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Articoli di riviste sul tema "Logistic networks"

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Autore: Grafiati

Pubblicato: 1 giugno 2024

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1

Wińcewicz-Bosy, Marta, e Iwo Nowak. "Logistic networks and globalization challenges". Scientific Papers of Silesian University of Technology. Organization and Management Series 2018, n. 128 (2018): 435–49. http://dx.doi.org/10.29119/1641-3466.2018.128.33.

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Ştefan, Nedelea, e Păun Laura Adriana. "Knowledge Sharing In Logistic Networks". Annales Universitatis Apulensis Series Oeconomica 2, n. 10 (31 dicembre 2008): 489–92. http://dx.doi.org/10.29302/oeconomica.2008.10.2.6.

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3

Elbetch, Bilel. "Generalized logistic equation on Networks". Comptes Rendus. Mathématique 361, G5 (18 luglio 2023): 911–34. http://dx.doi.org/10.5802/crmath.460.

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4

Nefedova, N. E. "PUBLICLY-GEOGRAPHICAL RESEARCHES OF TRANSPORT-LOGISTIC NETWORKS AND SYSTEMS". Odesa National University Herald. Geography and Geology 19, n. 3(22) (2 aprile 2015): 107–14. http://dx.doi.org/10.18524/2303-9914.2014.3(22).40353.

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Abstract (sommario):

Among the issues of the day of economic and social development of countries an important place is occupied by the problems of forming of transport-logistic networks and systems, as effective and concerted work of a transport system and modern logistic organization of commodity streams is motive force for socio-economic development of the state. Transport networks (transport lines and knots) are examined as an inalienable link of logistic chain of motion of commodity. Functional cooperation and spatial relations that is set as a result of realization of logistic projects from advancement of commodities on the basis of an existent transport structure of lines and knots (networks) form transport-logistic networks and systems. Research aim – to consider theoretical and methodological bases of publicly-geographical researches of transport-logistic networks and systems. A research object is transport-logistic networks and systems. The article of research is features of forming, functioning and territorial organization of transport-logistic structure of lines and knots (networks) and systems. A theoretical value is generalization of theoretical experience and development of concept-category vehicle of publicly-geographical researches of transport-logistic networks and systems. A practical value is development of methodological principles and methodical approaches of publicly-geographical researches of transport-logistic networks and systems.The article is sanctified to the features of forming of the territorial transport-logistic systems and network territorial organization of transport-logistic activity. Given historical review of becoming and development of geography of transport, publicly-geographical researches of logistic and transport logistic. Considered principles of network and system organization of transport-logistic activity.

5

Kramarz, Marzena, e Mariusz Kmiecik. "Quality of Forecasts as the Factor Determining the Coordination of Logistics Processes by Logistic Operator". Sustainability 14, n. 2 (17 gennaio 2022): 1013. http://dx.doi.org/10.3390/su14021013.

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(1) Background: Currently, logistics operators are struggling with the problem of acquiring new areas to create added value. One of such challenges is acquiring a new function in the form of demand forecasting and coordination skills. The increase in the need to forecast demand is related to the increasing complexity of the distribution network, omnichannel systems and turbulent environment. It is necessary to have a comprehensive approach to the distribution network and to develop competences related to coordination. For the authors, one of the most important coordination factors is the quality of forecasts, especially in relation to modern logistics operators. (2) Methods: In literature studies, the authors combine prognostic abilities with a predisposition to coordinate logistic processes in distribution networks. The aim of the research is to develop a forecasting model that will allow a logistic operator who aspires to coordinate logistics processes to create forecasts in the distribution system. The tool was developed in the R programming language and allows for forecasting based on data from the Warehouse Management System; (3) Results: The quality of forecasts is correlated with the characteristics of the products, the relationship between the manufacturing company and the logistics operator, and the configuration of the distribution network in individual chains. The results of the forecasts were compared with selected features of each of the 5 distribution networks that were tested. In parallel, the attributes of a company capable of forecasting in the distribution network were analyzed. These attributes were also compared to those of the logistics operator. (4) Conclusions: The authors proved that a logistic operator with a set of defined features is capable of generating demand in the entire distribution network.

6

Tao, Yi, Shihang Wang, Jiang Wu, Mingsong Zhao e Zhen Yang. "Logistic Network Construction and Economic Linkage Development in the Guangdong-Hong Kong-Macao Greater Bay Area: An Analysis Based on Spatial Perspective". Sustainability 14, n. 23 (24 novembre 2022): 15652. http://dx.doi.org/10.3390/su142315652.

