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Journal articles on the topic 'Optimization of network'

Author: Grafiati

Published: 5 June 2025

Last updated: 16 July 2025

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1

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 (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 provi

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Han Zengfu, Kong Jiankun, Wang Zhiguo, et al. "AI-based network topology optimization system." ITU Journal on Future and Evolving Technologies 2, no. 4 (2021): 81–90. http://dx.doi.org/10.52953/yxtb5085.

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Existing network topology planning does not fully consider the increasing network traffic and problem of uneven link capacity utilization, resulting in lower resource utilization and unnecessary investments in network construction. The AI-based network topology optimization system introduced in this paper builds a Long Short-Term Memory (LSTM) model for time series traffic forecasting, which uses NetworkX, a Python library, for graph analysis, dynamically optimizes the network topology by edge deletion or addition based on traffic over nodes, and ensures network load balancing when node traffi

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Le, Hoang Nghia. "FTTH Network Optimization." Journal of Telecommunications and Information Technology, no. 4 (December 30, 2014): 88–99. http://dx.doi.org/10.26636/jtit.2014.4.1051.

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Fiber To The Home (FTTH) is the most ambitious among optical technologies applied in the access segment of telecommunications networks. The main issues of deploying FTTH are the device price and the installation cost. Whilst the costs of optical devices are gradually decreasing, the cost of optical cable installation remains challenging. In this paper, the problem of optimization that has practical application for FTTH networks is presented. Because the problem is Non-deterministic polynomial-time hard (NP-hard), an approximation algorithm to solve it is proposed. The author has developed the

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S V, Gumaste, Kharat M U, and V. M Thakare. "Network Optimization (Mobile Backbone) - MILP Approach." International Journal of Scientific Engineering and Research 1, no. 1 (2013): 84–88. https://doi.org/10.70729/1130921.

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Ganie, Aadil Gani. "Private network optimization." Multidiszciplináris tudományok 11, no. 4 (2021): 248–54. http://dx.doi.org/10.35925/j.multi.2021.4.29.

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The main challenging task in laying a network is not to define its topology but to calculate its cost-benefit analysis, which is a research-oriented work. In any network, be it intra or internetwork, the main focus is always on optimizing cost and bandwidth. PSWAN is a medium-sized network at the Directorate of information technology India; this networking project provides internet services to many governmental and private offices. Optimization was required as the number of devices connected to this network was more. Two parameters that were optimized are 1. Bandwidth, and 2. Cost. Cost optimi

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Todd, Brody, Abiose Ibigbami, and John Doucette. "Survivable Network Design and Optimization with Network Families." Journal of Computer Networks and Communications 2014 (2014): 1–12. http://dx.doi.org/10.1155/2014/940130.

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In modeling communication networks for simulation of survivability schemes, one goal is often to implement these schemes across varying degrees of nodal connectivity to get unbiased performance results. Abstractions of real networks, simple random networks, and families of networks are the most common categories of these sample networks. This paper looks at how using the network family concept provides a solid unbiased foundation to compare different network protection models. The network family provides an advantage over random networks by requiring one solution per average nodal degree, as o

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Susanta Kumar Sahoo. "Optimizing Graph Theory Algorithms for Social Network Analysis." Communications on Applied Nonlinear Analysis 31, no. 4s (2024): 164–81. http://dx.doi.org/10.52783/cana.v31.834.

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Social network analysis (SNA) leverages graph theory to understand and visualize the complex relationships and structures within social networks. This research paper explores the optimization of graph theory algorithms tailored for SNA, focusing on efficiency improvements in handling large-scale networks. The study reviews key graph theory concepts, identifies common challenges in SNA, and evaluates various optimization techniques. Practical applications and case studies are presented to demonstrate the impact of these optimizations in real-world scenarios.

