Literatura científica selecionada sobre o tema "Agglomeration kernel"
Crie uma referência precisa em APA, MLA, Chicago, Harvard, e outros estilos
Consulte a lista de atuais artigos, livros, teses, anais de congressos e outras fontes científicas relevantes para o tema "Agglomeration kernel".
Ao lado de cada fonte na lista de referências, há um botão "Adicionar à bibliografia". Clique e geraremos automaticamente a citação bibliográfica do trabalho escolhido no estilo de citação de que você precisa: APA, MLA, Harvard, Chicago, Vancouver, etc.
Você também pode baixar o texto completo da publicação científica em formato .pdf e ler o resumo do trabalho online se estiver presente nos metadados.
Artigos de revistas sobre o assunto "Agglomeration kernel"
Li, Qiang, Xin Yuan, Meng Zhang, Weiwei Xu, Liming Huo e Qingkai Mu. "A modified agglomeration kernel model used for particle agglomeration". Advanced Powder Technology 33, n.º 1 (janeiro de 2022): 103349. http://dx.doi.org/10.1016/j.apt.2021.11.001.
Texto completo da fonteCronin, Kevin, e Francisco Javier Gutiérrez Ortiz. "The Evolution of Variance and Entropy of the Granule Size Distribution in Fluidized Bed Agglomeration". Processes 11, n.º 8 (26 de julho de 2023): 2247. http://dx.doi.org/10.3390/pr11082247.
Texto completo da fonteLiu, Zhonglan, e Yuanyuan Bao. "Spatial and Temporal Divergence of Water Resource Carrying Capacity in Hubei Province, China, from the Perspective of Three Major Urban Agglomerations". Sustainability 16, n.º 12 (14 de junho de 2024): 5059. http://dx.doi.org/10.3390/su16125059.
Texto completo da fonteLu, Hao, e Jie Bao. "Spatial Differentiation Effect of Rural Logistics in Urban Agglomerations in China Based on the Fuzzy Neural Network". Sustainability 14, n.º 15 (28 de julho de 2022): 9268. http://dx.doi.org/10.3390/su14159268.
Texto completo da fonteWang, Yi. "The Spatiotemporal Evolution and Influencing Factors of Urban Economic Resilience in the Yangtze River Delta Urban Agglomeration". Frontiers in Business, Economics and Management 5, n.º 3 (19 de outubro de 2022): 293–300. http://dx.doi.org/10.54097/fbem.v5i3.2039.
Texto completo da fonteGolovin, Ievgen, Gerd Strenzke, Robert Dürr, Stefan Palis, Andreas Bück, Evangelos Tsotsas e Achim Kienle. "Parameter Identification For Continuous Fluidized Bed Spray Agglomeration". Processes 6, n.º 12 (30 de novembro de 2018): 246. http://dx.doi.org/10.3390/pr6120246.
Texto completo da fonteOtto, Eric, Anton Maksakov, Robert Diirr, Stefan Palis e Achim Kienle. "Direct Discretized Kernel Identification for Continuous Agglomeration Processes". IFAC-PapersOnLine 55, n.º 7 (2022): 260–65. http://dx.doi.org/10.1016/j.ifacol.2022.07.454.
Texto completo da fonteZhong, Yang, Aiwen Lin, Chiwei Xiao e Zhigao Zhou. "Research on the Spatio-Temporal Dynamic Evolution Characteristics and Influencing Factors of Electrical Power Consumption in Three Urban Agglomerations of Yangtze River Economic Belt, China Based on DMSP/OLS Night Light Data". Remote Sensing 13, n.º 6 (17 de março de 2021): 1150. http://dx.doi.org/10.3390/rs13061150.
Texto completo da fonteMoseley, James L. "The discrete agglomeration model with a time-varying kernel". Nonlinear Analysis: Real World Applications 8, n.º 2 (abril de 2007): 405–23. http://dx.doi.org/10.1016/j.nonrwa.2005.12.001.
Texto completo da fonteLiu, Fei, Genyu Zhang, Chenghao Li, Tao Ren e Donato Masi. "Analysis of the Temporal and Spatial Pattern and Convergence Characteristics of High-Quality Sustainable Economic Development of Urban Agglomeration". Sustainability 15, n.º 20 (12 de outubro de 2023): 14807. http://dx.doi.org/10.3390/su152014807.
Texto completo da fonteTeses / dissertações sobre o assunto "Agglomeration kernel"
ACCETTURO, ANTONIO. "Saggi su geografia e crescita". Doctoral thesis, Università Cattolica del Sacro Cuore, 2007. http://hdl.handle.net/10280/110.
Texto completo da fonteI present one empirical and two theoretical models on the relationship between geography and growth. in the empirical paper, I present some stylized facts on the evolution of the spatial concentration of innovative activities in Italy in the period 1971-2001. Using markov-based non parametric techniques, I show that spatial concentration decreased but regional specialization is highly persistent. in the first theoretical paper, I present a model of romerian growth and industrial location characterized by congestion costs. I show how a process of agglomeration and divergence might be reverted once trade integration deepens. in the second theoretical paper, I show how usual predictions of the geography and growth models apply to a Schumpeterian growth model.
ACCETTURO, ANTONIO. "Saggi su geografia e crescita". Doctoral thesis, Università Cattolica del Sacro Cuore, 2007. http://hdl.handle.net/10280/110.
Texto completo da fonteI present one empirical and two theoretical models on the relationship between geography and growth. in the empirical paper, I present some stylized facts on the evolution of the spatial concentration of innovative activities in Italy in the period 1971-2001. Using markov-based non parametric techniques, I show that spatial concentration decreased but regional specialization is highly persistent. in the first theoretical paper, I present a model of romerian growth and industrial location characterized by congestion costs. I show how a process of agglomeration and divergence might be reverted once trade integration deepens. in the second theoretical paper, I show how usual predictions of the geography and growth models apply to a Schumpeterian growth model.