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Regional logistic networks and linking urban clusters to boost high quality economic development are both key topics in sustainable development in China. In recent years, China has highlighted the significance of the logistics industry and urban cluster development, attaching practical importance to the connections between these two topics from a spatial perspective. This paper aims to discuss how regional logistic networks linking urban clusters improve economic development. This study constructs a logistic evaluation indicator system based on the multi-indicator data of 11 cities in the Guangdong-Hong Kong-Macao Greater Bay Area in 2020. This research employs the entropy-weighted-TOPSIS method to measure and rank the comprehensive logistics quality of each city in the economically linked logistic network of the Guangdong-Hong Kong-Macao Greater Bay Area. This study applies the modified gravity model to explore the logistics linkage and logistic network characteristics of each city in the Guangdong-Hong Kong-Macao Greater Bay Area. Finally, this research analyzes how the agglomeration ability of the central cities in the Guangdong-Hong Kong-Macao Greater Bay Area affects other cities from a spatial perspective. Furthermore, this spatial perspective investigates the agglomeration effect of the economic linkage logistic network through the social network analysis method. The results have the following three implications. (1) The logistic network has a high density, a stable overall structure with a strong agglomeration effect, and there is an increasingly mature logistic network development in the Guangdong-Hong Kong-Macao Greater Bay Area in the Bay Area. (2) Agglomeration is significant in the central cities of the Guangdong-Hong Kong-Macao Greater Bay Area including Hong Kong, Shenzhen, Guangzhou, and Macao. Nonetheless, insufficient peripheral cities have been cultivated. Therefore, the government should focus on strengthening the balance of urban development in the bay area and improving the logistics access among cities to break through the barriers of regional synergistic development. (3) The economic development of cities is highly correlated with the level of logistics links. Additionally, the economy is the cornerstone to promoting the high-quality development of the logistics industry. Moreover, the economy and logistics are inseparable, mutually promoted, and developed together.

7

Solá Conde, Luis E., Javier Used e Miguel Romance. "Optimal distributions for multiplex logistic networks". Chaos: An Interdisciplinary Journal of Nonlinear Science 26, n. 6 (giugno 2016): 065312. http://dx.doi.org/10.1063/1.4953470.

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8

Steyerberg, Ewout W., Frank E. Harrell e Philip H. Goodman. "Neural Networks, Logistic Regression, and Calibration". Medical Decision Making 18, n. 3 (agosto 1998): 349–50. http://dx.doi.org/10.1177/0272989x9801800314.

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9

Feliks, Jerzy, Marek Karkula e Katarzyna Majewska. "The use of computer simulation for analysing the logistics networks resilience". WUT Journal of Transportation Engineering 120 (1 marzo 2018): 75–86. http://dx.doi.org/10.5604/01.3001.0014.4727.

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Abstract (sommario):

Logistic networks are complex systems, composed of many elements connected through nonlinear relations. This property makes it difficult to study these systems with traditional analytical methods. Therefore, computer simulation is a valuable tool in the practical applications of modeling the structure of the logistics network, the relationship between its components and the rules controling its functioning. The simulation model can be run in order to imitate the operation of the actual system in a given time interval and analyze its behavior under different scenarios. In the paper resilience measures for logistic networks are proposed and a multi-method approach of computer simulation for analysing their resistance is presented. The proposed concept allows determining and checking the possibilities ways of building long-term robustness of logistics networks for serious disturbances. The application of the model is illustrated by an example from the steel industry. AnyLogic 8.2 software was used for the implementation.

10

Mazur, Karolina, e Radosław Milewski. "Modeling of value flows in logistics networks. Comparison of basic tools". Management 22, n. 2 (1 dicembre 2018): 158–70. http://dx.doi.org/10.2478/manment-2018-0029.

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Summary The article presents the necessity of introducing modern systems for analyzing value flows in modern logistics networks. The essence of logistic networks and requirements for analytical systems have been presented. The main available approaches to analyzing value flows in the network have been identified: e3-value modeling, c3-value modeling framework, Value Network AnalysisTM, SimulValor, Modified SimulValor. These approaches (called models) were subjected to a critical analysis on the basis of which the basic directions of their development were indicated.

11

Kubo, Masao, Akihiro Yamaguchi, Sadayoshi Mikami e Mitsuo Wada. "Logistic Chaos Protects Evolution against Environment Noise". Journal of Robotics and Mechatronics 10, n. 4 (20 agosto 1998): 350–57. http://dx.doi.org/10.20965/jrm.1998.p0350.

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We propose a neuron with noise generator specially for the evolutionary robotics approach to incremental knowledge acquisition. Genetically evolving neural networks are modified continuously by genetic operations. Difficulty in incrementing knowledge when a neural network acts as a robotic controller arises when network operates unlike in the past due to disturbance by neurons added by genetic operators. To evolve a network robust against such internal noise, we propose adding noise generators to neurons. We show the effectiveness of the application of a logistic chaos noise generator to neurons by comparing several noise generators.

12

Becker, Till, Moritz Emanuel Beber, Katja Windt e Marc-Thorsten Hütt. "The impact of network connectivity on performance in production logistic networks". CIRP Journal of Manufacturing Science and Technology 5, n. 4 (gennaio 2012): 309–18. http://dx.doi.org/10.1016/j.cirpj.2012.09.004.

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13

Tzougas, George, e Konstantin Kutzkov. "Enhancing Logistic Regression Using Neural Networks for Classification in Actuarial Learning". Algorithms 16, n. 2 (9 febbraio 2023): 99. http://dx.doi.org/10.3390/a16020099.