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Đokić, Dragana, and Vladimir Đokić. "High Performance Network Optimization." Journal of UUNT: Informatics and Computer Sciences 2, no. 1 (2025): 9. https://doi.org/10.62907/juuntics250201009d.

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The term “big data” was coined to describe the vast amounts of information science and technology data that have been generated on a large scale over time. Based on existing research, the current state of the problem was observed, i.e. “Poor internet speed, network downtime, constant traffic jams, energy consumption due to increasing internet connectivity, which increases management overhead costs, network unavailability”. Therefore, this research provides a brief overview of the list of bandwidth optimization models applied through previous research works, indicating the optimal algorithms th

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Yang, Jing. "Optimization of Logistics Distribution Network based on Ant Colony Optimization Neural Network Algorithm." Scalable Computing: Practice and Experience 25, no. 5 (2024): 3641–50. http://dx.doi.org/10.12694/scpe.v25i5.3203.

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In order to improve the timeliness of logistics distribution, based on the theory of road network smoothness and reliability, the author conducted a study on the optimization of urban logistics distribution and transportation networks based on smoothness and reliability. The concept of logistics distribution and transportation network smoothness and reliability was proposed, and a logistics distribution and transportation network optimization model was established. The solving process of ant colony algorithm was given, and finally, a comparative analysis of a case was conducted. The results sh

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Hinding, Nurdin, Amir Kamal Amir, Jusmawati Massalesse, et al. "Determination of the Grid-Shaped Transportation Network's Optimization Value via Graph Labelling." Journal of Advanced Research in Applied Sciences and Engineering Technology 57, no. 2 (2024): 96–105. https://doi.org/10.37934/araset.57.2.96105.

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In order to move people, commodities, and services in an efficient and effective manner, transportation networks are essential. To increase these networks' efficiency and save expenses, they must be optimised. In this research, we offer a unique method that makes use of graph labelling techniques to determine the optimization value of a transportation network. The goal is to give the network's constituent parts labels that accurately represent their potential for optimisations. We start by creating a graph model of the transportation network, with vertices standing in for important places and

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VASYLKIVSKYI, Mikola, Andrii PRYKMETA, Andrii OLIYNYK, and Diana NIKITOVYCH. "OPTIMIZATION OF INTELLIGENT TELECOMMUNICATION NETWORKS." Herald of Khmelnytskyi National University. Technical sciences 217, no. 1 (2023): 33–41. http://dx.doi.org/10.31891/2307-5732-2023-317-1-33-41.

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The paper presents the results of research on the use of machine learning in telecommunication networks and describes the basics of the theory of artificial intelligence. The impact of dynamic Bayesian network (DBN) and DNN on the development of many technologies, including user activity detection, channel estimation, and mobility tracking, is determined. The indicators of the effectiveness of communications based on the theory of information bottlenecks, which is at the junction of machine learning and forecasting, statistics and information theory, are considered. A neural network model that

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Semenov, E. S., M. S. Deogenov, S. V. Galich, D. A. Tyukhtyaev, and A. O. Pasuk. "IP network optimization by software defined networks." Infokommunikacionnye tehnologii 13, no. 4 (2015): 414–19. http://dx.doi.org/10.18469/ikt.2015.13.4.09.

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13

van Nes, Rob. "Multilevel Network Optimization for Public Transport Networks." Transportation Research Record: Journal of the Transportation Research Board 1799, no. 1 (2002): 50–57. http://dx.doi.org/10.3141/1799-07.

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Wang, Hui, Nazim Agoulmine, Maode Ma, and Yanliang Jin. "Network lifetime optimization in wireless sensor networks." IEEE Journal on Selected Areas in Communications 28, no. 7 (2010): 1127–37. http://dx.doi.org/10.1109/jsac.2010.100917.

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Panda, Subodh, Bikash Swain, and Sandeep Mishra. "Boiler Performance Optimization Using Process Neural Network." Indian Journal of Applied Research 3, no. 7 (2011): 298–300. http://dx.doi.org/10.15373/2249555x/july2013/93.

