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Relevant bibliographies by topics / Modeling and network analysis

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Academic literature on the topic 'Modeling and network analysis'

Author: Grafiati

Published: 3 June 2025

Last updated: 6 July 2025

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Journal articles on the topic "Modeling and network analysis"

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Pandey, Hemant, and Romi Bala. "Mathematical Approaches to Network Science: Modeling and Analysis." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 11, no. 1 (2020): 1668–73. http://dx.doi.org/10.61841/turcomat.v11i1.14629.

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Network science, a multidisciplinary field, employs mathematical approaches to model and analyze complex systems as networks or graphs. This paper provides an overview of the fundamental concepts, mathematical modeling techniques, analysis methods, and applications of network science. It emphasizes the importance of mathematical approaches in understanding the structure and dynamics of networks in various domains, including social, biological, and technological networks. The paper also discusses challenges such as scalability and incorporating dynamics, along with future research directions. Overall, mathematical approaches are essential for advancing network science and unlocking new insights into complex systems.

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PÜTSCH, FELIX. "ANALYSIS AND MODELING OF SCIENCE COLLABORATION NETWORKS." Advances in Complex Systems 06, no. 04 (2003): 477–85. http://dx.doi.org/10.1142/s0219525903001043.

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We analyze a science collaboration network, i.e. a network whose nodes are scientists with edges connecting them for each paper published together. Furthermore, we develop a model for the simulation of discontiguous small-world networks that shows good coherence with empirical data.

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LIU, BING, and P. S. THIAGARAJAN. "MODELING AND ANALYSIS OF BIOPATHWAYS DYNAMICS." Journal of Bioinformatics and Computational Biology 10, no. 04 (2012): 1231001. http://dx.doi.org/10.1142/s0219720012310014.

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Cellular processes are governed and coordinated by a multitude of biopathways. A pathway can be viewed as a complex network of biochemical reactions. The dynamics of this network largely determines the functioning of the pathway. Hence the modeling and analysis of biochemical networks dynamics is an important problem and is an active area of research. Here we review quantitative models of biochemical networks based on ordinary differential equations (ODEs). We mainly focus on the parameter estimation and sensitivity analysis problems and survey the current methods for tackling them. In this context we also highlight a recently developed probabilistic approximation technique using which these two problems can be considerably simplified.

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Jang, Seung Gyeong, and Hae-Deok Song. "Keyword Network and Topic Modeling Analysis of Nurse Safety Education Literature." Korean Educational Research Association 63, no. 3 (2025): 31–52. https://doi.org/10.30916/kera.63.3.31.

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의료 환경에서 환자 안전을 위한 간호사의 역할이 더욱 중요해지고 있으며, 이에 따라 효과적인 교육 전략 개발이 필수적이다. 본 연구는 키워드 네트워크 분석을 활용하여 간호사 대상 환자 안전 교육 연구의 주요 개념 및 연구 흐름을 분석하고, 교육학적 시사점을 도출하는 것을 목적으로 한다. 2010년부터 2022년까지 Web of Science, PubMed, Scopus 데이터베이스에서 간호사 안전 교육과 관련된 총 1,133건의 문헌을 검색하였으며, 최종적으로 130건을 분석 대상으로 선정하였다. 연구 분석을 위해 R 프로그램을 활용하여 문헌의 제목, 초록, 키워드를 추출하였으며, 키워드의 빈도 및 중심성을 계산하고 워드클라우드 패키지를 사용하여 시각화하였다. 또한, 키워드 네트워크 분석을 적용하여 연구 주제 간 관계를 분석하고, 네트워크 중심성 및 군집 분석을 수행하였다. 분석 결과, 시뮬레이션, 팀, 실습, 지식, 술기 등의 키워드가 주요 개념으로 도출되었다. 또한, 전문직 간 협업 교육, 간호술기 향상 훈련, 시뮬레이션 기반 사례 교육과 관련된 연구 주제가 주요 토픽으로 도출되었다. 본 연구는 간호사 대상 환자 안전 교육이 단순한 지식 전달을 넘어, 실무 중심의 체험형 학습과 협업 역량 강화의 중요성을 강조하고 있음을 시사한다. 본 연구는 간호 교육에서 효과적인 교수법 개발을 위한 기초 자료를 제공할 것으로 기대된다.

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Mimouni, Faycal, and Abdellah Abouabdellah. "Proposition of a modeling and an analysis methodology of integrated reverse logistics chain in the direct chain." Journal of Industrial Engineering and Management 9, no. 2 (2016): 359. http://dx.doi.org/10.3926/jiem.1720.

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Purpose: Propose a modeling and analysis methodology based on the combination of Bayesian networks and Petri networks of the reverse logistics integrated the direct supply chain.Design/methodology/approach: Network modeling by combining Petri and Bayesian network.Findings: Modeling with Bayesian network complimented with Petri network to break the cycle problem in the Bayesian network.Research limitations/implications: Demands are independent from returns.Practical implications: Model can only be used on nonperishable products.Social implications: Legislation aspects: Recycling laws; Protection of environment; Client satisfaction via after sale service.Originality/value: Bayesian network with a cycle combined with the Petri Network.

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Wu, Weiqiang, Ning Huang, and Zhitao Wu. "Traffic chaotic dynamics modeling and analysis of deterministic network." Modern Physics Letters B 30, no. 18 (2016): 1650285. http://dx.doi.org/10.1142/s0217984916502857.

