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Journal articles on the topic 'Network of problem'

Author: Grafiati

Published: 10 March 2023

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1

Nasution, Mahyuddin K. M., Rahmad Syah, and Marischa Elveny. "Social Network Analysis: Towards Complexity Problem." Webology 18, no. 2 (December 23, 2021): 449–61. http://dx.doi.org/10.14704/web/v18i2/web18332.

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Social network analysis is a advances from field of social networks. The structuring of social actors, with data models and involving intelligence abstracted in mathematics, and without analysis it will not present the function of social networks. However, graph theory inherits process and computational procedures for social network analysis, and it proves that social network analysis is mathematical and computational dependent on the degree of nodes in the graph or the degree of social actors in social networks. Of course, the process of acquiring social networks bequeathed the same complexity toward the social network analysis, where the approach has used the social network extraction and formulated its consequences in computing.

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2

Hau, Than Nguyen, Hiroshi Hirai, and Nobuyuki Tsuchimura. "ON HALF-INTEGRALITY OF NETWORK SYNTHESIS PROBLEM." Journal of the Operations Research Society of Japan 57, no. 2 (2014): 63–73. http://dx.doi.org/10.15807/jorsj.57.63.

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3

KAMIMURA, RYOTARO. "MULTI-LAYERED GREEDY NETWORK-GROWING ALGORITHM: EXTENSION OF GREEDY NETWORK-GROWING ALGORITHM TO MULTI-LAYERED NETWORKS." International Journal of Neural Systems 14, no. 01 (February 2004): 9–26. http://dx.doi.org/10.1142/s012906570400184x.

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In this paper, we extend our greedy network-growing algorithm to multi-layered networks. With multi-layered networks, we can solve many complex problems that single-layered networks fail to solve. In addition, the network-growing algorithm is used in conjunction with teacher-directed learning that produces appropriate outputs without computing errors between targets and outputs. Thus, the present algorithm is a very efficient network-growing algorithm. The new algorithm was applied to three problems: the famous vertical-horizontal lines detection problem, a medical data problem and a road classification problem. In all these cases, experimental results confirmed that the method could solve problems that single-layered networks failed to. In addition, information maximization makes it possible to extract salient features in input patterns.

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GU, WEIZHEN, D. FRANK HSU, and XINGDE JIA. "ON A NETWORK SENSING PROBLEM." Journal of Interconnection Networks 07, no. 01 (March 2006): 63–73. http://dx.doi.org/10.1142/s0219265906001582.

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Live traffic flow information can help improve the efficiency of a communication network. There are many ways available to monitor the traffic flow of a network. In this paper, we propose a very efficient monitoring strategy. This strategy not only reduces the number of nodes to be monitored but also determines the complete traffic information of the entire network using the information from the monitored nodes. The strategy is optimal for monitoring a network because it reduces the number of monitored nodes to a minimum. Fast algorithms are also presented in this paper to compute the traffic information for the entire network based on the information collected from the monitored nodes. The monitoring scheme discussed in this paper can be applied to the internet, telecommunication networks, wireless ad hoc networks, large scale multiprocessor computing systems, and other information systems where the transmission of information needs to be monitored.

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GEN, MITSUO, and RUNWEI CHENG. "EVOLUTIONARY NETWORK DESIGN: HYBRID GENETIC ALGORITHMS APPROACH." International Journal of Computational Intelligence and Applications 03, no. 04 (December 2003): 357–80. http://dx.doi.org/10.1142/s1469026803001075.

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In recent years we have evidenced an extensive effort in the development of computer communication networks, which have deeply integrated in human being's everyday life. One of the important aspects of the network design process is the topological design problem involved in establishing a communication network. However, with the increase of the problem scale, the conventional techniques are facing the challenge to effectively and efficiently solve those complicated network design problems. In this article, we give a brief survey on our recent research works of network design problems by using genetic algorithms (GAs), such as, multistage process planning problem, fixed charge transportation problem, minimum spanning tree problem, centralized network design, and local area network design, shortest path problem, minimum cost maximum flow problem, and optimal scheduling problems based on network topology. All these problems are illustrated from the point of genetic representation encoding skill and the genetic operators with hybrid strategies. Numerical experiments show the effectiveness and efficiency of such kind of GA-based approach.

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BONG, NOVI H., JOE RYAN, and KIKI A. SUGENG. "MaxDDBS Problem on Beneš Network." Journal of Interconnection Networks 17, no. 03n04 (September 2017): 1741003. http://dx.doi.org/10.1142/s0219265917410031.