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Zhao, Fang, Ike Ubaka, and Albert Gan. "Transit Network Optimization." Transportation Research Record: Journal of the Transportation Research Board 1923, no. 1 (2005): 180–88. http://dx.doi.org/10.1177/0361198105192300119.

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This paper presents a mathematical methodology for transit route network optimization. The goal is to provide an effective computational tool for optimization of a large-scale transit route network. The objectives are to minimize transfers and maximize service coverage. Formulation of the method consists of three parts: representation of transit route network solution search spaces, representation of transit route and network constraints, and a stochastic search scheme capable of finding the expected global optimal result on the basis of an integrated simulated annealing, tabu, and greedy sear

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Grout, VM, and PW Sanders. "Communication network optimization." Computer Communications 11, no. 5 (1988): 281–87. http://dx.doi.org/10.1016/0140-3664(88)90039-4.

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18

Rezazad, Hadi. "Computer network optimization." Wiley Interdisciplinary Reviews: Computational Statistics 3, no. 1 (2010): 34–46. http://dx.doi.org/10.1002/wics.135.

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Kozdrowski, Stanisław, Mateusz Żotkiewicz, and Sławomir Sujecki. "Ultra-Wideband WDM Optical Network Optimization." Photonics 7, no. 1 (2020): 16. http://dx.doi.org/10.3390/photonics7010016.

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Ultra-wideband wavelength division multiplexed networks enable operators to use more effectively the bandwidth offered by a single fiber pair and thus make significant savings, both in operational and capital expenditures. The main objective of this study is to minimize optical node resources, such as transponders, multiplexers and wavelength selective switches, needed to provide and maintain high quality of network services, in ultra-wideband wavelength division multiplexed networks, at low cost. A model based on integer programming is proposed, which includes a detailed description of optica

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Rizky Amalia and Febriyanti Panjaitan. "Mask Detection Using Convolutional Neural Network Algorithm." Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) 6, no. 4 (2022): 639–47. http://dx.doi.org/10.29207/resti.v6i4.4276.

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The World Health Organizations and the Ministry of Health of the Republic of Indonesia have required the use of masks to suppress the spread of COVID-19. WHO provides guidance on how to use a good mask to cover the mouth and nose. This study aims to detect the correct use of masks using the Convolutional Neural Network. CNN is a popular Deep Learning algorithm for image data classification problems. The Mask Usage Detector is built with the help of a pre-trained MobileNetV2 model with an architecture that supports media that has minimum computations. This study will also compare the performanc

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Guo, Aipeng, and Chunhui Yuan. "Network Intelligent Control and Traffic Optimization Based on SDN and Artificial Intelligence." Electronics 10, no. 6 (2021): 700. http://dx.doi.org/10.3390/electronics10060700.

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For telecom operators, it is of great significance to employ artificial intelligence (AI) and big data technology in a software-defined network (SDN) in order to achieve intelligent network control, traffic management and optimization. This paper proposes a solution for intelligent work control and traffic optimization. This paper is mainly focused on SDN-based network traffic algorithm optimization and experimental verification. In this paper, we design a network control mechanism for network intelligent control as well as solutions for traffic optimization based on SDN and artificial intelli

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Ms., Prerana Shrivastava*. "SINK REPOSITIONING OPTIMIZATION TECHNIQUE USING PARTICLE SWARM OPTIMIZATION IN WIRELESS SENSOR NETWORKS." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 5, no. 6 (2016): 192–98. https://doi.org/10.5281/zenodo.54777.