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We developed a methodology for the neural network boosting of logistic regression aimed at learning an additional model structure from the data. In particular, we constructed two classes of neural network-based models: shallow–dense neural networks with one hidden layer and deep neural networks with multiple hidden layers. Furthermore, several advanced approaches were explored, including the combined actuarial neural network approach, embeddings and transfer learning. The model training was achieved by minimizing either the deviance or the cross-entropy loss functions, leading to fourteen neural network-based models in total. For illustrative purposes, logistic regression and the alternative neural network-based models we propose are employed for a binary classification exercise concerning the occurrence of at least one claim in a French motor third-party insurance portfolio. Finally, the model interpretability issue was addressed via the local interpretable model-agnostic explanations approach.

14

Battini, Daria, Maurizio Faccio, Alessandro Persona e Fabio Sgarbossa. "Modelling the Growing Process of Integrated Healthcare Supply Networks". International Journal of System Dynamics Applications 2, n. 1 (gennaio 2013): 1–13. http://dx.doi.org/10.4018/ijsda.2013010101.

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This work contributes to the practice of healthcare system modelling, by presenting an urgent issue: the growing process of integrated healthcare supply networks in reducing public healthcare systems’ annual expenses and improving performance. Various critical aspects affect the strategic design and development of healthcare logistic networks in practice. The conceptual discussion is empirically derived on the basis of the challenge created by the development of centralized healthcare supply networks supported by the implementation of new IT/IS investments and advanced logistic hubs for hospital material inventory management. The study moves towards the development of a newer “Healthcare Supply Network Causal Loop Diagram”, to analyse and predict the growth pattern of a healthcare logistic network in its complexity, and understand how well the supply network will fit with the benefit provided by new logistic economies of scale and the risk of failures under uncertainty.

15

Rettig, Rasmus, Christoph Schöne, Frederik Fröhlich e Christopher Niemöller. "Method for Systematic Assessment of Mobile Network Coverage for Logistic Applications on the German Highway". Network 2, n. 2 (30 maggio 2022): 311–28. http://dx.doi.org/10.3390/network2020020.

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Smart logistics, combining the capabilities of logistics with methods and techniques of the Internet of Things, Information and Communication Technologies, and the highest levels of automation are key to addressing the challenges of the 21st century and minimizing emissions while maximizing logistic performance. High-performance cellular networks are a prerequisite to fully using and leveraging their possibilities. These communication networks were developed based on the need for voice communication and streaming services. While the upcoming requirements are included in the latest versions of cellular networks, the existing infrastructure requires significant improvements and will have to adapt significantly. This study evaluates the performance of the current state of implementation of cellular networks on the German highway experimentally and analytically. The known indicators RSRP, RSSI, and RSRQ are analyzed spatially, over time, and for different driving conditions. The results indicate a high level of spatial correlation and a sufficient level of confidence, which are needed to ensure consistency and repeatability of these measurements. The procedure and the results can be used to assess the suitability of cellular networks for smart logistics applications and continuously monitor their improvement. The results indicate the status of the cellular network on the German highway which is worse compared to the network operator’s self-assessment.

16

Serrano, C., W. Aggoune-Mtalaa e N. Sauer. "Dynamic Models for Green Logistic Networks Design". IFAC Proceedings Volumes 46, n. 9 (2013): 736–41. http://dx.doi.org/10.3182/20130619-3-ru-3018.00101.

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17

Sajjadi, Mehdi, Mojtaba Seyedhosseini e Tolga Tasdizen. "Nonlinear Regression with Logistic Product Basis Networks". IEEE Signal Processing Letters 22, n. 8 (agosto 2015): 1011–15. http://dx.doi.org/10.1109/lsp.2014.2380791.

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18

Schumacher, Martin, Reinhard Roßner e Werner Vach. "Neural networks and logistic regression: Part I". Computational Statistics & Data Analysis 21, n. 6 (giugno 1996): 661–82. http://dx.doi.org/10.1016/0167-9473(95)00032-1.

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19

Vach, Werner, Reinhard Roßner e Martin Schumacher. "Neural networks and logistic regression: Part II". Computational Statistics & Data Analysis 21, n. 6 (giugno 1996): 683–701. http://dx.doi.org/10.1016/0167-9473(95)00033-x.

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20

Ishfaq, Rafay, e Charles R. Sox. "Hub location–allocation in intermodal logistic networks". European Journal of Operational Research 210, n. 2 (aprile 2011): 213–30. http://dx.doi.org/10.1016/j.ejor.2010.09.017.

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21

Du, Yan, Lijuan Jia, Shunshoku Kanae e Zijiang Yang. "Diffusion logistic regression algorithms over multiagent networks". Control Theory and Technology 18, n. 2 (maggio 2020): 160–67. http://dx.doi.org/10.1007/s11768-020-0009-2.

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22

Heckl, István, Károly Kalauz, Péter Kalocsai e László Halász. "Custom simulator for logistic networks in downstream". Clean Technologies and Environmental Policy 12, n. 6 (22 aprile 2010): 627–34. http://dx.doi.org/10.1007/s10098-010-0294-4.

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23

Ambrosino, Daniela, e Anna Sciomachen. "Impact of Externalities on the Design and Management of Multimodal Logistic Networks". Sustainability 13, n. 9 (30 aprile 2021): 5080. http://dx.doi.org/10.3390/su13095080.