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Network traffic is an important and direct acting factor of network reliability and performance. To understand the behaviors of network traffic, chaotic dynamics models were proposed and helped to analyze nondeterministic network a lot. The previous research thought that the chaotic dynamics behavior was caused by random factors, and the deterministic networks would not exhibit chaotic dynamics behavior because of lacking of random factors. In this paper, we first adopted chaos theory to analyze traffic data collected from a typical deterministic network testbed — avionics full duplex switched Ethernet (AFDX, a typical deterministic network) testbed, and found that the chaotic dynamics behavior also existed in deterministic network. Then in order to explore the chaos generating mechanism, we applied the mean field theory to construct the traffic dynamics equation (TDE) for deterministic network traffic modeling without any network random factors. Through studying the derived TDE, we proposed that chaotic dynamics was one of the nature properties of network traffic, and it also could be looked as the action effect of TDE control parameters. A network simulation was performed and the results verified that the network congestion resulted in the chaotic dynamics for a deterministic network, which was identical with expectation of TDE. Our research will be helpful to analyze the traffic complicated dynamics behavior for deterministic network and contribute to network reliability designing and analysis.

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Mykyjchuk, Mykola, and Nataliya Zihanshyn. "MODELING A NETWORK OF UNMANNED AERIAL VEHICLES." Measuring Equipment and Metrology 82, no. 3 (2021): 42–48. http://dx.doi.org/10.23939/istcmtm2021.03.042.

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The research concerns the methods of UAV group control in networks with duplex communication between nodes built on the "client-server" architecture. Such systems belong to self-organized networks with variable topology. It is important to study the allowable parameters of deviation from the task in the management of a group of UAVs and analysis of the network topology for the group flighting. The network was optimized according to the Ant Colony algorithm ACO. The application of different types of algorithms prevents routing problems in networks, such as ANTMANET, AntNet, ACODV and others. Methods of coordination of group joint actions are considered. A method is proposed by which the optimal number of UAVs operated by one operator can be determined and the traffic intensity of the communication channel is calculated, as well as the bandwidth and packet transmission delay are estimated.

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Cui, Yaxin, Faez Ahmed, Zhenghui Sha, et al. "A Weighted Statistical Network Modeling Approach to Product Competition Analysis." Complexity 2022 (January 4, 2022): 1–16. http://dx.doi.org/10.1155/2022/9417869.

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Statistical network models have been used to study the competition among different products and how product attributes influence customer decisions. However, in existing research using network-based approaches, product competition has been viewed as binary (i.e., whether a relationship exists or not), while in reality, the competition strength may vary among products. In this paper, we model the strength of the product competition by employing a statistical network model, with an emphasis on how product attributes affect which products are considered together and which products are ultimately purchased by customers. We first demonstrate how customers’ considerations and choices can be aggregated as weighted networks. Then, we propose a weighted network modeling approach by extending the valued exponential random graph model to investigate the effects of product features and network structures on product competition relations. The approach that consists of model construction, interpretation, and validation is presented in a step-by-step procedure. Our findings suggest that the weighted network model outperforms commonly used binary network baselines in predicting product competition as well as market share. Also, traditionally when using binary network models to study product competitions and depending on the cutoff values chosen to binarize a network, the resulting estimated customer preferences can be inconsistent. Such inconsistency in interpreting customer preferences is a downside of binary network models but can be well addressed by the proposed weighted network model. Lastly, this paper is the first attempt to study customers’ purchase preferences (i.e., aggregated choice decisions) and car competition (i.e., customers’ co-consideration decisions) together using weighted directed networks.

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P., Dr Karrupusamy. "Analysis of Neural Network Based Language Modeling." March 2020 2, no. 1 (2020): 53–63. http://dx.doi.org/10.36548/jaicn.2020.1.006.

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The fundamental and core process of the natural language processing is the language modelling usually referred as the statistical language modelling. The language modelling is also considered to be vital in the processing the natural languages as the other chores such as the completion of sentences, recognition of speech automatically, translations of the statistical machines, and generation of text and so on. The success of the viable natural language processing totally relies on the quality of the modelling of the language. In the previous spans the research field such as the linguistics, psychology, speech recognition, data compression, neuroscience, machine translation etc. As the neural network are the very good choices for having a quality language modelling the paper presents the analysis of neural networks in the modelling of the language. Utilizing some of the dataset such as the Penn Tree bank, Billion Word Benchmark and the Wiki Test the neural network models are evaluated on the basis of the word error rate, perplexity and the bilingual evaluation under study scores to identify the optimal model.

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P., Dr Karrupusamy. "Analysis of Neural Network Based Language Modeling." March 2020 2, no. 1 (2020): 53–63. http://dx.doi.org/10.36548/jaicn.2020.3.006.

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The fundamental and core process of the natural language processing is the language modelling usually referred as the statistical language modelling. The language modelling is also considered to be vital in the processing the natural languages as the other chores such as the completion of sentences, recognition of speech automatically, translations of the statistical machines, and generation of text and so on. The success of the viable natural language processing totally relies on the quality of the modelling of the language. In the previous spans the research field such as the linguistics, psychology, speech recognition, data compression, neuroscience, machine translation etc. As the neural network are the very good choices for having a quality language modelling the paper presents the analysis of neural networks in the modelling of the language. Utilizing some of the dataset such as the Penn Tree bank, Billion Word Benchmark and the Wiki Test the neural network models are evaluated on the basis of the word error rate, perplexity and the bilingual evaluation under study scores to identify the optimal model.