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In today’s wireless sensor networks mobile sinks plays an important role in data transmission and reception. Therefore it becomes very important to estimate the optimized position of the mobile sinks in order to improve the overall efficiency of the wireless sensor networks. In this paper, the particle swarm optimization technique has been used for the estimation of the position of the mobile sinks and its impact on the various performance factors of the wireless sensor network has been observed. The simulation result showed that finding the optimal location of the sink in the mobile env

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23

Duan, Chao, and Jun Luo. "Mobile Communication Network Optimization System Based on Artificial Intelligence." Wireless Communications and Mobile Computing 2021 (September 20, 2021): 1–5. http://dx.doi.org/10.1155/2021/9999873.

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The objective of this paper is to study the key technology of the mobile communication network optimization system based on artificial intelligence technology. Specific Content. This paper designs the artificial intelligence agent- (IA-) type mobile communication network optimization tool iOS2CMCN, analyzes the relevant intelligent technology introduced into the system, and analyzes the feasibility and practicability of iOS2CMCN through application examples. The results show that the optimization of mobile communication networks is one of the important links in the construction of communicatio

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Prakash, Arun, Rajesh Verma, Rajeev Tripathi, and Kshirasagar Naik. "Extended Mobile IPv6 Route Optimization for Mobile Networks in Local and Global Mobility Domain." International Journal of Mobile Computing and Multimedia Communications 2, no. 2 (2010): 1–17. http://dx.doi.org/10.4018/jmcmc.2010040101.

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Network mobility (NEMO) route optimization support is strongly demanded in next generation networks; without route optimization the mobile network (e.g., a vehicle) tunnels all traffic to its Home Agent (HA). The mobility may cause the HA to be geographically distant from the mobile network, and the tunneling causes increased delay and overhead in the network. It becomes peculiar in the event of nesting of mobile networks due to pinball routing, for example, a Personal Area Network (PAN) inside a vehicle. The authors propose an Extended Mobile IPv6 route optimization (EMIP) scheme to enhance t

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Ou, Xiaopeng, and Xu Yang. "Coverage optimization of wireless sensor networks based on bottle sea sheath optimization algorithm." Journal of Physics: Conference Series 2761, no. 1 (2024): 012032. http://dx.doi.org/10.1088/1742-6596/2761/1/012032.

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Abstract To tackle the problem of inadequate placement of wireless sensor networks’ sensor nodes, a proposed algorithm aims to enhance network coverage through a more optimal approach. Recognizing limitations in the Salp Swarm Algorithm (SSA) optimization, specifically its insufficient local search capability and susceptibility to local extreme values, a hybrid strategy is introduced in the search step. This strategy involves adaptive weight factor adjustments and incorporates Levy flight, achieving a better balance between global search, convergence speed, and computational accuracy. Conseque

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Gu, Musong, Lei You, Jun Hu, Lintao Duan, and Zhen Zuo. "The Wireless Sensor Networks Base Layout and Density Optimization Oriented towards Traffic Information Collection." Mathematical Problems in Engineering 2015 (2015): 1–8. http://dx.doi.org/10.1155/2015/214905.

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Wireless sensor networks (WSN) are applied in Intelligent Transport System for data collection. For the low redundancy rate of the wireless sensor networks nodes of traffic information collection, the senor nodes should be deployed reasonably for the WSN nodes to work effectively, and, thus, the base network structure and the density optimization of the sensor network are one of the main problems of WSN application. This paper establishes the wireless sensor networks design optimization model oriented to the traffic information collection, solving the design optimization model with the chemica

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Okindo, Geoffrey, Prof George Kamucha, and Dr Nicholas Oyie. "Dynamic Optimization in 5G Network Slices: A Comparative Study of Whale Optimization, Particle Swarm Optimization, and Genetic Algorithm." International Journal of Electrical and Electronics Research 12, no. 3 (2024): 849–62. http://dx.doi.org/10.37391/ijeer.120316.