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Maximum degree-diameter bounded subgraph problem is a problem of constructing the largest possible subgraph of given degree and diameter in a graph. This problem can be considered as a degree-diameter problem restricted to certain host graphs. The MaxDDBS problem with Beneš network as the host graph is discussed in this paper. Beneš network contains a back-to-back buttery network. Even though both networks have maximum degree 4, the structure of their maximum subgraphs are different. We give the constructive lower bound of the largest subgraph of Beneš network of various maximum degrees.

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Frantzeskakis, Linos F., and Hanan Luss. "The network redesign problem for access telecommunications networks." Naval Research Logistics 46, no. 5 (August 1999): 487–506. http://dx.doi.org/10.1002/(sici)1520-6750(199908)46:5<487::aid-nav3>3.0.co;2-b.

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WANG, QIN, and LONGSHU WU. "NETWORK DESIGN FOR MINIMUM SPANNING TREES UNDER HAMMING DISTANCE." ANZIAM Journal 58, no. 3-4 (April 2017): 342–49. http://dx.doi.org/10.1017/s1446181117000116.

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We consider a class of network-design problems with minimum sum of modification and network costs for minimum spanning trees under Hamming distance. By constructing three auxiliary networks, we present a strongly polynomial-time algorithm for this problem. The method can be applied to solve many network-design problems. And, we show that a variation model of this problem is NP-hard, even when the underlying network is a tree, by transforming the 0–1 knapsack problem to this model.

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Ahmed, Ayam Tawfeek, Ahmed Noori Rashid, and Khalid Shaker. "Localization in Wireless Sensor Network." Webology 19, no. 1 (January 20, 2022): 692–704. http://dx.doi.org/10.14704/web/v19i1/web19049.

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The major problems in a Wireless Sensor Networks (WSNs) is the localization problem, that relates to how an area covers by the sensor nodes. In this study, the problem formulates as the decision problem, that takes the best location for all sensors in the sensor field. Butterfly Optimization Algorithm (BOA), proposes to calculate the estimate locations for all sensors. Simulating the BOA with using number of sensors from 25 to 150 sensors and number of the anchor nodes. The distance between sensors and anchors measures by Received Signal Strength (RSS) so, this strategy is known as RSS-BOA. The obtained results shed that, the performance of the proposed algorithm is more accurate in comparing with BOA approach in the term sensor's location and the average error.

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Braunstein, Alfredo, Luca Dall’Asta, Guilhem Semerjian, and Lenka Zdeborová. "Network dismantling." Proceedings of the National Academy of Sciences 113, no. 44 (October 18, 2016): 12368–73. http://dx.doi.org/10.1073/pnas.1605083113.

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We study the network dismantling problem, which consists of determining a minimal set of vertices in which removal leaves the network broken into connected components of subextensive size. For a large class of random graphs, this problem is tightly connected to the decycling problem (the removal of vertices, leaving the graph acyclic). Exploiting this connection and recent works on epidemic spreading, we present precise predictions for the minimal size of a dismantling set in a large random graph with a prescribed (light-tailed) degree distribution. Building on the statistical mechanics perspective, we propose a three-stage Min-Sum algorithm for efficiently dismantling networks, including heavy-tailed ones for which the dismantling and decycling problems are not equivalent. We also provide additional insights into the dismantling problem, concluding that it is an intrinsically collective problem and that optimal dismantling sets cannot be viewed as a collection of individually well-performing nodes.

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Curet, Norman D. "The Network Diversion Problem." Military Operations Research 6, no. 2 (March 1, 2001): 35–44. http://dx.doi.org/10.5711/morj.6.2.35.

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12

Gatmiry, Khashayar, and Manuel Gomez-Rodriguez. "The Network Visibility Problem." ACM Transactions on Information Systems 40, no. 2 (April 30, 2022): 1–42. http://dx.doi.org/10.1145/3460475.

