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Journal articles on the topic "ANN sizing"

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Ahmad, Fateh Mohamad Nor, Salimin Suriana, Noor Abdullah Mohd, and Nafis Ismail Muhammad. "Application of artificial neural network in sizing a stand-alone photovoltaic system: a review." International Journal of Power Electronics and Drive System (IJPEDS) 11, no. 1 (2020): 342–49. https://doi.org/10.11591/ijpeds.v11.i1.pp342-349.

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Artificial Neural Network (ANN) techniques are becoming useful in the current era due to the vast development of the current computer technologies. ANN has been used in various fields especially in the field of science and technology. One of the advantage that makes ANN so interesting is the ANN’s ability to learn the input and output relationship even though the relationship is non-linear. In addition, ANN is also useful for modelling, optimization, prediction, forecasting, and controlling systems. The main objective of this paper is to present a review of the ANN techniques for sizing a stand-alone photovoltaic (PV) system. The review in this paper shows the potential of ANN as a design tool for a stand-alone PV. In addition, ANN is very useful to improve the sizing process of the stand-alone PV system. The sizing process is of paramount importance to a stand-alone PV system in order to make sure the system can generate ample electrical energy to supply the load demand.
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Nor, Ahmad Fateh Mohamad, Suriana Salimin, Mohd Noor Abdullah, and Muhammad Nafis Ismail. "Application of artificial neural network in sizing a stand-alone photovoltaic system: a review." International Journal of Power Electronics and Drive Systems (IJPEDS) 11, no. 1 (2020): 342. http://dx.doi.org/10.11591/ijpeds.v11.i1.pp342-349.

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<span>Artificial Neural Network (ANN) techniques are becoming useful in the current era due to the vast development of the current computer technologies. ANN has been used in various fields especially in the field of science and technology. One of the advantage that makes ANN so interesting is the ANN’s ability to learn the input and output relationship even though the relationship is non-linear. In addition, ANN is also useful for modelling, optimization, prediction, forecasting, and controlling systems. The main objective of this paper is to present a review of the ANN techniques for sizing a stand-alone photovoltaic (PV) system. The review in this paper shows the potential of ANN as a design tool for a stand-alone PV. In addition, ANN is very useful to improve the sizing process of the stand-alone PV system. The sizing process is of paramount importance to a stand-alone PV system in order to make sure the system can generate ample electrical energy to supply the load demand.</span>
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Saadi, Moufida, Dib Djalel, and Kadir Erkan. "Optimization and dimensioning of stand-alone systems: enhancing MPPT efficiency through DLGA integration." International Journal of Applied Power Engineering (IJAPE) 14, no. 2 (2025): 308. https://doi.org/10.11591/ijape.v14.i2.pp308-318.

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This paper explores optimizing and sizing stand-alone solar power systems using an intelligent maximum power point tracking (MPPT) method, enhanced by artificial neural networks (ANN). The study focuses on both system sizing and energy optimization, integrating genetic algorithms (GA) with deep learning (DL) to optimize the architecture of the ANN for improved performance in predicting solar energy output. The hybrid method, deep learning genetic algorithms (DLGA), efficiently reduces computational complexity and enhances flexibility through parameter tuning, significantly improving the performance of multi-layer perceptron networks. Additionally, a precise sizing methodology based on solar irradiance data was implemented to ensure the system is neither oversized nor undersized. The system's performance was tested and validated using MATLAB/Simulink simulations, which demonstrated superior predictive accuracy, faster convergence, and optimized energy capture. This combined approach of intelligent MPPT and accurate sizing presents a highly effective solution for improving the efficiency and reliability of stand-alone solar energy systems under varying environmental conditions.
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Capelo, Miguel, Bruno Brentan, Laura Monteiro, and Dídia Covas. "Near–Real Time Burst Location and Sizing in Water Distribution Systems Using Artificial Neural Networks." Water 13, no. 13 (2021): 1841. http://dx.doi.org/10.3390/w13131841.

