough to help ICT (Information and Communication Technology) experts to support management decisions. © 2012 Society for Modeling & Sim.

Open Access: No

DOI: DOI not available

Regression and statistical analysis of heat transfer enhancement in water/ethylene glycol (40/60) base molybdenum carbide (Mo2C) MXene nanofluid using a transient fractional model

Nadeem Ahmad Sheikh Zulkhibri Bin Ismail S. W. Teklu Ilyas Khan Ghada R. Elnaggar

Publication Name: Discover Nano

Publication Date: 2026-12-01

Volume: 21

Issue: 1

Page Range: Unknown

Description:

To investigate the effects of fractional order (), nanoparticle volume fraction (), magnetic field strength (), and Brinkman permeability () on both flow and heat transfer characteristics, a detailed parametric and statistical analysis is conducted. The statistical regression analysis shows that the volume fraction of nanoparticles and temperature have a strong positive correlation (coefficient = 0.94, p = 0.021) indicating that Mo2C MXene is an excellent heat absorption. On the other hand, the fractional parameter α has a strong negative effect on temperature field (coefficient = − 0.086, p < 0.001), which emphasizes its importance in describing the effects of thermal memory. The findings also indicate that, although MXene nanoparticles significantly increase thermal transport, an augmentation in magnetic field strength and Brinkman resistance cause a resistive Lorentz force and frictional drag, respectively, to prevent fluid flow. These results are physically informative about non-Fourier heat transfer in MXene-based nanofluids as well as offer invaluable information to developing high-performance thermal management systems and solar-energy applications.

Open Access: Yes

DOI: 10.1186/s11671-026-04645-z

Investigation of the fault tolerance of the PIM-SM IP multicast routing protocol for IPTV purposes

István Derka Gábor Lencse

Publication Name: Infocommunications Journal

Publication Date: 2013-03-01

Volume: 5

Issue: 1

Page Range: 21-28

Description:

IPTV services should use an IP multicast solution for a network bandwidth efficient delivery of the media contents. PIM-SM is the most commonly used IP multicast routing protocol in IPTV systems. A short introduction to the operation of PIM-SM is given. Its fault tolerance is examined by experimenting on a mesh topology multicast test network built up by XORP routers in a virtualizcd environment. Different fault scenarios are played and different parameters of PIM-SM and OSPF are examined if they influence and how they influence the outage time of an IPTV service. A formal model is given for the service outage time of the IPTV service on the basis of the results of the experiments.

Open Access: Yes

DOI: DOI not available

Evaluating the effectiveness of public finance used for social protection of internally displaced persons

Yuriy Bilan Halyna Mishchuk Natalia Samoliuk Halyna Yurchyk

Publication Name: Public and Municipal Finance

Publication Date: 2025-01-01

Volume: 14

Issue: 1

Page Range: 23-40

Description:

The increasing number of internally displaced persons (IDPs) in wartime Ukraine leads to growing problems in social protection funding. Under these circumstances, the evaluation of the effectiveness of public finance use is of increasing importance. The study aims to evaluate the effectiveness of public finance for internally displaced persons’ social protection, adapting the KPI methodology for analysis on the national level. The effectiveness is considered following the OECD approach as the extent to which the intervention achieved its objectives and results. At macrolevel of research, the integral indicator was developed based on indicators of input (financing of social protection programs), output (involvement of IDPs in social programs), activity (funding per recipient and multiplicative effect in GDP growth), mechanism (administrative costs for achieving results), and control (effectiveness of IDPs’ social protection compared to other demographic groups). Thirty indicators in total were used (e.g., budgetary funding allocated for housing assistance; budget expenditures on staff salaries of the authorities responsible for certain programs; coverage rate of unemployed IDPs receiving vocational training). The essential distance from the maximum level of expected results (1.0) allows concluding the low effectiveness in this area of public finance use: from 0.330 in 2020 to 0.668 in 2023. Gaps are evident in each direction, especially in input performance (the highest value did not exceed 0.370). The best results were achieved in housing funding and employment governance. The proposed approach is useful for analyzing gaps and identifying opportunities to improve the management of other social programs.

Open Access: Yes

DOI: 10.21511/pmf.14(1).2025.03