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Social media is an attention economy where broadcasters are constantly competing for attention in their followers’ feeds. Broadcasters are likely to elicit greater attention from their followers if their posts remain visible at the top of their followers’ feeds for a longer period of time. However, this depends on the rate at which their followers receive information in their feeds, which in turn depends on the broadcasters they follow. Motivated by this observation and recent calls for fairness of exposure in social networks, in this article, we look at the task of recommending links from the perspective of visibility optimization. Given a set of candidate links provided by a link recommendation algorithm, our goal is to find a subset of those links that would provide the highest visibility to a set of broadcasters. To this end, we first show that this problem reduces to maximizing a nonsubmodular nondecreasing set function under matroid constraints. Then, we show that the set function satisfies a notion of approximate submodularity that allows the standard greedy algorithm to enjoy theoretical guarantees. Experiments on both synthetic and real data gathered from Twitter show that the greedy algorithm is able to consistently outperform several competitive baselines.

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Kutateladze, Rusudan, and Maia Chkheidze. "Conceptual network construction problem." Works of Georgian Technical University, no. 1(515) (March 26, 2020): 24–30. http://dx.doi.org/10.36073/1512-0996-2020-1-24-30.

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14

Sumalee, Agachai, David P. Watling, and Shoichiro Nakayama. "Reliable Network Design Problem." Transportation Research Record: Journal of the Transportation Research Board 1964, no. 1 (January 2006): 81–90. http://dx.doi.org/10.1177/0361198106196400110.

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15

Sun, Zhe, Wen-Long Jin, and ManWo Ng. "Network sensor health problem." Transportation Research Part C: Emerging Technologies 68 (July 2016): 300–310. http://dx.doi.org/10.1016/j.trc.2016.04.015.

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16

Bern, Marshall W., and Ronald L. Graham. "The Shortest-Network Problem." Scientific American 260, no. 1 (January 1989): 84–89. http://dx.doi.org/10.1038/scientificamerican0189-84.

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17

Spitzer, Dean R. "Performance problem solving network." Performance + Instruction 24, no. 9 (November 1985): 24–25. http://dx.doi.org/10.1002/pfi.4150240911.

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18

Stetsyuk, Petro, Oleksii Lykhovyd, Volodymyr Zhydkov, and Anton Suprun. "OPTIMIZATION PROBLEMS OF MODERNIZATION OF THE CAPACITY OF ARCS OF FAULT-TOLERANT NETWORKS." Journal of Automation and Information sciences 5 (September 1, 2021): 5–20. http://dx.doi.org/10.34229/1028-0979-2021-5-1.

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Mathematical models of two classes of problems of modernization of the capacity of arcs of fault-tolerant oriented networks are considered. A network is considered to be fault-tolerant for which it is possible to satisfy all the demands for the transmission of flows when there will be one, but any failure, from all possible single network failures. For the first class of problems (problem A), all possible paths in the network can be used for the transmission of flows. For the second class of problems (problem P), only paths from a predetermined set of paths are used to transfer flows. Mathematical models are represented by linear, Boolean and nonlinear programming problems with a block structure of the constraint matrix.The material of the article is presented in five sections. The first section describes the concepts of a single failure and the scenario of network failures, the content of optimization problems A and P for modernization of capacity of arcs of a fault-tolerant network, a test network (6 vertices and 19 arcs) to test algorithms for solving the problems of modernization of fault-tolerant networks. In the second section, basic models of linear programming problems for finding the capacities of arcs of the fault-tolerant physical structure of a network (problem A) and the fault-tolerant logical structure of a network (problem P) are described, and their properties are considered. The third section describes problems A and P in the form of mixed Boolean linear programming models. Optimal solutions of problem A for various failure scenarios are given for the example of the test network. The solutions were found using the Gurobi program from the NEOS server, where the mathematical model of problem A is described in the AMPL modeling language.The fourth section describes nonlinear convex programming models for problems A and P, developed to find the optimal capacities of fault-tolerant networks according to the selected criterion, and a decomposition algorithm for their solution. The fifth section describes software in the FORTRAN programming language for the decomposition algorithm based on efficient implementations of Shor’s r-algorithms. The decomposition algorithm is compared with the IPOPT program based on the results of solving test problems.

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19

Leung, Henry, and Simon Haykin. "Rational Function Neural Network." Neural Computation 5, no. 6 (November 1993): 928–38. http://dx.doi.org/10.1162/neco.1993.5.6.928.

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In this paper we observe that a particular class of rational function (RF) approximations may be viewed as feedforward networks. Like the radial basis function (RBF) network, the training of the RF network may be performed using a linear adaptive filtering algorithm. We illustrate the application of the RF network by considering two nonlinear signal processing problems. The first problem concerns the one-step prediction of a time series consisting of a pair of complex sinusoid in the presence of colored non-gaussian noise. Simulated data were used for this problem. In the second problem, we use the RF network to build a nonlinear dynamic model of sea clutter (radar backscattering from a sea surface); here, real-life data were used for the study.