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Dissertations / Theses on the topic "Modeling and network analysis"

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Junuthula, Ruthwik Reddy. "Modeling, Evaluation and Analysis of Dynamic Networks for Social Network Analysis." University of Toledo / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=toledo1544819215833249.

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Bosque, Chacón Gabriel. "Network Analysis and Modeling in Systems Biology." Doctoral thesis, Universitat Politècnica de València, 2017. http://hdl.handle.net/10251/79082.

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This thesis is dedicated to the study and comprehension of biological networks at the molecular level. The objectives were to analyse their topology, integrate it in a genotype-phenotype analysis, develop richer mathematical descriptions for them, study their community structure and compare different methodologies for estimating their internal fluxes. The work presented in this document moves around three main axes. The first one is the biological. Which organisms were studied in this thesis? They range from the simplest biological agents, the viruses, in this case the Potyvirus genus to prokariotes such as Escherichia coli and complex eukariotes (Arabidopsis thaliana, Nicotiana benthamiana). The second axis refers to which biological networks were studied. Those are protein-protein interaction (PPIN) and metabolic networks (MN). The final axis relates to the mathematical and modelling tools used to generate knowledge from those networks. These tools can be classify in three main branches: graph theory, constraint-based modelling and multivariate statistics. The document is structured in six parts. The first part states the justification for the thesis, exposes a general thesis roadmap and enumerates its main contributions. In the second part important literature is reviewed, summarized and integrated. From the birth and development of Systems Biology to one of its most popular branches: biological network analysis. Particular focus is put on PPIN and MN and their structure, representations and features. Finally a general overview of the mathematical tools used is presented. The third, fourth and fifth parts represent the central work of this thesis. They deal respectively with genotypephenotype interaction and classical network analysis, constraint-based modelling methods comparison and modelling metabolic networks and community structure. Finally, in the sixth part the main conclusions of the thesis are summarized and enumerated. This thesis highlights the vital importance of studying biological entities as systems and how powerful and promising this integrated analysis is. Particularly, network analysis becomes a fundamental avenue of research to gain insight into those biological systems and to extract, integrate and display this new information. It generates knowledge from just data.<br>Esta tesis está dedicada al estudio y comprensión de redes biológicas a nivel molecular. Los objetivos fueron analizar su topología, integrar esta en un análisis de genotipo-fenotipo, desarrollar descripciones matemáticas más completas para ellas, estudiar su estructura de comunidades y comparar diferentes metodologías para estimar sus flujos internos. El trabajo presentado en este documento gira entorno a tres ejes principales. El primero es el biológico. ¿Qué organismos han sido estudiados en esta tesis? Estos van desde los agentes biológicos mas simples, los virus, en este caso el género Potyvirus, hasta procariotas como Escherichia coli y eucariotas complejos (Arabidopsis thaliana, Nicotiana benthamiana). El segundo eje hace referencia a las redes biológicas estudiadas, que fueron redes de interacción de proteínas (PPIN) y redes metabólicas (MN). El eje final es el de las herramientas matemáticas y de modelización empleadas para interrogar esas redes. Estas herramientas pueden clasificarse en tres grandes grupos: teoría de grafos, modelización basada en restricciones y estadística multivariante. Este documento está estructurado en seis partes. La primera expone la justificación para la tesis, muestra un mapa visual de la misma y enumera sus contribuciones principales. En la segunda parte, la bibliografía relevante es revisada y resumida. Desde el nacimiento y desarrollo de la Biología de Sistemas hasta una de sus ramas más populares: el análisis de redes biomoleculares. Especial interés es puesto en PPIN y MN: su estructura, representación y características. Finalmente, un resumen general de las herramientas matemáticas usadas es presentado. Los capítulos tercero, cuarto y quinto representan el cuerpo central de esta tesis. Estos tratan respectivamente sobre la interacción de genotipo-fenotipo y análisis topolólogico clásico de redes, modelos basados en restricciones y modelización de redes metabólicas y su estructura de comunidades. Finalmente, en la sexta parte las principales conclusiones de la tesis son resumidas y expuestas. Esta tesis pone énfasis en la vital importancia de estudiar los fenómenos biológicos como sistemas y en la potencia y prometedor futuro de este análisis integrativo. En concreto el análisis de redes supone un camino de investigación fundamental para obtener conocimiento sobre estos sistemas biológicos y para extraer y mostrar información sobre los mismos. Este análisis genera conocimiento partiendo únicamente desde datos.<br>Aquesta tesi està dedicada a l'estudi i comprensió de xarxes biològiques a nivell molecular. Els objectius van ser analitzar la seva topologia, integrar aquesta en una anàlisi de genotip-fenotip, desenvolupar descripcions matemàtiques més completes per a elles, estudiar la seva estructura de comunitats o modularitat i comparar diferents metodologies per estimar els fluxos interns. El treball presentat en aquest document gira entorn de tres eixos principals. El primer és el biològic. ¿Què organismes han estat estudiats en aquesta tesi? Aquests van des dels agents biològics mes simples, els virus, en aquest cas el gènere Potyvirus, fins procariotes com Escherichia coli i eucariotes complexos (Arabidopsis thaliana, Nicotiana benthamiana). El segon eix fa referència a les xarxes biològiques estudiades, que van ser les xarxes d'interacció de proteïnes (PPIN) i les xarxes metabòliques (MN). L'eix final és el de les eines matemàtiques i de modelització emprades per interrogar aquestes xarxes. Aquestes eines poden classificarse en tres grans grups: teoria de grafs, modelització basada en restriccions i estadística multivariant. Aquest document està estructurat en sis parts. La primera exposa la justificació per a la tesi, mostra un mapa visual de la mateixa i enumera les seves contribucions principals. A la segona part, la bibliografia rellevant és revisada i resumida. Des del naixement i desenvolupament de la Biologia de Sistemes fins a una de les seves branques més populars: l'anàlisi de xarxes moleculars. Especial interès és posat en PPIN i MN: la seva estructura, representació i característiques. Finalment, un resum general de les eines matemàtiques utilitzades és presentat. Els capítols tercer, quart i cinquè representen el cos central d'aquesta tesi. Aquests tracten respectivament sobre la interacció de genotip-fenotip i anàlisi topolólogico clàssic de xarxes, models basats en restriccions i modelització de xarxes metabòliques i la seva estructura de comunitats. Finalment, en la sisena part les principals conclusions de la tesi són resumides i exposades. Aquesta tesi posa èmfasi en la vital importància d'estudiar els fenòmens biològics com sistemes i en la potència i prometedor futur d'aquesta anàlisi integratiu. En concret l'anàlisi de xarxes suposa un camí d'investigació fonamental per obtenir coneixement sobre aquests sistemes biològics i per extreure i mostrar informació sobre els mateixos. Aquest anàlisi genera coneixement partint únicament des de dades.<br>Bosque Chacón, G. (2017). Network Analysis and Modeling in Systems Biology [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/79082<br>TESIS