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The current paper proposes a novel methodology for near–real time burst location and sizing in water distribution systems (WDS) by means of Multi–Layer Perceptron (MLP), a class of artificial neural network (ANN). The proposed methodology can be systematized in four steps: (1) construction of the pipe–burst database, (2) problem formulation and ANN architecture definition, (3) ANN training, testing and sensitivity analyses, (4) application based on collected data. A large database needs to be constructed using 24 h pressure–head data collected or numerically generated at different sensor locations during the pipe burst occurrence. The ANN is trained and tested in a real–life network, in Portugal, using artificial data generated by hydraulic extended period simulations. The trained ANN has demonstrated to successfully locate 60–70% of the burst with an accuracy of 100 m and 98% of the burst with an accuracy of 500 m and to determine burst sizes with uncertainties lower than 2 L/s in 90% of tested cases and lower than 0.2 L/s in 70% of the cases. This approach can be used as a daily management tool of water distribution networks (WDN), as long as the ANN is trained with artificial data generated by an accurate and calibrated WDS hydraulic models and/or with reliable pressure–head data collected at different locations of the WDS during the pipe burst occurrence.
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Khatib, Tamer, Azah Mohamed, and K. Sopian. "A Software Tool for Optimal Sizing of PV Systems in Malaysia." Modelling and Simulation in Engineering 2012 (2012): 1–11. http://dx.doi.org/10.1155/2012/969248.

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This paper presents a MATLAB based user friendly software tool called as PV.MY for optimal sizing of photovoltaic (PV) systems. The software has the capabilities of predicting the metrological variables such as solar energy, ambient temperature and wind speed using artificial neural network (ANN), optimizes the PV module/ array tilt angle, optimizes the inverter size and calculate optimal capacities of PV array, battery, wind turbine and diesel generator in hybrid PV systems. The ANN based model for metrological prediction uses four meteorological variables, namely, sun shine ratio, day number and location coordinates. As for PV system sizing, iterative methods are used for determining the optimal sizing of three types of PV systems, which are standalone PV system, hybrid PV/wind system and hybrid PV/diesel generator system. The loss of load probability (LLP) technique is used for optimization in which the energy sources capacities are the variables to be optimized considering very low LLP. As for determining the optimal PV panels tilt angle and inverter size, the Liu and Jordan model for solar energy incident on a tilt surface is used in optimizing the monthly tilt angle, while a model for inverter efficiency curve is used in the optimization of inverter size.
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Kim, Hye-Rim, and Tong-Seop Kim. "Optimization of Sizing and Operation Strategy of Distributed Generation System Based on a Gas Turbine and Renewable Energy." Energies 14, no. 24 (2021): 8448. http://dx.doi.org/10.3390/en14248448.

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Optimization of the sizing and operation strategy of a complex energy system requires a large computational burden because of the non-linear nature of the mathematical problem. Accordingly, using a conventional numerical method with only a physics-based model for complete optimization is impractical. To resolve this problem, this paper adopted an optimization method of using an artificial intelligence scheme that combines an artificial neural network (ANN) and a genetic algorithm (GA). Especially, the ANN was constructed based on results from a physics-based model to obtain a large amount of accurate simulation data in a short time frame. A distributed generation (DG) system based on a gas turbine (GT) and renewable energy (RE) was simulated to demonstrate the usefulness of the optimization method. In consideration of the capacity and partial load performance of the GT, the optimization of the sizing and operation strategy of the DG system was performed for three system design scenarios. The optimization criteria were cost-effectiveness and eco-friendliness. The method reduced the calculation time by more than three orders of magnitude while maintaining the same accuracy as the physics-based model. The approach and methodology are expected to be applicable to accurate and fast optimization of various sophisticated energy systems.
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Kulaksız, Ahmet Afşin, Bayram Akdemir, and Hale Bakır. "ANN-Based Sizing of Battery Storage in a Stand-Alone PV System." Journal of Automation and Control Engineering 3, no. 6 (2015): 8–12. http://dx.doi.org/10.12720/joace.4.1.8-12.

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Ashigwuike, Evans Chinemezu, and Stephen Adole Benson. "Optimal Location and Sizing of Distributed Generation in Distribution Network Using Adaptive Neuro-Fuzzy Logic Technique." European Journal of Engineering Research and Science 4, no. 4 (2019): 83–89. http://dx.doi.org/10.24018/ejers.2019.4.4.1237.