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20

WU, LONGSHU, QIN WANG, and XIAOBING YANG. "COMPUTATIONAL METHODS FOR LOGISTICS PROBLEMS RELATED TO OPTIMAL TREES." ANZIAM Journal 58, no. 3-4 (March 7, 2017): 333–41. http://dx.doi.org/10.1017/s1446181117000074.

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In recent years, balanced network optimization problems play an important role in practice, especially in information transmission, industry production and logistics management. In this paper, we consider some logistics optimization problems related to the optimal tree structures in a network. We show that the most optimal subtree problem is NP-hard by transforming the connected dominating set problem into this model. By constructing the network models of the most balanced spanning tree problem with edge set restrictions, and by finding the optimal subtrees in special networks, we present efficient computational methods for solving some logistics problems.

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Zelenina, Larisa I., D. S. Khripunov, Liudmila E. Khaimina, Evgenii S. Khaimin, and Inga M. Zashikhina. "The Problem of Images’ Classification: Neural Networks." Mathematics and Informatics LXIV, no. 3 (June 30, 2021): 289–300. http://dx.doi.org/10.53656/math2021-3-4-the.

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The article discusses the employment of an artificial neural network for the problem of image classification. Based on the compiled dataset, a convolutional neural network model was implemented and trained. An application for images classification was created. The practical value of the developed application allows an efficient use of a smartphone camera’s storage facilities. The article presents a detailed methodology of the application’s development.

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22

Katayama, Naoto. "A Combined Matheuristic for the Piecewise Linear Multicommodity Network Flow Problem." Asia-Pacific Journal of Operational Research 34, no. 06 (December 2017): 1750033. http://dx.doi.org/10.1142/s0217595917500336.

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Multicommodity network problems appear in numerous applications, such as telecommunications, logistics, transportation, distribution and production planning networks. The piecewise linear multicommodity network flow problem is a multicommodity network flow problem with piecewise linear costs corresponding to multiple resources, such as communication lines, vehicles and production lines. In the present paper, for the piecewise linear multicommodity network continuous flow problem, we present a path-based formulation and an arc-based formulation, and develop a combined matheuristic approach, which combines capacity scaling, a column and row generation technique, restricted branch-and-bound and a local branch method.

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23

Kojic, Nenad, Irini Reljin, and Branimir Reljin. "Neural network for optimization of routing in communication networks." Facta universitatis - series: Electronics and Energetics 19, no. 2 (2006): 317–29. http://dx.doi.org/10.2298/fuee0602317k.

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The efficient neural network algorithm for optimization of routing in communication networks is suggested. As it was known from literature different optimization and ill-defined problems may be resolved using appropriately designed neural networks, due to their high computational speed and the possibility of working with uncertain data. Under some assumptions the routing in packet-switched communication networks may be considered as optimization problem, more precisely, as a shortest-path problem. The Hopfield-type neural network is a very efficient tool for solving such problems. The suggested routing algorithm is designed to find the optimal path, meaning, the shortest path (if possible), but taking into account the traffic conditions: the incoming traffic flow, routers occupancy, and link capacities, avoiding the packet loss due to the input buffer overflow. The applicability of the proposed model is demonstrated through computer simulations in different traffic conditions and for different full-connected networks with both symmetrical and non-symmetrical links.

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Sun, K. T., and H. C. Fu. "A NEURAL NETWORK IMPLEMENTATION FOR THE TRAFFIC CONTROL PROBLEM ON CROSSBAR SWITCH NETWORKS." International Journal of Neural Systems 03, no. 02 (January 1992): 209–18. http://dx.doi.org/10.1142/s0129065792000176.

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In this paper, we propose a neural network for the traffic control problem on crossbar switch networks. First, we represent this problem by an energy function, then apply the proposed neural network to update the state of the energy function until a stable state is reached. Within O(n) iteration steps, where n is the size of an n×n network, the energy function reaches a stable state which corresponds to a feasible solution of the traffic control problem. Also, the simulation results show that our neural network generates either optimal or near optimal solutions. Based on our neural network approach, many problems of applying neural networks to optimization problems are overcome, for example, the unpredictable converging time to reach a stable state, the probability of converging to a local minimum which corresponds to an invalid solution and the selecting of proper parameters of an energy function for obtaining a good (near optimal) solution, etc.