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FERRERO, RENATO. "Network Modeling and Interference Analysis in Pervasive Technology." Doctoral thesis, Politecnico di Torino, 2012. http://hdl.handle.net/11583/2496150.

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Pervasive computing aims to create environments where the technology is invisibly integrated into. This vision is realized by means of wireless networks, i.e. cheap and small pervasively distributed devices which communicate wireless. Nowadays, these technologies are widely employed for several applications, such as accurate area monitoring and distributed information systems, where the information is directly matched to the items. The strength of a wireless network is the cooperation among nodes: in order to perform its task, a node relies on the information exchanged with other nodes. The nodes and the links of a wireless networks are easily modeled by a family of graphs called unit disk graph (UDG). The degree distribution of a unit disk graph is an important aspect for investigating the behavior of a wireless network. In the literature, several studies was focused on the degree distribution of unit disk graphs, but they lacked in precision. In Chapter 1, the degree distribution is studied with the inclusion of border effects. The achieved results are validated through simulations and compared to the state-of-the-art approaches. RFID technology is a key component in the implementation of pervasive computing. An RFID system consists of small tags containing a microchip and an antenna, readers to acquire data stored in the tags by means of radio frequency signals, and a back-end server for data processing and storage. Due to low production cost, the majority of RFID systems exploits passive tags, i.e. tags without a battery. Their simple integrated circuit is fed by the electromagnetic field emitted by the readers: passive tags operate only in response to a reader interrogation. By means of their automatic identification, physical objects can be easily mapped in an information system. Interferences among readers and tags may prevent communication. Two types of collision can be generated: the reader-to-tag collision, where a tag in the intersection of the interrogation zones of two readers is simultaneously queried by both of them, and the reader-to-reader collision, where two readers disturb each other if they are located within a specific distance called interference range. There are two types of reader collision: reader-to-tag and reader-to-reader collision. The reader-to-tag collision involves readers whose reading areas overlap. They could try to query the same tag at the same time. Although they use different frequency bands, none of them can identify the tag, since the tag has no filtering capabilities. The reader-to-reader collision prevents a reader from correctly identify tags due to the concomitant transmission of another reader. In this case, the weak response of the tags is distorted by the stronger signal of the other reader. An evaluation of the reader-to-reader collisions is often based on simple models that consider only direct collisions among two readers, like for example the unit disk graph model. Instead, more complex models capture the total signal power emitted by each reader and assume that the power of each signal decays as distance grows. Chapter 2 describes the main models of the two families and compare their accuracy. Many protocols have been proposed to reduce reader-to-reader collisions in RFID systems. The majority of them exploits Carrier Sense Multiple Access (CSMA) or Time Division Multiple Access (TDMA) scheme. Chapter 3 describes the main state-of-the-art approaches and the most effective criteria for their performance evaluation. A distinction among the protocols can be introduced according to their requirements: beside the protocols that are characterized by limited requirements, there are other protocols that require an advanced communication system. Two popular state-of-the-art TDMA protocols that use only one data channel are DCS and Colorwave. A relevant quality of DCS is its fairness, due to the opportunity to reserve a timeslot for the nodes that experience a reader-to-reader collision. Colorwave represents an evolution of DCS, and its main novelty is the introduction of an adaptable parameter. Colorwave maximizes the network throughput, since the readers with few neighbors communicate more often than the ones in denser areas. Moreover, Colorwave is suitable for networks with mobile readers, because it can manage deployment changes, avoiding performance loss. In Chapter 4, three different protocols are proposed, adopting the basic mechanisms common to DCS and Colorwave, and without introducing any additional requirements. Probabilistic Distributed Color Selection (PDCS) introduces in the collision resolution of DCS an additional parameter p, representing the probability of adopting a different behavior after the detection of a collision. Consequently, the number of collisions decreases. Moreover, this protocol allows a multichannel transmission, according to the international RFID regulations. Distributed Color Natural Selection (DCNS) is specifically developed in order to exploit a new configuration, called the Killer configuration. The goal of the proposed configuration is to generate a selfish behavior similar to the natural selection. As a result, the throughput of the network improves and the largest benefit can be get by the RFID readers chosen according to the application specification. Probabilistic Colorwave (PCW) introduces a probabilistic parameter in the collision resolution routine of Colorwave. The effects of this factor are analyzed for two different configurations: the one adopted by Colorwave and the killer configuration adopted by DCNS. With respect to the TDMA protocols that exploits one additional control channel, NFRA provides an optimal management of the readers inside the interference range (neighborhood). However, two drawbacks can be identified in this algorithm. First of all, the algorithm maximizes the throughput, privileging readers with a limited neighborhood, since they have lower probability to be overridden by close transmission. As a consequence, their frequent queries could prevent readers with a larger neighborhood from communicating. To schedule the readers for transmitting, the algorithm assigns to disabled readers the same priority of transmitting ones, so during long executions there may be significant differences among the transmissions performed by each reader. Secondly, some hardware assumptions make the implementation of NFRA in passive RFID systems hard. Two different approaches are described in Chapter 5 in order to mitigate the main drawbacks of NFRA. NFRA++ includes two techniques to improve both the fairness and the throughput of NFRA. Geometric Distribution Reader Anticollision (GDRA) exploits the Sift geometric probability distribution function to minimize reader collision problems. GDRA shows better performance than NFRA, it can be implemented in a real DRE without extra hardware and it is compliant with EPC-ETSI requirements.