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This study presents a comprehensive framework for optimizing 5G network slices using metaheuristic algorithms, focusing on Enhanced Mobile Broadband (eMBB), Ultra-Reliable Low-Latency Communications (URLLC), and massive Machine Type Communications (mMTC) scenarios. The initial setup involves a MATLAB-based 5G New Radio (NR) Physical Downlink Shared Channel (PDSCH) simulation and OpenAir-Interface (OAI) 5G network testbed, utilizing Ubuntu 22.04 Long Term Support (LTS), MicroStack, Open-Source MANO (OSM), and k3OS to create a versatile testing environment. Key network parameters are identified

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Nedić, Angelia, and Ji Liu. "Distributed Optimization for Control." Annual Review of Control, Robotics, and Autonomous Systems 1, no. 1 (2018): 77–103. http://dx.doi.org/10.1146/annurev-control-060117-105131.

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Advances in wired and wireless technology have necessitated the development of theory, models, and tools to cope with the new challenges posed by large-scale control and optimization problems over networks. The classical optimization methodology works under the premise that all problem data are available to a central entity (a computing agent or node). However, this premise does not apply to large networked systems, where each agent (node) in the network typically has access only to its private local information and has only a local view of the network structure. This review surveys the develo

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He, Yongqiang, and Mingming Yang. "Research on cross-layer design and optimization algorithm of network robot 5G multimedia sensor network." International Journal of Advanced Robotic Systems 16, no. 4 (2019): 172988141986701. http://dx.doi.org/10.1177/1729881419867016.

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Cross-layer optimization based on maximizing the utility of network robot 5G multimedia sensor network is a systematic method for cross-layer design of wireless networks. It abstracts the functional and performance requirements of the layers in the protocol stack into objective functions and constraints in mathematical optimization problems. In this article, the cross-layer optimization problem of wireless Mesh networks using multi-radio interface multi-channel technology is studied. The optimization problem is modelled based on the network utility maximization method, and the corresponding al

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Fatimah, Siti. "Neural Network Optimization Optimization For Medical Image Processing." Jurnal Komputer Indonesia 2, no. 1 (2023): 33–40. http://dx.doi.org/10.37676/jki.v2i1.566.

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Medical image processing is a crucial field in healthcare, especially in supporting diagnosis and clinical decision-making. Artificial Neural Networks (ANNs) have become an effective tool in medical image processing, but challenges in ANN optimization still need to be addressed to achieve higher accuracy and better efficiency. This article examines JST optimization methods applied to medical image processing. Various techniques such as network architecture adjustment, regulation, and the use of advanced optimization algorithms are explored in this study. The results show that JST optimization

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Zhang, Tao. "Collaborative Cognitive Wireless Network Optimization Model and Network Parameter Optimization Algorithm." Journal of Electrical and Computer Engineering 2023 (January 13, 2023): 1–11. http://dx.doi.org/10.1155/2023/3748089.

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In recent years, the combination of cognitive radio and collaborative communication has been widely studied and applied because of its ability to increase user throughput and improve spectrum utilization in a flat-fading wireless channel environment. Such cognitive radio networks that use user collaboration to improve channel capacity and spectrum utilization are called collaborative cognitive radio networks. A Nash equilibrium game-based relay node selection algorithm is investigated, which aims to maximize the utility function of primary and cognitive users. Secondly, a Stackelberg game is i

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Li, Xingmin, Hongwei Li, Shuaibing Li, Ziwei Jiang, and Xiping Ma. "Review on Reactive Power and Voltage Optimization of Active Distribution Network with Renewable Distributed Generation and Time-Varying Loads." Mathematical Problems in Engineering 2021 (November 23, 2021): 1–18. http://dx.doi.org/10.1155/2021/1196369.

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With a high proportion of renewable distributed generation and time-varying load connected to the distribution network, great challenges have appeared in the reactive power optimization control of the active distribution networks. This paper first introduces the characteristics of active distribution networks, the mechanism and research status of wind power, photovoltaic, and other renewable distributed generators, and time-varying loads participating in reactive power and voltage optimization. Then, the paper summarizes the methods of reactive power optimization and voltage regulation of acti

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Qi, Shengyuan, Lin Yang, Linru Ma, Shanqing Jiang, and Guang Cheng. "Dual-Network Layered Network: A Method to Improve Reliability, Security, and Network Efficiency in Distributed Heterogeneous Network Transmission." Electronics 13, no. 23 (2024): 4749. https://doi.org/10.3390/electronics13234749.