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Baher, Nima Tahami, Farzin Taghipourian, and Ehsan Teymourian. "Dynamic Virtual Hub Location Problem." Advanced Materials Research 433-440 (January 2012): 4931–35. http://dx.doi.org/10.4028/www.scientific.net/amr.433-440.4931.

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A controversial issue in the planning of air transportation networks is inclement weather. In this situation, hub facilities would not be able to provide a good service to their spoke nodes temporarily. Thus, some other kinds of predetermined underutilized facilities in the network are used as virtual hubs to host some or all connections of original hubs to recover the incurred incapacitation and increase network flexibility and demand flow.Here, we present a dynamic virtual hub location problem with the aim of minimizing transportation cost in the network. We examine the effectiveness of our model using the US well-known CAB data set.

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Ohta, S. "CNF-SAT modelling for banyan-type networks and its application for assessing the rearrangeability." Journal of Physics: Conference Series 2090, no. 1 (November 1, 2021): 012133. http://dx.doi.org/10.1088/1742-6596/2090/1/012133.

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Abstract A banyan-type network is a switching network, which is constructed by placing unit switches with two inputs and two outputs in s (s > 1) stages. In each stage, 2 n – 1 (n > 1) unit switches are aligned. Past studies conjecture that this network becomes rearrangeable when s ≥ 2n-1. Although a considerable number of theoretical analyses have been done, the rearrangeability of the banyan-type network with 2n – 1 or more stages is not completely proved. As a tool to assess the rearrangeability, this study presents a CNF-SAT (conjunctive normal form - satisfiability) modelling scheme for banyan-type networks. In the proposed scheme, the routing is formulated to a SAT problem represented in CNF. By feeding the problem to a SAT solver, it is found whether the problem is satisfiable or unsatisfiable. If the problem is unsatisfiable for a certain request, the network is not rearrangeable. By contrast, if the problem is satisfiable for any requests, the network is rearrangeable. This study applies the CNF-SAT modelling scheme to various configurations of 2n – 1 stage banyan-type networks. These networks are assessed for rearrangeability by solving the SAT problems. The proposed method will be helpful to conduct future theoretical studies on banyan-type networks.

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Bulygin, M. V., M. M. Gayanova, A. M. Vulfin, A. D. Kirillova, and R. Ch Gayanov. "Convolutional neural network in the images colorization problem." Information Technology and Nanotechnology, no. 2416 (2019): 340–53. http://dx.doi.org/10.18287/1613-0073-2019-2416-340-353.

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Object of the research are modern structures and architectures of neural networks for image processing. Goal of the work is improving the existing image processing algorithms based on the extraction and compression of features using neural networks using the colorization of black and white images as an example. The subject of the work is the algorithms of neural network image processing using heterogeneous convolutional networks in the colorization problem. The analysis of image processing algorithms with the help of neural networks is carried out, the structure of the neural network processing system for image colorization is developed, colorization algorithms are developed and implemented. To analyze the proposed algorithms, a computational experiment was conducted and conclusions were drawn about the advantages and disadvantages of each of the algorithms.

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Fu Jie Tey, Fu Jie Tey, Tin-Yu Wu Fu Jie Tey, Yueh Wu Tin-Yu Wu, and Jiann-Liang Chen Yueh Wu. "Generative Adversarial Network for Simulation of Load Balancing Optimization in Mobile Networks." 網際網路技術學刊 23, no. 2 (March 2022): 297–304. http://dx.doi.org/10.53106/160792642022032302010.

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<p>The commercial operation of 5G networks is almost ready to be launched, but problems related to wireless environment, load balancing for example, remain. Many load balancing methods have been proposed, but they were implemented in simulation environments that greatly differ from 5G networks. Current load balancing algorithms, on the other hand, focus on the selection of appropriate Wi-Fi or macro & small cells for Device to Device (D2D) communications, but Wi-Fi facilities and small cells are not available all the time. For this reason, we propose to use the macro cells that provide large coverage to achieve load balancing. By combing Generative Adversarial Network (GAN) with the ns-3 network simulator, this paper uses neural networks in TensorFlow to optimize load balancing of mobile networks, increase the data throughput and reduce the packet loss rate. In addition, to discuss the load balancing problem, we take the data produced by the ns-3 network simulator as the real data for GAN.</p> <p> </p>

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Armandpour, Mohammadreza, Patrick Ding, Jianhua Huang, and Xia Hu. "Robust Negative Sampling for Network Embedding." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 3191–98. http://dx.doi.org/10.1609/aaai.v33i01.33013191.