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Sung, Woong Je. "A neural network construction method for surrogate modeling of physics-based analysis." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/43721.

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A connectivity adjusting learning algorithm, Optimal Brain Growth (OBG) was proposed. Contrast to the conventional training methods for the Artificial Neural Network (ANN) which focus on the weight-only optimization, the OBG method trains both weights and connectivity of a network in a single training process. The standard Back-Propagation (BP) algorithm was extended to exploit the error gradient information of the latent connection whose current weight has zero value. Based on this, the OBG algorithm makes a rational decision between a further adjustment of an existing connection weight and a creation of a new connection having zero weight. The training efficiency of a growing network is maintained by freezing stabilized connections in the further optimization process. A stabilized computational unit is also decomposed into two units and a particular set of decomposition rules guarantees a seamless local re-initialization of a training trajectory. The OBG method was tested for the multiple canonical, regression and classification problems and for a surrogate modeling of the pressure distribution on transonic airfoils. The OBG method showed an improved learning capability in computationally efficient manner compared to the conventional weight-only training using connectivity-fixed Multilayer Perceptrons (MLPs).

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Park, Pangun. "Modeling, Analysis and Design of Wireless Sensor Network Protocols." Doctoral thesis, KTH, Reglerteknik, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-29821.

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Wireless sensor networks (WSNs) have a tremendous potential to improve the efficiencyof many systems, for instance, in building automation and process control.Unfortunately, the current technology does not offer guaranteed energy efficiencyand reliability for closed-loop stability. The main contribution of this thesis is toprovide a modeling, analysis, and design framework for WSN protocols used in controlapplications. The protocols are designed to minimize the energy consumption ofthe network, while meeting reliability and delay requirements from the applicationlayer. The design relies on the analytical modeling of the protocol behavior.First, modeling of the slotted random access scheme of the IEEE 802.15.4medium access control (MAC) is investigated. For this protocol, which is commonlyemployed in WSN applications, a Markov chain model is used to derive theanalytical expressions of reliability, delay, and energy consumption. By using thismodel, an adaptive IEEE 802.15.4 MAC protocol is proposed. The protocol designis based on a constrained optimization problem where the objective function is theenergy consumption of the network, subject to constraints on reliability and packetdelay. The protocol is implemented and experimentally evaluated on a test-bed. Experimentalresults show that the proposed algorithm satisfies reliability and delayrequirements while ensuring a longer lifetime of the network under both stationaryand transient network conditions.Second, modeling and analysis of a hybrid IEEE 802.15.4 MAC combining theadvantages of a random access with contention with a time division multiple access(TDMA) without contention are presented. A Markov chain is used to model thestochastic behavior of random access and the deterministic behavior of TDMA.The model is validated by both theoretical analysis and Monte Carlo simulations.Using this new model, the network performance in terms of reliability, averagepacket delay, average queueing delay, and throughput is evaluated. It is shown thatthe probability density function of the number of received packets per superframefollows a Poisson distribution. Furthermore, it is determined under which conditionsthe time slot allocation mechanism of the IEEE 802.15.4 MAC is stable.Third, a new protocol for control applications, denoted Breath, is proposedwhere sensor nodes transmit information via multi-hop routing to a sink node. Theprotocol is based on the modeling of randomized routing, MAC, and duty-cycling.Analytical and experimental results show that Breath meets reliability and delayrequirements while exhibiting a nearly uniform distribution of the work load. TheBreath protocol has been implemented and experimentally evaluated on a test-bed.Finally, it is shown how the proposed WSN protocols can be used in controlapplications. A co-design between communication and control application layers isstudied by considering a constrained optimization problem, for which the objectivefunction is the energy consumption of the network and the constraints are thereliability and delay derived from the control cost. It is shown that the optimaltraffic load when either the communication throughput or control cost are optimizedis similar.<br>QC 20110217

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Paothong, Arnut. "Dynamic Processes in Network Goods: Modeling, Analysis and Applications." Scholar Commons, 2013. http://scholarcommons.usf.edu/etd/4558.