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Abstract (sommario):

It is now widely accepted that the locations of intermediate facilities, such as logistics platforms or inland ports, are key elements of multimodal freight distribution networks and heavily influence their effectiveness. This crucial role of localization decisions is even more significant if we consider their impact on the external costs of the entire logistic corridor, with reference to the cost components associated with environmental sustainability. This paper faces a facility location problem concerning a port system network serving inbound container flows arriving by sea and travelling via road and/or rail towards the hinterland. The aim is to evaluate the impact of externalities on the overall management of the distribution network, including location decisions, flow routing and transport mode choice. We present a Mixed Integer Linear Programming (MILP) model having the goal of minimizing both the location and shipping costs, while accounting for external cost components. In particular, as a novel environmental issue, we propose three different objective functions including congestion, air pollution, and, incidentally, noise and infrastructure deterioration. We allow the containerized flows to be split among several capacitated facilities and road and rail transport modalities. The reported computational experimentation refers to different intermodal freight logistic networks through real data derived from the logistic network departing from the maritime terminals associated with the port of the Ligurian region towards their main destinations in the north-west side of Italy. Finally, we evaluate the impact on both flows and total costs due to a closure or a capacity reduction on some links of the network. The evidence of the impact of sustainability external costs on the design and management of the multimodal logistic network under analysis is emphasized.

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Liu, Rui Yan, Yi Ping Yuan, Shu Guang Tian e Xiao Juan Li. "Network Characteristics Analysis of the Xinjiang Regional Logistic Based on Complex Networks". Key Engineering Materials 522 (agosto 2012): 804–9. http://dx.doi.org/10.4028/www.scientific.net/kem.522.804.

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Reasonable logistics system plays a fundamental role in the process of regional economic development. With the development of Xinjiang's energy resources conversion strategy is ceaseless and thorough, as the country imported energy and scarce mineral resources international channel, Xinjiang internal and external logistics hub action are highlighted with each passing day. In this paper the complex network theory is applied to the Xinjiang regional logistics network, important cities, ports, warehousing point for a node to connect these nodes highway straight-line distance of the railway side, constructed the Xinjiang regional characteristics of the logistics network model. Select the node degree distribution, betweenness, average path length, clustering coefficient as a measure, static statistical properties of the network are analyzed. Provide basic data for the Xinjiang regional logistics network.

25

Liang, Yitao, e Guy Van den Broeck. "Learning Logistic Circuits". Proceedings of the AAAI Conference on Artificial Intelligence 33 (17 luglio 2019): 4277–86. http://dx.doi.org/10.1609/aaai.v33i01.33014277.

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This paper proposes a new classification model called logistic circuits. On MNIST and Fashion datasets, our learning algorithm outperforms neural networks that have an order of magnitude more parameters. Yet, logistic circuits have a distinct origin in symbolic AI, forming a discriminative counterpart to probabilistic-logical circuits such as ACs, SPNs, and PSDDs. We show that parameter learning for logistic circuits is convex optimization, and that a simple local search algorithm can induce strong model structures from data.

26

Tunç, Taner. "A New Hybrid Method Logistic Regression and Feedforward Neural Network for Lung Cancer Data". Mathematical Problems in Engineering 2012 (2012): 1–10. http://dx.doi.org/10.1155/2012/241690.

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Logistic regression (LR) is a conventional statistical technique used for data classification problem. Logistic regression is a model-based method, and it uses nonlinear model structure. Another technique used for classification is feedforward artificial neural networks. Feedforward artificial neural network is a data-based method which can model nonlinear models through its activation function. In this study, a hybrid approach of model-based logistic regression technique and data-based artificial neural network was proposed for classification purposes. The proposed approach was applied to lung cancer data, and obtained results were compared. It was seen that the proposed hybrid approach was superior to logistic regression and feedforward artificial neural networks with respect to many criteria.

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H, Prokudin, Chupaylenko O, Khobotnia T, Hilevska K e Denis O. "LOGISTIC APPROACH TO THE ORGANIZATION OF UNBALANCED FREIGHT TRANSPORTATION ON TRANSPORT NETWORKS". National Transport University Bulletin 1, n. 51 (2022): 323–31. http://dx.doi.org/10.33744/2308-6645-2022-1-51-323-331.

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This article describes the logistics approach, which through the use of transport technologies solves the problem of optimal organization of unbalanced transportation of goods on transport networks. This situation often arises when the volume of deliveries of goods from its suppliers exceeds the capacity of warehouses of its consumers. In this case, we are faced with the need to use intermediate points for the temporary storage of surplus cargo and as a consequence of a multi-stage transport task. The object of research is the process of freight management on transport networks. The purpose of the work is to study the peculiarities of decision-making on freight transport management on transport networks with the use of information technology. Research methods - the method of reducing the network representation of freight into a matrix model and the method of potentials to find the optimal plan of freight. The matrix of transport correspondence between suppliers, consumers and intermediate points is not set explicitly, but simply introduced a map of their location, ie the transport task is set using the transport network. With the help of the modified Dijkstra method, the shortest routes between suppliers and consumers of cargo are found on the transport network, as well as between them and intermediate points for temporary storage of excess cargo. The optimal plan of cargo transportation is calculated with the help of the designed software and tool complex, which combines the stage of reduction of the network representation of the scheme of cargo delivery to the tabular form and the stage of planning and further implementation of mass cargo transportation on the transport network. KEY WORDS: FREIGHT TRANSPORTATION, TRANSPORT NETWORK, MULTI-STAGE TRANSPORT TASK, OPTIMIZATION, SOFTWARE-INSTRUMENT COMP.