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This article delves into the routing architecture and reliable transmission service framework of dual-network layered networks, with a focus on analyzing their core design ideas and implementation strategies. In the context of increasing network complexity today, traditional single-network architectures are unable to meet diverse application needs. Therefore, dual-network layered networks, as an innovative solution, are gradually receiving attention from both academia and industry. This article first analyzes the key technical elements in the dual-network layered network architecture, includin

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Klepac, Goran. "Particle Swarm Optimization Algorithm as a Tool for Profile Optimization." International Journal of Natural Computing Research 5, no. 4 (2015): 1–23. http://dx.doi.org/10.4018/ijncr.2015100101.

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Complex analytical environment is challenging environment for finding customer profiles. In situation where predictive model exists like Bayesian networks challenge became even bigger regarding combinatory explosion. Complex analytical environment can be caused by multiple modality of output variable, fact that each node of Bayesian network can potetnitaly be target variable for profiling, as well as from big data environment, which cause data complexity in way of data quantity. As an illustration of presented concept particle swarm optimization algorithm will be used as a tool, which will fin

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Zainal, Azavitra. "pH Neutralization Plant Optimization Using Artificial Neural Network." Journal of Advanced Research in Dynamical and Control Systems 12, SP4 (2020): 1466–72. http://dx.doi.org/10.5373/jardcs/v12sp4/20201625.

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Xu, L., K. Fujimura, and M. B. McDonald. "Automatic separation of overlapping seedlings by network optimization." Seed Science and Technology 35, no. 2 (2007): 337–50. http://dx.doi.org/10.15258/sst.2007.35.2.09.

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Ghaffariyan M, R., K. Stampfer, J. Sessions, T. Durston, CH Kanzian, and M. Kuehmaier. "Road network optimization using heuristic and linear programming." Journal of Forest Science 56, No. 3 (2010): 137–45. http://dx.doi.org/10.17221/12/2009-jfs.

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&nbsp;To minimize the cost of logging, it is necessary to optimize the road density. The aim of this study was to determine optimal road spacing (ORS) in Northern Austria. The stepwise regression method was used in modelling. The production rate of tower yarder was 10.4 m<SUP>3</SUP>/PSHo (Productive system hours) and cost of 19.71 €.m<SUP>–3</SUP>. ORS was studied by calculating road construction cost, installation cost and yarding cost per m<SUP>3</SUP> for different road spacing. The minimum total cost occurred at 39.15 €.m<SUP>–3</SUP> an

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Liao, Huilian. "Review on Distribution Network Optimization under Uncertainty." Energies 12, no. 17 (2019): 3369. http://dx.doi.org/10.3390/en12173369.

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With the increase of renewable energy in electricity generation and increased engagement from demand sides, distribution network planning and operation face great challenges in the provision of stable, secure and dedicated service under a high level of uncertainty in network behaviors. Distribution network planning and operation, at the same time, also benefit from the changes of current and future distribution networks in terms of the availability of increased resources, diversity, smartness, controllability and flexibility of the distribution networks. This paper reviews the critical optimiz

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Walton, N. S. "Utility Optimization in Congested Queueing Networks." Journal of Applied Probability 48, no. 1 (2011): 68–89. http://dx.doi.org/10.1239/jap/1300198137.