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Many recent network embedding algorithms use negative sampling (NS) to approximate a variant of the computationally expensive Skip-Gram neural network architecture (SGA) objective. In this paper, we provide theoretical arguments that reveal how NS can fail to properly estimate the SGA objective, and why it is not a suitable candidate for the network embedding problem as a distinct objective. We show NS can learn undesirable embeddings, as the result of the “Popular Neighbor Problem.” We use the theory to develop a new method “R-NS” that alleviates the problems of NS by using a more intelligent negative sampling scheme and careful penalization of the embeddings. R-NS is scalable to large-scale networks, and we empirically demonstrate the superiority of R-NS over NS for multi-label classification on a variety of real-world networks including social networks and language networks.

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Shushpanov, Ilia, and Konstantin Suslov. "About Flexibility Problem of Distribution Electrical Network." EPJ Web of Conferences 217 (2019): 01014. http://dx.doi.org/10.1051/epjconf/201921701014.

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Global electricity companies have embarked on a transition to digital microprocessor devices. Digitalization penetrates every aspect of power industry, whether it is power generation, transmission or distribution. Being the most widespread, the distribution electrical networks are nevertheless the least digitalized. Some issues about them are still insufficiently studied. These are the collection of necessary information, adaptation methods, and the effect of the unrecognizability of some short circuits. This can be explained by improper placement of devices, which causes lack of data, which, in turn, leads to the failure of relay protection and emergency control systems of distribution electrical networks to provide selectivity. The paper proposes algorithms for placing measuring devices so that the information will be collected properly. Placement of the devices will allow adjusting the operating parameters of the relay protection and emergency control systems depending on changes in external weather conditions and load fluctuations in the network. We propose a technique for control of distribution network, taking into account the type of damage in case of emergency in real time, and a technique for placement of measuring devices and creation of an information communication network.

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K Rakesh, Shanu, Bharat Choudhary, and Rachna Sandhu. "Cooperative Problem Solving in Telecommunication Network." INTERNATIONAL JOURNAL OF MANAGEMENT & INFORMATION TECHNOLOGY 4, no. 3 (July 24, 2013): 388–92. http://dx.doi.org/10.24297/ijmit.v4i3.4548.

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Swarm intelligence, as demonstrated by natural biological swarms, has numerous powerful properties desirable in many engineering systems, such as telecommunication. Communication network management is becoming increasingly difficult due to the increasing size, rapidly changing topology, and complexity of communication networks. This paper describes how biologically-inspired agents can be used to solve control problems in telecommunications. These agents, inspired by the foraging behaviour of ants, exhibit the desirable characteristics of simplicity of action and interaction. The colle ction of agents, or swarm system, deals only with local knowledge and exhibits a form of distributed control with agent communication effected through the environment. In this paper we explore the application of ant-like agents to the problem of routing in telecommunication networks.

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Kusper, Gábor, Csaba Biró, and Benedek Nagy. "Resolvable Networks—A Graphical Tool for Representing and Solving SAT." Mathematics 9, no. 20 (October 15, 2021): 2597. http://dx.doi.org/10.3390/math9202597.

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In this paper, we introduce the notion of resolvable networks. A resolvable network is a digraph of subnetworks, where subnetworks may overlap, and the inner structure of subnetworks are not interesting from the viewpoint of the network. There are two special subnetworks, Source and Sink, with the following properties: there is no incoming edge to Source, and there is no outgoing edge from Sink. Any resolvable network can be represented by a satisfiability problem in Boolean logic (shortly, SAT problem), and any SAT problem can be represented by a resolvable network. Because of that, the resolution operation is valid also for resolvable networks. We can use resolution to find out or refine the inner structure of subnetworks. We give also a pessimistic and an optimistic interpretation of subnetworks. In the pessimistic case, we assume that inside a subnetwork, all communication possibilities are represented as part of the resolvable network. In the optimistic case, we assume that each subnetwork is strongly connected. We show that any SAT problem can be visualized using the pessimistic interpretation. We show that transitivity is very limited in the pessimistic interpretation, and in this case, transitivity corresponds to resolution of clauses. In the optimistic interpretation of subnetworks, we have transitivity without any further condition, but not all SAT problems can be represented in this case; however, any such network can be represented as a SAT problem. The newly introduced graphical concept allows to use terminology and tools from directed graphs in the field of SAT and also to give graphical representations of various concepts of satisfiability problems. A resolvable network is also a suitable data structure to study, for example, wireless sensor networks. The visualization power of resolvable networks is demonstrated on some pigeon hole SAT problems. Another important application field could be modeling the communication network of an information bank. Here, a subnetwork represents a dataset of a user which is secured by a proxy. Any communication should be done through the proxy, and this constraint can be checked using our model.