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The growing gap between electric power generated and that demanded is of utmost concern especially in developing economy, hence calling for measures to argument the existing power generated of which DG is a more viable aspect to explore in curtailing this challenges; although been confronted with issue of location and sizing. This research applied Adaptive neuro fuzzy logic technique to optimize DG location and size. A 24 bus radial network was used to demonstrate this process and having a suitable location and size at optimal position reduces power losses and also improves the voltage profile at the buses. The method was simulated using ANFIS toolbox MATLAB R2013b (8.2.0.701) 64-bit software and tested using Gwagwalada injection sub-station feeder 1 system. The results obtained were compared to that obtained using ANN. It was observed that adaptive neuro fuzzy logic technique performed better in terms of reducing power losses compared to ANN technique. The percentage reduction in the power loss at the buses cumulatively is 48.96% for ANN while adaptive neuro fuzzy logic technique is 49.21%. The voltage profile of the networks after optimizing the DG location and sizes using adaptive neuro fuzzy logic technique were also found to be much improved with the lowest bus voltage improved from 0.9284 to 1.05pu.
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Ashigwuike, Evans Chinemezu, and Stephen Adole Benson. "Optimal Location and Sizing of Distributed Generation in Distribution Network Using Adaptive Neuro-Fuzzy Logic Technique." European Journal of Engineering and Technology Research 4, no. 4 (2019): 83–89. http://dx.doi.org/10.24018/ejeng.2019.4.4.1237.

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The growing gap between electric power generated and that demanded is of utmost concern especially in developing economy, hence calling for measures to argument the existing power generated of which DG is a more viable aspect to explore in curtailing this challenges; although been confronted with issue of location and sizing. This research applied Adaptive neuro fuzzy logic technique to optimize DG location and size. A 24 bus radial network was used to demonstrate this process and having a suitable location and size at optimal position reduces power losses and also improves the voltage profile at the buses. The method was simulated using ANFIS toolbox MATLAB R2013b (8.2.0.701) 64-bit software and tested using Gwagwalada injection sub-station feeder 1 system. The results obtained were compared to that obtained using ANN. It was observed that adaptive neuro fuzzy logic technique performed better in terms of reducing power losses compared to ANN technique. The percentage reduction in the power loss at the buses cumulatively is 48.96% for ANN while adaptive neuro fuzzy logic technique is 49.21%. The voltage profile of the networks after optimizing the DG location and sizes using adaptive neuro fuzzy logic technique were also found to be much improved with the lowest bus voltage improved from 0.9284 to 1.05pu.
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Karunarathne, Sumudu S., Khim Chhantyal, Dag A. Eimer, and Lars E. Øi. "Artificial Neural Networks (ANNs) for Density and Viscosity Predictions of CO2 Loaded Alkanolamine + H2O Mixtures." ChemEngineering 4, no. 2 (2020): 29. http://dx.doi.org/10.3390/chemengineering4020029.

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The physical properties, like density and viscosity, of alkanolamine + H2O (water) + CO2 (carbon dioxide) mixtures receive a significant amount of attention as they are essential in equipment sizing, mathematical modelling and simulations of amine-based post-combustion CO2 capture processes. Non-linear models based on artificial neural networks (ANNs) were trained to correlate measured densities and viscosities of monoethanol amine (MEA) + H2O, MEA + H2O + CO2, and 2-amino-2-methyl-1-propanol (AMP) + MEA + H2O + CO2 mixtures and results were compared with conventional correlations found in literature. For CO2-loaded aqueous amine mixtures, results from the ANN models are in good agreement with measured properties with less than 1% average absolute relative deviation (AARD). The ANN-based methodology shows much better agreement (R2 > 0.99) between calculated and measured values than conventional correlations.
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Dissertations / Theses on the topic "ANN sizing"

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Boyajian, Tabetha Suzanne. "Sizing Up the Stars." Digital Archive @ GSU, 2009. http://digitalarchive.gsu.edu/phy_astr_diss/34.