Lalleman, Sophie. "Étude cinétique et physico-chimique des phénomènes d’agglomération en vue de la modélisation de la précipitation oxalique dans l’industrie nucléaire". Electronic Thesis or Diss., Université de Lorraine, 2012. http://www.theses.fr/2012LORR0426.
Texto completo da fonteDuring oxalic precipitation, three major mechanisms take place: nucleation, crystal growth and agglomeration. After the acquisition of the kinetic laws of nucleation and growth of neodymium oxalate and uranium oxalate by Andrieu (1999), the objective of this study is to determine the respective agglomeration kinetic laws. Determining the agglomeration kinetic law consists more specifically in determining a quantity called agglomeration kernel. This kernel is a measure of the frequency and efficiency of the collisions which occur between particles in the reactor. The agglomeration mechanism is complex as it is sensible to many parameters. The objective is to determine a kinetic law showing explicitly the parameters influencing the mechanism of agglomeration. Mathematical and experimental methods are firstly developed on an inactive compound (neodymium III) and then applied on uranium IV, a simulant of plutonium IV. Experiments are conducted in a perfectly mixed reactor, under operating conditions similar to the industrial ones. An original mathematical method is also developed to solve the population balance. To obtain a predictive kinetic model, it is essential to consider deviation from ideality for the calculation of supersaturation, through activity coefficients. After a thermodynamic study, the Bromley model (1973) is finally chosen to evaluate activity coefficients. The overall processing of our experimental data leads to the agglomeration kinetic laws of neodymium oxalate crystals and oxalate uranium IV over a wide range of operating conditions
Li, Na. "MMD and Ward criterion in a RKHS : application to Kernel based hierarchical agglomerative clustering". Thesis, Troyes, 2015. http://www.theses.fr/2015TROY0033/document.
Texto completo da fonteClustering, as a useful tool for unsupervised classification, is the task of grouping objects according to some measured or perceived characteristics of them and it has owned great success in exploring the hidden structure of unlabeled data sets. Kernel-based clustering algorithms have shown great prominence. They provide competitive performance compared with conventional methods owing to their ability of transforming nonlinear problem into linear ones in a higher dimensional feature space. In this work, we propose a Kernel-based Hierarchical Agglomerative Clustering algorithms (KHAC) using Ward’s criterion. Our method is induced by a recently arisen criterion called Maximum Mean Discrepancy (MMD). This criterion has firstly been proposed to measure difference between different distributions and can easily be embedded into a RKHS. Close relationships have been proved between MMD and Ward's criterion. In our KHAC method, selection of the kernel parameter and determination of the number of clusters have been studied, which provide satisfactory performance. Finally an iterative KHAC algorithm is proposed which aims at determining the optimal kernel parameter, giving a meaningful number of clusters and partitioning the data set automatically
Capítulos de livros sobre o assunto "Agglomeration kernel"
Zhong, Aijia, e Guang Yang. "Research on the Change of Land Use Agglomeration Based on Kernel Density Estimation and Hot Spot Analysis". In Proceedings of the 25th International Symposium on Advancement of Construction Management and Real Estate, 987–1003. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-3587-8_65.
Texto completo da fonteMiyamoto, Sadaaki. "Positive-Definite Kernels in Agglomerative Hierarchical Clustering". In Behaviormetrics: Quantitative Approaches to Human Behavior, 61–68. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-0420-2_4.
Texto completo da fonteTrabalhos de conferências sobre o assunto "Agglomeration kernel"
Strenzke, Gerd, Ievgen Golovin, Maximilian Wegner, Stefan Palis, Andreas Bück, Achim Kienle e Evangelos Tsotsas. "Influence of drying conditions on process properties and parameter identification for continuous fluidized bed spray agglomeration". In 21st International Drying Symposium. Valencia: Universitat Politècnica València, 2018. http://dx.doi.org/10.4995/ids2018.2018.7319.
Texto completo da fonteQing, X., W. Xin, Y. Yan e W. Long. "The aggregation rate constant of the discrete population balance model in hot melt fluidized bed coating process". In 21st International Drying Symposium. Valencia: Universitat Politècnica València, 2018. http://dx.doi.org/10.4995/ids2018.2018.7726.
Texto completo da fonteLiu, Peng, e Yi Wang. "Analysis of Agglomeration Characteristics of Public Service Facilities in Mountainous Villages and Towns Based on POI Data". In AHFE 2023 Hawaii Edition. AHFE International, 2023. http://dx.doi.org/10.54941/ahfe1004325.
Texto completo da fonteMall, Raghvendra, Rocco Langone e Johan A. K. Suykens. "Agglomerative hierarchical kernel spectral data clustering". In 2014 IEEE Symposium on Computational Intelligence and Data Mining (CIDM). IEEE, 2014. http://dx.doi.org/10.1109/cidm.2014.7008142.
Texto completo da fonte"Kernel Hierarchical Agglomerative Clustering - Comparison of Different Gap Statistics to Estimate the Number of Clusters". In International Conference on Pattern Recognition Applications and Methods. SCITEPRESS - Science and and Technology Publications, 2014. http://dx.doi.org/10.5220/0004828202550262.
Texto completo da fonteBove, Stefano, Tron Solberg e Bjo̸rn H. Hjertager. "Evaluation of the Parallel Parent and Daughter Classes Technique (PPDC) for Solving Population Balance Equations by Discretization: Aggregation and Breakage". In ASME 2004 Heat Transfer/Fluids Engineering Summer Conference. ASMEDC, 2004. http://dx.doi.org/10.1115/ht-fed2004-56726.
Texto completo da fonte