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Hu, Xinxin, Haotian Chen, Hongchang Chen, Xing Li, Junjie Zhang, and Shuxin Liu. "Mining Mobile Network Fraudsters with Augmented Graph Neural Networks." Entropy 25, no. 1 (January 11, 2023): 150. http://dx.doi.org/10.3390/e25010150.

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With the rapid evolution of mobile communication networks, the number of subscribers and their communication practices is increasing dramatically worldwide. However, fraudsters are also sniffing out the benefits. Detecting fraudsters from the massive volume of call detail records (CDR) in mobile communication networks has become an important yet challenging topic. Fortunately, Graph neural network (GNN) brings new possibilities for telecom fraud detection. However, the presence of the graph imbalance and GNN oversmoothing problems makes fraudster detection unsatisfactory. To address these problems, we propose a new fraud detector. First, we transform the user features with the help of a multilayer perceptron. Then, a reinforcement learning-based neighbor sampling strategy is designed to balance the number of neighbors of different classes of users. Next, we perform user feature aggregation using GNN. Finally, we innovatively treat the above augmented GNN as weak classifier and integrate multiple weak classifiers using the AdaBoost algorithm. A balanced focal loss function is also used to monitor the model training error. Extensive experiments are conducted on two open real-world telecom fraud datasets, and the results show that the proposed method is significantly effective for the graph imbalance problem and the oversmoothing problem in telecom fraud detection.

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Sangroula, Uchit, Kuk-Heon Han, Kang-Min Koo, Kapil Gnawali, and Kyung-Taek Yum. "Optimization of Water Distribution Networks Using Genetic Algorithm Based SOP–WDN Program." Water 14, no. 6 (March 9, 2022): 851. http://dx.doi.org/10.3390/w14060851.

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Water distribution networks are vital hydraulic infrastructures, essential for providing consumers with sufficient water of appropriate quality. The cost of construction, operation, and maintenance of such networks is extremely large. The problem of optimization of a water distribution network is governed by the type of water distribution network and the size of pipelines placed in the distribution network. This problem of optimal diameter allocation of pipes in a distribution network has been heavily researched over the past few decades. This study describes the development of an algorithm, ‘Smart Optimization Program for Water Distribution Networks’ (SOP–WDN), which applies genetic algorithm to the problem of the least-cost design of water distribution networks. SOP–WDN demonstrates the application of an evolutionary optimization technique, i.e., genetic algorithm, linked with a hydraulic simulation solver EPANET, for the optimal design of water distribution networks. The developed algorithm was applied to three benchmark water distribution network optimization problems and produced consistently good results. SOP–WDN can be utilized as a tool for guiding engineers during the design and rehabilitation of water distribution pipelines.

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Kondo, Nobuhiko, Toshiharu Hatanaka, and Katsuji Uosaki. "RBF Networks Ensemble Construction based on Evolutionary Multi-objective Optimization." Journal of Advanced Computational Intelligence and Intelligent Informatics 12, no. 3 (May 20, 2008): 297–303. http://dx.doi.org/10.20965/jaciii.2008.p0297.

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The ensemble learning has attracted much attention over the last decade. While constructing RBF network ensemble the generally encountered problems are how to construct diverse RBF networks and how to combine outputs. The construction of RBF network can be considered as a multi-objective optimization problem regarding model complexity. A set of RBF networks which is multi-objectively optimized can be obtained by solving the above-mentioned problem. In this paper the construction of RBF networks by evolutionary multi-objective optimization method and its ensemble are considered, and it is applied to the pattern classification problem. Also some ensemble member selection methods and output combination methods are considered. Experimental study on the benchmark problem of pattern classification is carried out; then it is illustrated that the RBF network ensemble has a performance, which is comparable to that of other ensemble methods.

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Sinha, Aman Kumar, and S. P. Varma. "Solving Open Queueing Network Problem." International Journal of Emerging Research in Management and Technology 6, no. 7 (June 29, 2018): 116. http://dx.doi.org/10.23956/ijermt.v6i7.195.