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We consider a multiclass single-server queueing network as a model of a packet switching network. The rates packets are sent into this network are controlled by queues which act as congestion windows. By considering a sequence of congestion controls, we analyse a sequence of stationary queueing networks. In this asymptotic regime, the service capacity of the network remains constant and the sequence of congestion controllers act to exploit the network's capacity by increasing the number of packets within the network. We show that the stationary throughput of routes on this sequence of networks

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Walton, N. S. "Utility Optimization in Congested Queueing Networks." Journal of Applied Probability 48, no. 01 (2011): 68–89. http://dx.doi.org/10.1017/s0021900200007646.

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We consider a multiclass single-server queueing network as a model of a packet switching network. The rates packets are sent into this network are controlled by queues which act as congestion windows. By considering a sequence of congestion controls, we analyse a sequence of stationary queueing networks. In this asymptotic regime, the service capacity of the network remains constant and the sequence of congestion controllers act to exploit the network's capacity by increasing the number of packets within the network. We show that the stationary throughput of routes on this sequence of networks

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Oluwatobi, Akinmerese, Awodele Oludele, Makinwa Kofi, Kuyoro Shade, and Adedeji Folasade. "A Study of Network Optimization Models for High-Performance Networks." International Journal of Innovative Science and Research Technology 8, no. 5 (2023): 2664–70. https://doi.org/10.5281/zenodo.8021560.

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An important feature of a bandwidth optimization system is the adequate provision of internet services with high data rates and wide coverage. Low bandwidth causes poor internet speed, network downtime, constant network traffic congestion and network unavailability during peak and off-peak periods, to mention a few. Existing research on bandwidth optimization focused on bandwidth allocation in creating different channels and traffic isolation to Guarantee good Quality of Service (QoS). Despite several optimization techniques and bandwidth allocation algorithms of existing researchers, there is

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Syahputra, Ramadoni, and Indah Soesanti. "Optimisasi Multi-objektif pada Rekonfigurasi Jaringan Distribusi Tenaga Listrik dengan Integrasi Pembangkit Terdistribusi Menggunakan Metode Sistem Kekebalan Buatan." Jurnal Teknik Elektro 12, no. 2 (2020): 57–71. http://dx.doi.org/10.15294/jte.v12i2.26353.

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This study proposes a multi-objective optimization for power distribution network reconfiguration by integrating distributed generators using an artificial immune system (AIS) method. The most effective and inexpensive technique in reducing power losses in distribution networks is optimizing the network reconfiguration. On the other hand, small to medium scale renewable energy power plant applications are growing rapidly. These power plants are operated on-grid to a distribution network, known as distributed generation (DG). The presence of DG in this distribution network poses new challenges

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Wei, Jingyu. "Subway network optimization and passenger travel experience." Applied and Computational Engineering 33, no. 1 (2024): 73–79. http://dx.doi.org/10.54254/2755-2721/33/20230236.

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This conference paper examines the significance of subway network optimization in relation to passenger travel experience. It begins with an introduction that highlights the importance of subway networks in urban transportation and establishes the objectives of network optimization. A comprehensive literature review explores previous research on subway network optimization and passenger travel experience, identifying strengths, limitations, and research gaps. The paper then explores various methods of subway network optimization, including network structure optimization, train scheduling optim

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Ouahi, Hassan, and Abdenbi Mazoul. "Traffic optimization in IoT networks." E3S Web of Conferences 229 (2021): 01050. http://dx.doi.org/10.1051/e3sconf/202122901050.

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Since the 2000s, the idea that the Internet could be used for machine-to-machine communication and process automation has emerged. Together with the development of electronic objects capable of communicating with IP protocols, this idea led to the concept of the Internet of Things (IoT Internet of Things). Nowadays, the evolution of networks is very intense. New networks are appearing, “all-optical” solutions in the heart of networks, “wireless” solutions to facilitate access to users or to implant sensors / actors in places difficult to access, or finally the Internet of communicating objects

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Hui, Honglin, Hao Gong, Jiawen Gao, Wanqing Lu, and Xiuye Hu. "Research on Emergency Dispatch Optimization of E-commerce Logistics Based on Multi Objective Optimization Model." Highlights in Business, Economics and Management 51 (February 27, 2025): 9–15. https://doi.org/10.54097/54118e11.