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The network externality function plays a very important role in the study of economic network industries. Moreover, the consumer group dynamic interactions coupled with network externality concept is going to play a dominant role in the network goods in the 21st century. The existing literature is stemmed on a choice of externality function with certain quantitative properties. The utility function coupled with the network externality function is used to investigate static properties of rational equilibrium. The aim of this work is to systematically initiate a development of quantitative effects of the concept of network externality and its influence on the characteristics of network market equilibrium. We introduce several basic concepts, notably, network externality process and network goods. Formulating a principle of network externality, we developed a mathematical dynamic model (1) for the network externality process. A closed form solution of the mathematical model was determined and analyzed (2). The presented qualitative and quantitative analysis provides a systematic and unified way of constructing the existing network externality function. The solution process is called "Generalized Network Externality Function (GNEF)". Moreover, our study of quantitative description, parametric representation of attributes and sensitivity analysis of network externality process provides a tool for planning, policy and performance for network goods (3). In the absence of desired data set, we presented an illustration to exhibit the significance of GNEF. We used two types of data sets on the US banking asset and deposit. Employing nonlinear regression methods and data sets, we developed statistical models for the US banking asset and deposit, and constructed two normalized the US banking deposit models (4). Finally, using the concept of theory of relative growth and GNEF (4), we developed two dynamic models for the network externality for the US banking asset with respect to the US banking deposit as a financial market share (5). Incorporating the GNEF (2) in the consumer utility function, a concept of market share adjustment function is introduced and utilized to develop dynamic models for existing rational and static expectation processes (6). In fact, the role and scope of dynamic models of market share adjustment process are extended to the well-known adaptive expectation and its extension process (7). Using a fixed point theorem and the method of upper and lower solutions of discrete time processes, the existence of equilibrium states of developed dynamic models of market share adjustment processes are established in a systematic way (8). Furthermore, the qualitative properties (stability and oscillatory) of equilibrium states are investigated in terms of model and speed of adjustment parameters. Moreover, the system parameter space is decomposed according to qualitative properties (stability, instability and oscillatory) and the type of expectation processes. Very recently, the idea of local network externality is utilized to characterize the rational equilibrium (under fulfilled expectation assumptions). From the study on two-scale network dynamic model of human mobility process an eco-socio-culture interactions, we note that heterogeneity in the network goods consumer community generates a local network externality. Furthermore, dynamic models of adaptive expectation processes (6,7) for network goods provide tool to extend the characterization of rational equilibrium study to static, current and lagged adaptive types equilibriums. Here, we treat the consumer decision to be a dynamic process. We formulate a dynamic structural representation of a consumer network structure, structure of utility function and decision rule under the influence of local network externality concept (9). For the consumer network structure, we generalize the one-dimensional Hotelling location line model to multi-dimensional location (10). This formulation generates a mathematical model for a consumer decision dynamic process (11). The byproduct of the dynamic model leads to an agent-based simulation model (12). The simulation model is employed to investigate different types of consumer decision dynamic market equilibriums. Moreover, prototype illustrations are given to exhibit the association between network attributes and its market equilibriums. We extend the work of two firms (duopoly) into multi-firms (oligopoly and monopolistic competition). This work shed light on the policies for manager to meet performance goal of their firm in network goods industry. In future, we propose to extend this work to incorporate random fluctuations, to remove restrictions and the local and global economic framework in the 21st century.

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Abuaitah, Giovani Rimon. "ANOMALIES IN SENSOR NETWORK DEPLOYMENTS: ANALYSIS, MODELING, AND DETECTION." Wright State University / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=wright1376594068.

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Al-Omari, Huthaifa Abdelhameed. "Analysis and Modeling of One-Way Network Delay Variations." Cleveland, Ohio : Case Western Reserve University, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=case1244058771.

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Thesis (Ph.D.)--Case Western Reserve University, 2009<br>Title from PDF (viewed on 19 August 2009) Department of Electrical Engineering and Computer Science Includes abstract Includes bibliographical references Available online via the OhioLINK ETD Center

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Maitra, Arindam. "A generic approach to network modeling for harmonic analysis." Diss., Mississippi State : Mississippi State University, 2002. http://library.msstate.edu/etd/show.asp?etd=etd-03272002-133910.

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Koh, Jin Hou. "Simulation modeling and analysis of device-aware network architectures." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2004. http://library.nps.navy.mil/uhtbin/hyperion/04Dec%5FKoh.pdf.

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Books on the topic "Modeling and network analysis"

1

1926-, Garzia Ricardo F., and Garzia Mario R. 1955-, eds. Network modeling, simulation, and analysis. M. Dekker, 1990.

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Mohsen, Guizani, ed. Network modeling and simulation: A practical perspective. Wiley, 2010.

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Guizani, Mohsen. Network modeling and simulation: A practical perspective. Wiley, 2010.

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Wehrle, Klaus. Modeling and Tools for Network Simulation. Springer-Verlag Berlin Heidelberg, 2010.

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A, Edwards Jerry, and Willnow Lindle D, eds. Computer modeling of water distribution systems. American Water Works Association, 2012.