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For the main part of this dissertation, I have executed a survey of nearby, main sequence A, F, and G-type stars with the CHARA Array, successfully measuring the angular diameters of forty-four stars to better than 4% accuracy. The results of these observations also yield empirical determinations of stellar linear radii and effective temperatures for the stars observed. In addition, these CHARA-determined temperatures, radii, and luminosities are fit to Yonsei-Yale isochrones to constrain the masses and ages of the stars. These quantities are compared to the results found in Allende Prieto & Lambert (1999), Holmberg et al. (2007), and Takeda (2007), who indirectly determine these same properties by fitting models to observed photometry. I find that for most cases, the models underestimate the radius of the star by ~12%, while in turn they overestimate the effective temperature by ~ 1.5 - 4%, when compared to my directly measured values, with no apparent correlation to the star's metallicity or color index. These overestimated temperatures and underestimated radii in these works appear to cause an additional offset in the star's surface gravity measurements, which consequently yield higher masses and younger ages, in particular for stars with masses greater than ~ 1.3 M_sol. Alternatively, these quantities I measure are also compared to direct measurements from a large sample of eclipsing binary stars in Andersen (1991), and excellent agreement is seen within both data sets. Finally, a multi-parameter solution is found to fit color-temperature-metallicity values of the stars in this sample to provide a new calibration of the effective temperature scale for these types of stars. Published work in the field of stellar interferometry and optical spectroscopy of early-type stars are presented in Appendix D and E, respectively.
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Mattsson, Rosa. "AKD sizing - dispersion colloidal stability, spreading and sizing with pre-flocculated dispersions /." Licentiate thesis, Luleå tekniska universitet, 2002. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-17236.

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Alkylketene dimer, AKD, dispersions are used in the paper industry to obtain paper grades with a hydrophobic character i.e. resistance to sorption of water. AKD is used in neutral to alkaline internal sizing, pH in the interval of 6-9. AKD dispersions consist of wax particles emulsified in water. The particles are electrostatically and in most cases also sterically stabilized by cationic polyelectrolytes. The size of the particles is usually in the range of 0.5-2 µm in diameter. The idea of having cationic particles is that they are supposed to be deposited onto the negatively charged fiber surfaces, heterocoagulation. An increased usage of recycled pulp and a closure of the wet-end circuits of the paper machine will lead to increasing levels of dissolved and colloidal substances. These substances could be detrimental by affecting the AKD deposition onto the fiber material and the colloidal stability i.e. induce flocculation of sizing particles. Flocculation could lead to an inhomogeneous distribution of the sizing agent. The aims addressed in this thesis were the following: to investigate if high levels of shear, electrolyte concentration, anionic polymers and surfactants could affect the colloidal stability and induce flocculation of differently designed AKD dispersions to study the migration of AKD and the influence of extractives on the migration to study the sizing efficiency and retention using flocculated dispersions The colloidal stability of the dispersions was tested under shear by measuring the particle size distribution and the microelectrophoretic mobility. The migration of AKD through paper sheets with defined thickness and through paper sheets impregnated with extractives was analyzed with contact angle measurements on stored samples. The sizing efficiency of flocculated AKD was determined by measuring 60-second Cobb and contact angles on laboratory sheets. The retention of AKD was determined by quantitative analysis of the AKD content in the laboratory sheets using alkaline hydrolysis followed by solvent extraction and quantification with capillary gas chromatography. It was shown that anionic polymers and surfactants could seriously affect the colloidal stability of the dispersions, while shear and electrolyte concentration had a small influence. Dispersions with a high surface charge flocculates easier than dispersions with a low surface charge in process water from the wet-end of a linerboard paper machine. The flocculation rate is fast and occurs on the same time scale as deposition onto fines and fibers. The AKD agglomerates could be up to 30 µm in diameter even at high levels of shear. The AKD diffusion coefficient in paper sheets was estimated to be 10-11 m2/s at a temperature above the melting point of the wax. The results indicate that extractives do not interfere with the AKD migration. A reasonable explanation is that migration occurs via the vapor phase. It was also shown that sizing with flocculated AKD improved the sizing efficiency significantly due to increased retention. This clearly indicates that migration is efficient and that agglomerates can be used for internal sizing provided that the flocculation process is controlled. The conventional picture that the sizing agents must be very evenly distributed to achieve efficient sizing could, from the viewpoint of these results, be questioned. The process of sizing with pre-flocculated AKD dispersions is the subject of a patent application. Even if this thesis is focused on AKD dispersions, the obtained knowledge should be possible to transfer to other sizing systems. The emulsification process for rosin and ASA is based on the same principles as for AKD.<br>Godkänd; 2002; 20070222 (ysko)
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Hoff, Kristen G. "Lot-sizing in the wood furniture industry." Thesis, Virginia Tech, 1991. http://hdl.handle.net/10919/42123.