28

ALTINTAŞ, Furkan Fahri. "ESTIMATION OF RELATIONS BETWEEN LOGISTICS PERFORMANCE COMPONENTS BY ARTIFICIAL NEURAL NETWORKS". EUROASIA JOURNAL OF SOCIAL SCIENCES & HUMANITIES 8, n. 3 (25 maggio 2021): 101–12. http://dx.doi.org/10.38064/eurssh.212.

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Countries will be able to determine the degree of logistics performance input components to provide the logistics output components, and countries will be able to reveal which logistics input components should be carried out to provide output components. This situation enables countries to make sense of their contributions to the global economy and global trade. In this context, the relationship structure between logistics performance input components and logistics performance output components over the values of Logistic Performance Index (LPI) components of the countries in 2018, 2016, 2014, 2012 and 2010 LPI reports has been predicted with Artificial Neural Networks. According to the findings, the predictive values of contribution to the affective structure of the input components were listed as infrastructure, customs and service quality, and the predictive values of contribution to the influence structure of the output components as timeliness, international shipments and tracking and trace. As a result of the findings, it was found that the independent variables included in the analysis have quite high predictive power for dependent variables. Finally, the significance and normalized significance estimation significance values of the independent variables are listed as infrastructure, service quality and customs. In the study, it was observed that the contribution predictions of customs and service quality logistic input components to the structure of affecting the logistic output components were less than the infrastructure component. Therefore, it has been concluded that countries should carry out activities that will provide logistics performance output components of service quality and customs components in order to increase their own logistics performance and to contribute more to the global economy and trade.

29

Dancey, D., Z. A. Bandar e D. McLean. "Logistic Model Tree Extraction From Artificial Neural Networks". IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics) 37, n. 4 (agosto 2007): 794–802. http://dx.doi.org/10.1109/tsmcb.2007.895334.

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Farraa, Berna Bou, Rosa Abbou e Jean Jacques Loiseau. "Inventory control of a class of logistic networks". Systems & Control Letters 147 (gennaio 2021): 104845. http://dx.doi.org/10.1016/j.sysconle.2020.104845.

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Lapuerta, Pablo, Gilbert L'Italien, Robert Giugliano e Kim A. Eagle. "Neural Networks, Logistic Regression, and Calibration: A Reply". Medical Decision Making 18, n. 4 (ottobre 1998): 444–45. http://dx.doi.org/10.1177/0272989x9801800414.

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Steyerberg, Ewout W., Frank E. Harrell e Philip H. Goodman. "Neural Networks, Logistic Regression, and Calibration: A Rejoinder". Medical Decision Making 18, n. 4 (ottobre 1998): 445–46. http://dx.doi.org/10.1177/0272989x9801800415.

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Marmolejo-Saucedo, J. A., J. Niembro-García e LF Alva-Guerra. "Structural dynamics of logistic networks: A sustainable approach". IFAC-PapersOnLine 52, n. 13 (2019): 2704–9. http://dx.doi.org/10.1016/j.ifacol.2019.11.616.

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Ramirez, Ramiro, Chien-Yi Huang e Shu-Hao Liang. "5G Digital Twin: A Study of Enabling Technologies". Applied Sciences 12, n. 15 (3 agosto 2022): 7794. http://dx.doi.org/10.3390/app12157794.

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Abstract (sommario):

5G networks require dynamic network monitoring and advanced security solutions. This work performs the essential steps to implement a basic 5G digital twin (DT) in a warehouse scenario. This study provides a paradigm of end-to-end connection and encryption to internet of things (IoT) devices. Network function virtualization (NFV) technologies are crucial to connecting and encrypting IoT devices. Innovative logistical scenarios are undergoing constant changes in logistics, and higher deployment of IoT devices in logistic scenarios, such as warehouses, demands better communication capabilities. The simulation tools enable digital twin network implementation in planning. Altair Feko (WinProp) simulates the radio behavior of a typical warehouse framework. The radio behavior can be exported as a radio simulation dataset file. This dataset file represents the virtual network’s payload. GNS3, an open-source network simulator, performs data payload transmission among clients to servers using custom NFV components. By transmitting data from client to server, we achieved end-to-end communication. Additionally, custom NFV components enable advanced encryption standard (AES) adoption. In summary, this work analyzes the round-trip time (RTT) and throughput of the payload data packages, in which two data packages, encrypted and non-encrypted, are observed.