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Gaver, Donald Paul. Defense Data Network (DDN) performance analysis using probability modeling. Naval Postgraduate School, 1990.

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Mathis, Philippe. Graphs and networks: Multilevel modeling. 2nd ed. J. Wiley & Sons, 2010.

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Philippe, Mathis, ed. Graphs and networks: Multilevel modeling. 2nd ed. J. Wiley & Sons, 2010.

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Philippe, Mathis, ed. Graphs and networks: Multilevel modeling. 2nd ed. J. Wiley & Sons, 2010.

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Bell, Michael. Service-oriented modeling: Service analysis, design, and architecture. John Wiley & Sons, 2008.

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Book chapters on the topic "Modeling and network analysis"

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Gebali, Fayez. "Modeling Network Traffic." In Analysis of Computer Networks. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-15657-6_15.

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Gebali, Fayez. "Modeling Network Traffic." In Analysis of Computer and Communication Networks. Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-74437-7_11.

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Xu, Kuai. "Behavior Modeling of Network Traffic." In Network Behavior Analysis. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-8325-1_3.

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Xu, Kuai. "Structural Modeling of Network Traffic." In Network Behavior Analysis. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-8325-1_4.

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Xu, Kuai. "Graphical Modeling of Network Traffic." In Network Behavior Analysis. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-8325-1_5.

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Hills, Thomas. "Investigating Mathematical Search Behavior Using Network Analysis." In Modeling Students' Mathematical Modeling Competencies. Springer US, 2009. http://dx.doi.org/10.1007/978-1-4419-0561-1_50.

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DeLaurentis, Daniel A., Kushal Moolchandani, and Cesare Guariniello. "Network Theory." In System of Systems Modeling and Analysis. CRC Press, 2022. http://dx.doi.org/10.1201/9781003231011-7.

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Abboud, Khadige, and Weihua Zhuang. "Spatiotemporal Network Topology Analysis." In Mobility Modeling for Vehicular Communication Networks. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-25507-1_4.

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Janowski, Sebastian Jan, Barbara Kaltschmidt, and Christian Kaltschmidt. "Biological Network Modeling and Analysis." In Approaches in Integrative Bioinformatics. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-41281-3_8.

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Antonelli, Dario, and Giulia Bruno. "Healthcare Network Modeling and Analysis." In Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-662-44745-1_68.

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Conference papers on the topic "Modeling and network analysis"

1

Huong Giang, Hoang Thi, Kohei Shiomoto, Tatsuya Otoshi, and Masayuki Murata. "Adapting Topic Modeling for Network Behavior Analysis." In 2025 IEEE 26th International Conference on High Performance Switching and Routing (HPSR). IEEE, 2025. https://doi.org/10.1109/hpsr64165.2025.11038863.

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Doma, Vikrant, Fletcher Trueblood, Parneet Saran, and Matin Pirouz. "Towards Using Network Analysis for Brain Anomaly Modeling." In 2025 IEEE 15th Annual Computing and Communication Workshop and Conference (CCWC). IEEE, 2025. https://doi.org/10.1109/ccwc62904.2025.10903701.

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Islam, Md Tariqul, and Christian Esteve Rothenberg. "QoE Evaluation for Emerging Media Applications: Network-Level Analysis and Traffic Modeling." In 2024 IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN). IEEE, 2024. https://doi.org/10.1109/nfv-sdn61811.2024.10807495.

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Policroniades Chípuli, G., I. Flores de la Mota, J. Lara de Paz, and O. S. Shirai Reyna. "VRP complex network analysis and simulation." In THE EUROPEAN MODELING AND SIMULATION SYMPOSIUM. CAL-TEK srl, 2019. http://dx.doi.org/10.46354/i3m.2019.emss.048.

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Adjabi, Smail, and Karima Lagha. "Performance evaluation of a tandem queueing network." In Recent Advances in Stochastic Modeling and Data Analysis. WORLD SCIENTIFIC, 2007. http://dx.doi.org/10.1142/9789812709691_0074.

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Yu, Wenchao, Charu C. Aggarwal, and Wei Wang. "Temporally Factorized Network Modeling for Evolutionary Network Analysis." In WSDM 2017: Tenth ACM International Conference on Web Search and Data Mining. ACM, 2017. http://dx.doi.org/10.1145/3018661.3018669.

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Durr, M., V. Protschky, and C. Linnhoff-Popien. "Modeling Social Network Interaction Graphs." In 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012). IEEE, 2012. http://dx.doi.org/10.1109/asonam.2012.110.

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Wang, Liqian, and Xue Chen. "Network Reliability Modeling and Analysis of Passive Optical Networks." In 2009 WRI International Conference on Communications and Mobile Computing (CMC). IEEE, 2009. http://dx.doi.org/10.1109/cmc.2009.79.

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Shirai Reyna, O. S., and I. Flores de la Mota. "Complex network analysis: Mexico's City metro system." In THE EUROPEAN MODELING AND SIMULATION SYMPOSIUM. CAL-TEK srl, 2019. http://dx.doi.org/10.46354/i3m.2019.emss.022.

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Yager, Ronald R. "Intelligent social network modeling and analysis." In 2008 3rd International Conference on Intelligent System and Knowledge Engineering (ISKE 2008). IEEE, 2008. http://dx.doi.org/10.1109/iske.2008.4730886.