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We consider the problem of scheduling production in a wood furniture plant. In particular, we consider the problem of selecting orders from various types of furniture products and determining their lot-sizes for production when there are sequence dependent setup times involved in the production of these items. This is termed the aggregate scheduling problem. In addition, we consider the problem of scheduling work at various production facilities in the presence of capacity constraints once the items for production and their quantities are selected. This is termed the detailed scheduling problem. The aggregate scheduling problem is formulated as a mixed integer program and solved using a dynamic programming procedure. The detailed scheduling program is a linear program and is solved using a canned linear programming package. In order to understand the state-of-the-art in the furniture industry, various furniture plants in Southwest Virginia were visited and a national survey was conducted. The results are summarized. The survey emphasized the problem addressed in this research. In order to understand the decision points better in the furniture manufacturing process, the IDEF (ICAM definition) procedure is used to describe the furniture manufacturing process. The methodology developed is applied to a real-life problem and the results are summarized.<br>Master of Science
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Leung, Janny M. Y., Thomas L. Magnanti, and Rita Vachani. "Facets and Algorithms for Capacitated Lot Sizing." Massachusetts Institute of Technology, Operations Research Center, 1987. http://hdl.handle.net/1721.1/5210.

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The dynamic economic lot sizing model, which lies at the core of numerous production planning applications, is one of the most highly studied models in all of operations research. And yet, capacitated multi-item versions of this problem remain computationally elusive. We study the polyhedral structure of an integer programming formulation of a single-item capacitated version of this problem, and use these results to develop solution methods for multi-item applications. In particular, we introduce a set of valid inequalities for the problem and show that they define facets of the underlying integer programming polyhedron. Computational results on several single and multiple product examples show that these inequalities can be used quite effectively to develop an efficient cutting plane/branch and bound procedure. Moreover, our results show that in many instances adding certain of these inequalities a priori to the problem formulation, and avoiding the generation of cutting planes, can be equally effective.
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Riley, James B. (James Barret). "Laser diffraction particle sizing : sampling and inversion." Thesis, Massachusetts Institute of Technology, 1987. http://hdl.handle.net/1721.1/58492.

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Thesis (Ph. D.)--Joint Program in Oceanographic Engineering (Massachusetts Institute of Technology, Dept. of Ocean Engineering; and the Woods Hole Oceanographic Institution), 1987.<br>Bibliography: p. 213-228.<br>by James B. Riley.<br>Ph.D.
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Filho, Márcio Antonio Ferreira Belo. "Lot sizing with setup carryover and crossover." Universidade de São Paulo, 2014. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-29042016-142624/.