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Queueing networks may be considered as a group of inter-connected nodes (say ) where each node represents a service facility of some kind with servers at the node ( ). We propose to apply 1st the method given by J. R. Jackson and then we would like to solve the same problem by the method of J. D. C. Little.

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Chen, Anthony, Juyoung Kim, Zhong Zhou, and Piya Chootinan. "Alpha Reliable Network Design Problem." Transportation Research Record: Journal of the Transportation Research Board 2029, no. 1 (January 2007): 49–57. http://dx.doi.org/10.3141/2029-06.

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Naiman, S. M., V. B. Medvedev, and N. Z. Mingaleev. "ROAD NETWORK AND WASTE PROBLEM." World of Transport and Transportation 15, no. 3 (June 28, 2017): 182–86. http://dx.doi.org/10.30932/1992-3252-2017-15-3-17.

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[For the English abstract and full text of the article please see the attached PDF-File (English version follows Russian version)].ABSTRACT The authors of the article systematize the processes of waste generation of the motor transport complex throughout the life cycle of the constructed and operated road. At the same time, variants of land, underground and aboveground lines, solid and liquid waste types, as well as factors affecting their quantitative indicators, and the features of the most waste-generating activities related to the road industry are differentiated. Keywords: road network, transport enterprises, construction, reconstruction, operation, waste.

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Kubo, Mikio, and Hiroshi Kasugai. "THE PROBABILISTIC NETWORK DESIGN PROBLEM." Journal of the Operations Research Society of Japan 35, no. 3 (1992): 256–72. http://dx.doi.org/10.15807/jorsj.35.256.

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Waller, S. Travis, and Athanasios K. Ziliaskopoulos. "Stochastic Dynamic Network Design Problem." Transportation Research Record: Journal of the Transportation Research Board 1771, no. 1 (January 2001): 106–13. http://dx.doi.org/10.3141/1771-14.

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Lunday, Brian J., and Hanif D. Sherali. "A Dynamic Network Interdiction Problem." Informatica 21, no. 4 (January 1, 2010): 553–74. http://dx.doi.org/10.15388/informatica.2010.305.

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Kabadi, S. N., J. Yan, D. Du, and K. P. K. Nair. "Integer Exact Network Synthesis Problem." SIAM Journal on Discrete Mathematics 23, no. 1 (January 2009): 136–54. http://dx.doi.org/10.1137/050641776.

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Teo, Chung-Piaw, and Jia Shu. "Warehouse-Retailer Network Design Problem." Operations Research 52, no. 3 (June 2004): 396–408. http://dx.doi.org/10.1287/opre.1030.0096.

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Averbakh, Igor, and Jordi Pereira. "The flowtime network construction problem." IIE Transactions 44, no. 8 (August 2012): 681–94. http://dx.doi.org/10.1080/0740817x.2011.636792.

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Karoonsoontawong, Ampol, and S. Travis Waller. "Dynamic Continuous Network Design Problem." Transportation Research Record: Journal of the Transportation Research Board 1964, no. 1 (January 2006): 104–17. http://dx.doi.org/10.1177/0361198106196400112.

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Shahabi, Mehrdad, and Avinash Unnikrishnan. "Robust hub network design problem." Transportation Research Part E: Logistics and Transportation Review 70 (October 2014): 356–73. http://dx.doi.org/10.1016/j.tre.2014.08.003.

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Current, John R., Charles S. ReVelle, and Jared L. Cohon. "The hierarchical network design problem." European Journal of Operational Research 27, no. 1 (October 1986): 57–66. http://dx.doi.org/10.1016/s0377-2217(86)80007-8.

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Chabrier, Alain, Emilie Danna, Claude Le Pape, and Laurent Perron. "Solving a Network Design Problem." Annals of Operations Research 130, no. 1-4 (August 2004): 217–39. http://dx.doi.org/10.1023/b:anor.0000032577.81139.84.

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Ben-Ayed, Omar. "Parcel distribution network design problem." Operational Research 13, no. 2 (August 3, 2011): 211–32. http://dx.doi.org/10.1007/s12351-011-0118-2.

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Mote, John. "The family constrained network problem." Discrete Applied Mathematics 13, no. 2-3 (March 1986): 249–57. http://dx.doi.org/10.1016/0166-218x(86)90086-7.

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