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Reports on the topic "Modeling and network analysis"

1

Snijders, Tom. Longitudinal Social Network Analysis. Instats Inc., 2024. https://doi.org/10.61700/zimra7qjrsnu11850.

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This three-day workshop provides an introductory overview of longitudinal social network analysis using the RSiena package, focusing on the application of Stochastic Actor-oriented Models to study network dynamics and the co-evolution of networks and behavior. Participants will gain practical skills in modeling network panel data, as well as modeling co-evolution of networks and behavior, for application of these techniques across various academic disciplines.

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Lawton, Craig R., James E. Dr Campbell, .), Dennis James Anderson, and John P. Eddy. Network and adaptive system of systems modeling and analysis. Office of Scientific and Technical Information (OSTI), 2007. http://dx.doi.org/10.2172/908063.

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Boakye, K., P. Kidwell, G. Konjevod, and J. Lenderman. Literature review for vehicle correspondence and network modeling and analysis. Office of Scientific and Technical Information (OSTI), 2015. http://dx.doi.org/10.2172/1236136.

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Hossain, Niamat Ullah Ibne, Raed Jaradat, Seyedmohsen Hosseini, Mohammad Marufuzzaman, and Randy Buchanan. A framework for modeling and assessing system resilience using a Bayesian network : a case study of an interdependent electrical infrastructure systems. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/40299.

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This research utilizes Bayesian network to address a range of possible risks to the electrical power system and its interdependent networks (EIN) and offers possible options to mitigate the consequences of a disruption. The interdependent electrical infrastructure system in Washington, D.C. is used as a case study to quantify the resilience using the Bayesian network. Quantification of resilience is further analyzed based on different types of analysis such as forward propagation, backward propagation, sensitivity analysis, and information theory. The general insight drawn from these analyses indicate that reliability, backup power source, and resource restoration are the prime factors contributed towards enhancing the resilience of an interdependent electrical infrastructure system.

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Rehrer, Sarah, Andrew Griffin, and Matthew Renner. Cross country mobility (CCM) modeling using triangulated irregular networks (TIN). Engineer Research and Development Center (U.S.), 2022. http://dx.doi.org/10.21079/11681/46082.

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Cross country mobility (CCM) models terrain that has insufficient or unavailable infrastructure for crossing. This historically has been done with either hand-drawn and estimated maps or with raster-based terrain analysis, both of which have their own strengths and weaknesses. In this report the authors explore the possibility of using triangulated irregular networks (TINs) as a means of representing terrain characteristics used in CCM and discuss the possibilities of using such networks for routing capabilities in lieu of a traditional road-based network. The factors used to calculate CCM are modified from previous methods to capture a more accurate measurement of terrain characteristics. Using a TIN to store and represent CCM information achieves comparable results to raster cost analysis with the additional benefits of an integrated network useful for visualization and routing and a reduction in the number of related files. Additionally, TINs can in some cases more accurately show the contours of the landscape and reveal feature details or impediments that may be lost within a raster, thus improving the quality of CCM overlays.

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Hertel, Thomas. Future Directions in Global Trade Analysis. GTAP Working Paper, 2000. http://dx.doi.org/10.21642/gtap.wp04.

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This paper discusses future directions in global trade analysis from the perspective of the Global Trade Analysis Project (GTAP) network. The first section offers a projection of where the GTAP network might be in the year 2010. This is followed by an analysis of the basic drivers of change in global trade analysis. These include: network externalities and the push for greater openness in both modeling and database work. The second half of the paper revisits John Whalley's "Hidden Challenges" for applied general equilibrium analysis, discussing how well we have fared with respect to these challenges, first posed in 1986. The paper closes with some additional challenges for global trade analysis in the coming decade.

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Pepyne, David L., and Yu-Chi Ho. Modeling and Analysis of Information Attack in Computer Networks. Defense Technical Information Center, 2003. http://dx.doi.org/10.21236/ada416393.

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Hertel, Thomas. Global Applied General Equilibrium Analysis using the GTAP Framework. GTAP Working Paper, 2012. http://dx.doi.org/10.21642/gtap.wp66.

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Contributed Chapter for Peter B. Dixon and Dale W. Jorgenson (eds.) This chapter provides an overview of the first two decades of the Global Trade Analysis Project (GTAP) – an effort to support a standardized data base and CGE modeling platform for international economic analysis. It characterizes GTAP in four different dimensions: institutional innovation, a network, a database and a standardized modeling platform. Guiding principles for the GTAP modeling framework include flexibility, ease of use, transparency, and symmetric treatment of production and utility fundamentals across regions. The chapter reviews core modeling assumptions relating to the regional household, private consumption behavior, welfare decomposition, the “global bank”, treatment of the international trade and transport sector, and imports. Model validation and sensitivity analysis, as well as software issues receive attention as well. The chapter also offers brief overviews of the two major areas of application: international economic integration and global environmental issues. It closes with a discussion of future directions for the Project.

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AMMERMAN, C., and J. BERNARDIN. DESIGN AND ANALYSIS OF THE SNS CCL HOT MODEL WATER COOLING SYSTEM USING THE SINDA/FLUINT NETWORK MODELING TOOL. Office of Scientific and Technical Information (OSTI), 1999. http://dx.doi.org/10.2172/772944.

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Mayo, Jackson R., and Robert C. Armstrong. Notes on "Modeling, simulation and analysis of complex networked systems". Office of Scientific and Technical Information (OSTI), 2009. http://dx.doi.org/10.2172/984134.

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