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Herlan, Eka Sudarmaji e M. Rubiul Yatim. "Predictive Creditworthiness Modeling in Energy-Saving Finance: Machine Learning Logit and Neural Network". Financial Risk and Management Reviews 8, n. 1 (8 febbraio 2022): 1–11. http://dx.doi.org/10.18488/89.v8i1.2919.

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Customer's creditworthiness was becoming more crucial for ESCO. Machine learning was used to predict the creditworthiness of clients in retrofit financing processes. Machine learning was used to predict the creditworthiness of clients in ESCO financing processes. This research aimed to develop a retrofitting scoring model to leverage a machine learning and life cycle cost analysis (LCCA) to evaluate alternative financing for Energy Efficiency Saving in Indonesia. The model was built on the Logistic Regression model and Artificial Neural Networks model of machine learning. The model was developed and tested using the Python algorithm, and the proposed model's efficiency was demonstrated. The logistic regression calculations showed that the accuracy value of prediction data with test data was 88.3562 % and 87.67% for Artificial Neural Networks and Logistic Regression models. The prediction rate result that refers to the correct predictions among all test data for Artificial Neural Networks and Logistic Regression model was 92.20% and 91.98%, respectively. Meanwhile, the percentage of customers who were correct to all customers predicted to default was 94.41% for Artificial Neural Networks and 93.81% for the Logistic Regression model. Credit models were helpful to evaluate the risk of consumer loans. Finally, the quality and performance of these models were evaluated and compared to identify the best one. The logistic regression and neural network models obtained were good and very similar, although the neural network was slightly better.

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Islam, Md Shahidul. "Social networks and their effects on the choice of contraceptive use and method in Bangladesh". International Journal of Human Rights in Healthcare 13, n. 1 (23 luglio 2019): 58–71. http://dx.doi.org/10.1108/ijhrh-07-2018-0045.

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Purpose The purpose of this paper is to examine the effects of social networks on contraceptive adoption in Bangladesh. Design/methodology/approach Data were collected from 430 couples; the age of men was between 15 and 49 years. χ2 test was applied to test the association between independent variables and current contraceptive use. Binary logistic regression was applied to examine the effects of social network on contraceptive use, and multinomial logistic regression was applied to examine the effect of social network on the choice of method. Findings Results from binary logistic regression reveal that social networks of both men (OR=2.71, 95% CI=1.371−5.354) and women (OR= 3.597, 95% CI=1.754−7.380) had a strong positive effect on current contraceptive use. The result from multinomial logistic regression also shows that men’s social network (OR= 2.74, 95% CI= 1.356−5.548) and women’s social network (OR=4.165,95% CI=1.958−8.860) were also associated with choosing a modern contraceptive method. Originality/value Social networks have a significant effect on current contraceptive use and modern method choice in Bangladesh. A social network approach should be included in family planning program in Bangladesh.

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Ren, Le Yi, e Xiao Long Deng. "The Research on Network Communication Complex System Based on Logistic Equation". Applied Mechanics and Materials 513-517 (febbraio 2014): 530–34. http://dx.doi.org/10.4028/www.scientific.net/amm.513-517.530.

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In this paper, from the view of the complexity of network organization system, the preliminary research has been carried on network communication complexity system. The concept of the complexity of the network transmission system is introduced in the paper, and networks as complex system is described by the Logistic model. It is a new attempt on the research of network communication with the complexity science research methods based on foundation information science. The research contributes to methodology on the research of the evaluation on network communication effect and network communication content in the future.

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Almquist, Zack W., e Carter T. Butts. "Logistic Network Regression for Scalable Analysis of Networks with Joint Edge/Vertex Dynamics". Sociological Methodology 44, n. 1 (7 marzo 2014): 273–321. http://dx.doi.org/10.1177/0081175013520159.

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Lozano, S., e B. Adenso-Díaz. "Increasing Sustainability of Logistic Networks by Reducing Product Losses: A Network DEA Approach". Mathematical Problems in Engineering 2018 (13 novembre 2018): 1–21. http://dx.doi.org/10.1155/2018/3479251.

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This paper considers a multiproduct supply network, in which losses (e.g., spoilage of perishable products) can occur at either the nodes or the arcs. Using observed data, a Network Data Envelopment Analysis (NDEA) approach is proposed to assess the efficiency of the product flows in varying periods. Losses occur in each process as the observed output flows are lower than the observed input flows. The proposed NDEA model computes, within the NDEA technology, input and output targets for each process. The target operating points correspond to the minimum losses attainable using the best observed practice. The efficiency scores are computed comparing the observed losses with the minimum feasible losses. In addition to computing relative efficiency scores, an overall loss factor for each product and each node and link can be determined, both for the observed data and for the computed targets. A detailed illustration and an experimental design are used to study and validate the proposed approach. The results indicate that the proposed approach can identify and remove the inefficiencies in the observed data and that the potential spoilage reduction increases with the variability in the losses observed in the different periods.

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Rahman, Khaista, Muhammad Adnan Aziz, Nighat Usman, Tayybah Kiren, Tanweer Ahmad Cheema, Hina Shoukat, Tarandeep Kaur Bhatia, Asrin Abdollahi e Ahthasham Sajid. "Cognitive Lightweight Logistic Regression-Based IDS for IoT-Enabled FANET to Detect Cyberattacks". Mobile Information Systems 2023 (29 aprile 2023): 1–11. http://dx.doi.org/10.1155/2023/7690322.