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Production planning problems are of paramount importance within supply chain planning, supporting decisions on the transformation of raw materials into finished products. Lot sizing in production planning refers to the tactical/operational decisions related to the size and timing of production orders to satisfy a demand. The objectives of lot-sizing problems are generally economical-related, such as saving costs or increasing profits, though other aspects may be taken into account such as quality of the customer service and reduction of inventory levels. Lot-sizing problems are very common in production activities and an efficient planning of such activities gives the company a clear advantage over concurrent organizations. To that end it is required the consideration of realistic features of the industrial environment and product characteristics. By means of mathematical modelling, such considerations are crucial, though their inclusion results in more complex formulations. Although lot-sizing problems are well-known and largely studied, there is a lack of research in some real-world aspects. This thesis addresses two main characteristics at the lot-sizing context: (a) setup crossover; and (b) perishable products. The former allows the setup state of production line to be carried over between consecutive periods, even if the line is not yet ready for processing production orders. The latter characteristic considers that some products have fixed shelf-life and may spoil within the planning horizon, which clearly affects the production planning. Furthermore, two types of perishable products are considered, according to the duration of their lifetime: medium-term and short-term shelf-lives. The latter case is tighter than the former, implying more constrained production plans, even requiring an integration with other supply chain processes such as distribution planning. Research on stronger mathematical formulations and solution approaches for lot-sizing problems provides valuable tools for production planners. This thesis focuses on the development of mixed-integer linear programming (MILP) formulations for the lot-sizing problems considering the aforementioned features. Novel modelling techniques are introduced, such as the proposal of a disaggregated setup variable and the consideration of lot-sizing instead of batching decisions in the joint production and distribution planning problem. These formulations are subjected to computational experiments in state-of-the-art MILP-solvers. However, the inherent complexity of these problems may require problemdriven solution approaches. In this thesis, heuristic, metaheuristic and matheuristic (hybrid exact and heuristic) procedures are proposed. A lagrangean heuristic addresses the capacitated lot-sizing problem with setup carryover and perishable products. A novel dynamic programming procedure is used to achieve the optimal solution of the uncapacitated single-item lot-sizing problem with setup carryover and perishable item. A heuristic, a fix-and-optimize procedure and an adaptive large neighbourhood search approach are proposed for the operational integrated production and distribution planning. Computational results on generated set of instances based on the literature show that the proposed methods yields competitive performances against other literature approaches.<br>Problemas de planejamento da produção são de suma importância no planejamento da cadeia de suprimentos, dando suporte às decisões da transformação de matérias-primas em produtos acabados. O dimensionamento de lotes em planejamento de produção é definido pelas decisões tático-operacionais relacionadas com o tamanho das ordens de produção e quando fabricá-las para satisfazer a demanda. Os objetivos destes problemas são geralmente de cunho econômico, tais como a redução de custos ou o aumento de lucros, embora outros aspectos possam ser considerados, tais como a qualidade do serviço ao cliente e a redução dos níveis de estoque. Problemas de dimensionamento de lotes são muito comuns em atividades de produção e um planejamento eficaz de tais atividades, estabelece uma clara vantagem à empresa em relação à concorrência. Para este objetivo, é necessária a consideração de características realistas do ambiente industrial e do produto. Para a modelagem matemática do problema, estas considerações são cruciais, embora sua inclusão resulte em formulações mais complexas. Embora os problemas de dimensionamento de lotes sejam bem conhecidos e amplamente estudados, várias características reais importantes não foram estudadas. Esta tese aborda, no contexto de dimensionamento de lotes, duas características muito relevantes: (a) preservação da preparação total e parcial; e (b) produtos perecíveis. A primeira permite que o estado de preparação de uma linha de produção seja mantido entre dois períodos consecutivos, mesmo que a linha de produção ainda não esteja totalmente pronta para o processamento de ordens de produção. A ultima característica determina que alguns produtos tem prazo de validade fixo, menor ou igual do que o horizonte de planejamento, o que afeta o planejamento da produção. Além disso, de acordo com a duração de sua vida útil, foram considerados dois tipos de produtos perecíveis: produtos com tempo de vida de médio e curto prazo. O ultimo caso resulta em um problema mais apertado do que o anterior, o que implica em planos de produção mais restritos. Isto pode exigir uma integração com outros processos da cadeia de suprimentos, tais como o planejamento de distribuição dos produtos acabados. Pesquisas sobre formulações matemáticas mais fortes e abordagens de solução para problemas de dimensionamento de lotes fornecem ferramentas valiosas para os planejadores de produção. O foco da tese reside no desenvolvimento de formulações de programação linear inteiro-mistas (MILP) para os problemas de dimensionamento de lotes, considerando as características mencionadas anteriormente. Novas técnicas de modelagem foram introduzidas, como a proposta de variáveis de preparação desagregadas e a consideração de decisões de dimensionamento de lotes ao invés de decisões de agrupamento de ordens de produção no problema integrado de planejamento de produção e distribuição. Estas formulações foram submetidas a experimentos computacionais em MILP-solvers de ponta. No entanto, a complexidade inerente destes problemas pode exigir abordagens de solução orientadas ao problema. Nesta tese, abordagens heurísticas, metaheurísticas e matheurísticas (híbrido de métodos exatos e heurísticos) foram propostas para os problemas discutidos. Uma heurística lagrangeana aborda o problema de dimensionamento de lotes com restrições de capacidade, preservação da preparação total e produtos perecíveis. Um novo procedimento de programação dinâmica e utilizado para encontrar a solução ótima do problema de dimensionamento de lotes de um único produto perecível, sem restrições de capacidade e preservação da preparação total. Uma heurística, um procedimento x-and-optimize e uma abordagem por buscas adaptativas em grande vizinhanças são propostas para o problema integrado de planejamento de produção e distribuição. Resultados computacionais em conjuntos de instâncias geradas com base na literatura mostram que os métodos propostos obtiveram performances competitivas com relação a outras abordagens da literatura.
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Xiao, Wen Qiang. "Essays on scheduling and lot sizing models /." View Abstract or Full-Text, 2002. http://library.ust.hk/cgi/db/thesis.pl?IEEM%202002%20XIAO.