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Logistics networks are closely related to daily life, and ensuring network circulation and responding to emergencies are crucial. This article delves into the logistics network adjustment strategy, aiming to improve the ability of the logistics network to respond to emergencies. The study begins by analysing the daily delivery volume and revealing the cyclical and trending characteristics of logistics demand. Subsequently, the ARIMA model and the BP neural network model were used to predict the transportation data, which could take into account the autocorrelation and nonlinear characteristics

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Chung, Daewon, and Insoo Sohn. "Neural Network Optimization Based on Complex Network Theory: A Survey." Mathematics 11, no. 2 (2023): 321. http://dx.doi.org/10.3390/math11020321.

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Complex network science is an interdisciplinary field of study based on graph theory, statistical mechanics, and data science. With the powerful tools now available in complex network theory for the study of network topology, it is obvious that complex network topology models can be applied to enhance artificial neural network models. In this paper, we provide an overview of the most important works published within the past 10 years on the topic of complex network theory-based optimization methods. This review of the most up-to-date optimized neural network systems reveals that the fusion of

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Wang, Miao, Xu Yang, Yunchong Qian, et al. "Adaptive Neural Network Structure Optimization Algorithm Based on Dynamic Nodes." Current Issues in Molecular Biology 44, no. 2 (2022): 817–32. http://dx.doi.org/10.3390/cimb44020056.

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Large-scale artificial neural networks have many redundant structures, making the network fall into the issue of local optimization and extended training time. Moreover, existing neural network topology optimization algorithms have the disadvantage of many calculations and complex network structure modeling. We propose a Dynamic Node-based neural network Structure optimization algorithm (DNS) to handle these issues. DNS consists of two steps: the generation step and the pruning step. In the generation step, the network generates hidden layers layer by layer until accuracy reaches the threshold

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Syulistyo, Arie Rachmad, Dwi Marhaendro Jati Purnomo, Muhammad Febrian Rachmadi, and Adi Wibowo. "PARTICLE SWARM OPTIMIZATION (PSO) FOR TRAINING OPTIMIZATION ON CONVOLUTIONAL NEURAL NETWORK (CNN)." Jurnal Ilmu Komputer dan Informasi 9, no. 1 (2016): 52. http://dx.doi.org/10.21609/jiki.v9i1.366.

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Neural network attracts plenty of researchers lately. Substantial number of renowned universities have developed neural network for various both academically and industrially applications. Neural network shows considerable performance on various purposes. Nevertheless, for complex applications, neural network’s accuracy significantly deteriorates. To tackle the aforementioned drawback, lot of researches had been undertaken on the improvement of the standard neural network. One of the most promising modifications on standard neural network for complex applications is deep learning method. In th

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Hickish, Bob, David I. Fletcher, and Robert F. Harrison. "Investigating Bayesian Optimization for rail network optimization." International Journal of Rail Transportation 8, no. 4 (2019): 307–23. http://dx.doi.org/10.1080/23248378.2019.1669500.

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TSIOUTSIAS, DIMITRIS I., and ERIC MJOLSNESS. "OPTIMIZATION DYNAMICS FOR PARTITIONED NEURAL NETWORKS." International Journal of Neural Systems 05, no. 04 (1994): 275–86. http://dx.doi.org/10.1142/s0129065794000281.

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Given a relaxation-based neural network and a desired partition of the neurons in the network into modules with relatively slow communication between modules, we investigate relaxation dynamics for the resulting partitioned neural network. In particular, we show how the slow inter-module communication channels can be modeled by means of certain transformations of the original objective function which introduce new state variables for the inter-module communication links. We report on a parallel implementation of the resulting relaxation dynamics, for a two-dimensional image segmentation networ

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