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In recent few years, flying ad hoc networks are utilized more for interconnectivity. In the topological scenario of FANETs, IoT nodes are available on ground where UAVs collect information. Due to high mobility patterns of UAVs cause disruption where intruders easily deploy cyberattacks like DoS/DDoS. Flying ad hoc networks use to have UAVs, satellite, and base station in the physical structure. IoT-based UAV networks are having many applications which include agriculture, rescue operations, tracking, and surveillance. However, DoS/DDoS attacks disturb the behaviour of entire FANET which lead to unbalance energy, end-to-end delay, and packet loss. This research study is focused about the detail study of machine learning-based IDS. Also, cognitive lightweight-LR approach is modeled using UNSW-NB 15 dataset. IoT-based UAV network is introduced using machine learning to detect possible security attacks. The queuing and data traffic model is utilized to implement DT, RF, XGBoost, AdaBoost, Bagging and logistic regression in the environment of IoT-based UAV network. Logistic regression is the proposed approach which is used to estimate statistical possibility. Overall, experimentation is based on binomial distribution. There exists linear association approach in logistic regression. In comparison with other techniques, logistic regression behaviour is lightweight and low cost. The simulation results presents logistic regression better results in contrast with other techniques. Also, high accuracy is balanced well in optimal way.

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Jennings, Jacob, Jay C. Perrett, Daniel W. Wundersitz, Courtney J. Sullivan, Stephen D. Cousins e Michael I. Kingsley. "Predicting successful draft outcome in Australian Rules football: Model sensitivity is superior in neural networks when compared to logistic regression". PLOS ONE 19, n. 2 (29 febbraio 2024): e0298743. http://dx.doi.org/10.1371/journal.pone.0298743.

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Using logistic regression and neural networks, the aim of this study was to compare model performance when predicting player draft outcome during the 2021 AFL National Draft. Physical testing, in-game movement and technical involvements were collected from 708 elite-junior Australian Rules football players during consecutive seasons. Predictive models were generated using data from 465 players (2017 to 2020). Data from 243 players were then used to prospectively predict the 2021 AFL National Draft. Logistic regression and neural network models were compared for specificity, sensitivity and accuracy using relative cut-off thresholds from 5% to 50%. Using factored and unfactored data, and a range of relative cut-off thresholds, neural networks accounted for 73% of the 40 best performing models across positional groups and data configurations. Neural networks correctly classified more drafted players than logistic regression in 88% of cases at draft rate (15%) and convergence threshold (35%). Using individual variables across thresholds, neural networks (specificity = 79 ± 13%, sensitivity = 61 ± 24%, accuracy = 76 ± 8%) were consistently superior to logistic regression (specificity = 73 ± 15%, sensitivity = 29 ± 14%, accuracy = 66 ± 11%). Where the goal is to identify talented players with draft potential, model sensitivity is paramount, and neural networks were superior to logistic regression.

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Barykin, Sergey Yevgenievich, Irina Vasilievna Kapustina, Sergey Mikhailovich Sergeev e Vladimir Konstantinovich Yadykin. "Algorithmic Foundations of Economic and Mathematical Modeling of Network Logistics Processes". Journal of Open Innovation: Technology, Market, and Complexity 6, n. 4 (13 dicembre 2020): 189. http://dx.doi.org/10.3390/joitmc6040189.

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Nowadays, digitizing the data stream is enabling the evolution of logistics processes. The data-driven network logistics processes are evaluated by leading economic indicators. The purpose of this study is to further develop the algorithmic foundations of economic and mathematical modeling of logistics networks based on advanced technologies that the digitalization process provides. Methods of mathematical modeling of flows of various resources in logistic networks, the structure of which is presented in the form of a graph, are used in the work. The economic benefit lies in the implementation of the planning concept based on leading indicators. As a result, using a set of formalisms, a mathematical model has been developed, which will make it possible to search for optimal solutions based on the criterion of economic efficiency. The results obtained will find application not only in transport problems. Network logistics includes the transportation of liquid and gaseous materials through pipelines, energy through electrical networks. A universal mathematical model will allow the results to be applied in many industries and economic activities when it is required to make economically sound decisions based on a stream of digital data coming in real time.

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Fowler, Luke. "When Need Meets Opportunity: Expanding Local Air Networks". American Review of Public Administration 48, n. 3 (1 dicembre 2016): 219–31. http://dx.doi.org/10.1177/0275074016680026.

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Although the Clean Air Act (CAA) relies on a traditional inter-government partnership, new initiatives from local governments that fall outside of the conventional implementation strategy have created a unique public service delivery network by adding layers to the implementation scheme. Using both logistic and multinomial logistic models and a data set of 497 Metropolitan (MSA) and Micropolitian (µSA) areas, this research tests a model of network membership for local governments based on internal organizational and external network factors. Findings indicate policy problems, perceptions of resource availability, network density and structure, and socio-economic and political factors affect local initiative to expand networks.