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York, Martin A. S. M. Massachusetts Institute of Technology. "Turbofan engine sizing and tradeoff analysis via signomial programming/." Thesis, Massachusetts Institute of Technology, 2017. http://hdl.handle.net/1721.1/112383.

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Thesis: S.M., Massachusetts Institute of Technology, Department of Aeronautics and Astronautics, 2017.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Cataloged from student-submitted PDF version of thesis.<br>Includes bibliographical references (pages 79-80).<br>This thesis presents a full 1D core+fan flowpath turbofan optimization model, based on first principles, and meant to be used during aircraft conceptual design optimization. The model is formulated as a signomial program, which is a type of optimization problem that can be solved locally using sequential convex optimization. Signomial programs can be solved reliably and eciently, and are straightforward to integrate with other optimization models in an all-at-once manner. To demonstrate this, the turbofan model is integrated with a simple commercial aircraft sizing model. The turbofan model is validated against the Transport Aircraft System OPTimization turbofan model as well as two Georgia Tech Numerical Propulsion System Simulation turbofan models. Four integrated engine/aircraft parametric studies are performed, including a 2,460 variable multi-mission optimization that solves in 28 seconds.<br>by Martin A. York.<br>S.M.
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Darwish, Mohammed. "Lot-sizing and scheduling optimization using genetic algorithm." Thesis, Högskolan i Skövde, Institutionen för ingenjörsvetenskap, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-17045.

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Simultaneous lot-sizing and scheduling problem is the problem to decide what products to be produced on which machine and in which order, as well as the quantity of each product. Problems of this type are hard to solve. Therefore, they were studied for years, and a considerable number of papers is published to solve different lotsizing and scheduling problems, specifically real-case problems. This work proposes a Real-Coded Genetic Algorithm (RCGA) with a new chromosome representation to solve a non-identical parallel machine capacitated lot-sizing and scheduling problem with sequence dependent setup times and costs, machine cost and backlogging. Such a problem can be found in real world production line at furniture manufacturer in Sweden. Backlogging is an important concept in this problem, and it is often ignored in the literature. This study implements three different types of crossover; one of them has been chosen based on numerical experiments. Four mutation operators have been combined together to allow the genetic algorithm to scan the search area and maintain genetic diversity. Other steps like initializing of the population and a reinitializing process have been designed carefully to achieve the best performance and to prevent the algorithm from trapped into the local optimum. The proposed algorithm is implemented and coded in MATLAB and tested for a set of standard medium to large-size problems taken from the literature. A variety of problems were solved to measure the impact of different characteristics of problems such as the number of periods, machines, and products on the quality of the solution provided by the proposed RCGA. To evaluate the performance of the proposed algorithm, the average deviation from the lower bound and runtime for the proposed RCGA are compared with three other algorithms from the literature. The results show that, in addition to its high computational speed, the proposed RCGA outperforms the other algorithms for non-identical parallel machine problems, while it is outperformed by the other algorithms for problems with the more identical parallel machine. The results show that the different characteristics of problem instances, like increasing setup cost, and size of the problem influence the quality of the solutions provided by the proposed RCGA negatively.
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Upton, Eric George. "An Intelligent, Robust Approach to Volumetric Aircraft Sizing." Diss., Georgia Institute of Technology, 2007. http://hdl.handle.net/1853/16128.