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Canestrino, Rossella, e Amir Forouharfar. "Networks and network strategies: New theorization based upon a systematic literature review". Journal of Entrepreneurship, Management and Innovation 17, n. 3 (2021): 37–66. http://dx.doi.org/10.7341/20211732.

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PURPOSE: This paper aims to introduce a general all-embracing taxonomy of networks and its relevant strategies to facilitate the teaching and learning of the strategic concepts of networks in strategic management. METHODOLOGY: To fulfill its intention, the paper has adopted a systematic literature review (SLR), since the introduced taxonomy and its corresponding strategies should be a compendious reflection and summary of the current literature of the studies on strategic networks. RESULTS: The paper unfolded seven potential configurations of the networks and then proceeded with the proposition of their relevant strategies with regard to the networks’ relationships and forms. These networks were named as Reciprocally Interdependent Networks, Sequentially Interdependent Networks, Partnering Networks, Complementary (Overlapping) Networks, Supporting (Logistic) Networks, Distributing Networks, and Co-Innovation Knowledge-Sharing Networks. Their corresponding network strategies were identified as Multi-Level Promotion Strategy, Just-In-Time Strategy, Network Partnership Strategy, Compensatory Strategy, Network Logistic Strategy, Distributing Network Strategy, and Network R&D Strategy, respectively. IMPLICATIONS FOR THEORY AND PRACTICE: Systematics or a system of classification is a fundamental necessity in any field of knowledge, benefiting both academia and learners. Accordingly, this paper provides a comprehensive but concise means of classifying networks and their strategies to overcome the paucity still existing in the literature. These efforts invite future research and conversation about networks and network strategies, proposing a guiding framework for the debate. ORIGINALITY AND VALUE: Lack of consensus about theories and conceptualizations in strategic network studies became an inspiration for this research, which allowed for the clarification of the mentioned existing paucity.

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Bányai, Tamás, Béla Illés, Christian Landschützer, Fabian Schenk e Flavien Massi. "COOPERATION IN LOGISTICS TECHNOLOGY RESEARCH: HOW TWINNING PROJECT AFFECTS R+D IN THE FIELD OF LOGISTIC SYSTEMS AND NETWORKS". Advanced Logistic Systems - Theory and Practice 12, n. 1 (25 aprile 2019): 21–36. http://dx.doi.org/10.32971/als.2019.002.

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The overall aim of the UMi-TWINN project was to reinforce the scientific excellence and innovation capacity in logistic systems of the University of Miskolc and its high-quality twinning partners for the benefit of different industries and logistics markets. To boost twinning partners' scientific excellence and innovation capacity in logistics technologies, as well as implementing a research and innovation strategy we have focused on the following three sub-topics: design of logistic systems and networks, intelligent transport systems and dynamical analysis of materials handling machines. Within the frame of this paper the authors describe the main results in the field of design of logistic systems.

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ARA, Anderson, Francisco LOUZADA e Luis Aparecido MILAN. "CLASSIFICATION BINARY MODELS FOR BIOMEDICAL DATA: SIMPLE PROBABILISTIC NETWORKS AND LOGISTIC REGRESSION". REVISTA BRASILEIRA DE BIOMETRIA 36, n. 1 (28 marzo 2018): 48. http://dx.doi.org/10.28951/rbb.v36i1.114.

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In the biomedical area a critical factor is whether a classication model is accurate enough in order to provide correct classication whether or not a patient has a certain disease. Several techniques may be used in order to accommodate such situation. In this context, Bayesian networks have emerged as a practical classication technology with successful applications in many elds. At the same time, logistic regression is a widely used statistical classication method and evidenced in the literature. In the current paper we focus on investigating the preditive performance of a probabilistic networks in its simple particular case, the so called naive Bayes network, compared to the logistic regression. A systematic simulation study is performed and the procedures are illustrated in some benchmark biomedical data sets. data sets.

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Olha, Liudmyla, Andrii, Viktoriia, Tetiana e Tetiana. "The Global Value of Distribution Networks and Logistic Opportunities". International Journal of Economics and Business Administration VIII, Special Issue 1 (1 agosto 2020): 227–38. http://dx.doi.org/10.35808/ijeba/544.

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Zekić-Sušac, Marijana, Nataša Šarlija, Adela Has e Ana Bilandžić. "Predicting company growth using logistic regression and neural networks". Croatian Operational Research Review 7, n. 2 (30 dicembre 2016): 229–48. http://dx.doi.org/10.17535/crorr.2016.0016.

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Sarraj, Rochdi, Eric Ballot, Shenle Pan, Driss Hakimi e Benoit Montreuil. "Interconnected logistic networks and protocols: simulation-based efficiency assessment". International Journal of Production Research 52, n. 11 (9 dicembre 2013): 3185–208. http://dx.doi.org/10.1080/00207543.2013.865853.

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Gan, Christopher, Visit Limsombunc, Mike Clemes e Amy Weng. "Consumer Choice Prediction: Artificial Neural Networks versus Logistic Models". Journal of Social Sciences 1, n. 4 (1 aprile 2005): 211–19. http://dx.doi.org/10.3844/jssp.2005.211.219.

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