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Advances in computational power have produced great strides in the later design and production portions of an aircraft s life cycle, and these advances have included the internal layout component of the design and manufacturing process. However, conceptual and preliminary design tools for internal layout remain primarily based on historical regressions and estimations a situation that becomes untenable when considering revolutionary designs or component technologies. Bringing internal layout information forward in the design process can encourage the same level of benefits enjoyed by other disciplines as advances in aerodynamics, structures and other fields propagate forward in the design of complex systems. Accurate prediction of the volume required to contain all of an aircraft s internal components results in a more accurate prediction of aircraft specifications, mission effectiveness, and costs, helping determine if an aircraft is the best choice for continued development. This is not a computationally simple problem, however, and great care must be taken to ensure the efficiency of any proposed solution. Any solution must also address the uncertainty inherent in describing internal components early in the design process. Implementing a methodology that applies notions of an intelligent search for a solution, as well as deals robustly with component sizing, produces a high chance of success. Development of a robust, rapid method for assessing the volumetric characteristics of an aircraft in the context of the conceptual and preliminary design processes can offer many of the benefits of a complete internal layout without the immense assignment of resources typical in the detail phase of the design process. A simplified methodology for volumetrically sizing an aircraft is presented here as well as an assessment of the state-of-the-art techniques for volumetric considerations used in current aircraft design literature. A prototype tool using a combination of original code and publicly available libraries is developed and explored. A sample aircraft design is undertaken with the prototype tool to demonstrate the effectiveness of the methodology.
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Books on the topic "ANN sizing"

1

Bachman, Vicki. Sizing up measurement. Math Solutions Publications, 2007.

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Confer, Chris. Sizing up measurement. Math Solutions Publications, 2007.

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Provder, Theodore, and John Texter, eds. Particle Sizing and Characterization. American Chemical Society, 2004. http://dx.doi.org/10.1021/bk-2004-0881.

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1939-, Provder Theodore, Texter J, American Chemical Society. Division of Colloid and Surface Chemistry, and American Chemical Society Meeting, eds. Particle sizing and characterization. American Chemical Society, 2004.

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Kirckof, Gary. Servomotor sizing and application. International Society of Automation, 2012.

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Robinette, Kathleen M., Daisy Veitch, Sandra Alemany, and Karen Bredenkamp. Product Fit and Sizing. CRC Press, 2024. http://dx.doi.org/10.1201/9781003397533.

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Lawrence, Ann. Sizing up measurement. Math Solutions Publications, 2007.

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Wakan, Naomi. Sizing up Some sumo. Pacific-Rim Publishers, 1992.

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United States. Bonneville Power Administration., ed. Sizing irrigation mainlines and fittings. Bonneville Power Administration, U.S. Dept. of Energy, 1985.

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Khan, Muhammad Qamar, Yasir Nawab, and Ick Soo Kim, eds. Garment Sizing and Pattern Making. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-7683-2.

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Book chapters on the topic "ANN sizing"

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Weik, Martin H. "sizing." In Computer Science and Communications Dictionary. Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_17572.

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Jones, A. R. "Conclusion and Perspective." In Optical Particle Sizing. Springer US, 1988. http://dx.doi.org/10.1007/978-1-4757-1983-3_51.

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Bachalo, W. D. "The Phase Doppler Method: Analysis and Application." In Optical Particle Sizing. Springer US, 1988. http://dx.doi.org/10.1007/978-1-4757-1983-3_23.

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Bauckhage, Klaus, Hans-H. Flögel, and Frank Schöne. "Size and Velocity Measurements of Spherical Particles in Multiphase Flows and the Prediction of Absolute Particle Concentrations." In Optical Particle Sizing. Springer US, 1988. http://dx.doi.org/10.1007/978-1-4757-1983-3_36.

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Zerull, R. H., R. T. Killinger, and R. H. Giese. "Optical Particle Sizing and Particle Characterization Based on Polarization Measurements." In Optical Particle Sizing. Springer US, 1988. http://dx.doi.org/10.1007/978-1-4757-1983-3_49.

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Kouzelis, D., S. M. Candel, E. Esposito, and S. Zikikout. "Particle Sizing by Laser Light Diffraction : Improvements in Optics and Algorithms." In Optical Particle Sizing. Springer US, 1988. http://dx.doi.org/10.1007/978-1-4757-1983-3_27.

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Brown, D. J., E. J. Weatherby, and K. Alexander. "Shape, Concentration and Anomalous Diffraction Effects in Sizing Solids in Liquids." In Optical Particle Sizing. Springer US, 1988. http://dx.doi.org/10.1007/978-1-4757-1983-3_28.

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Bottlinger, Michael, and Heinz Umhauer. "Scattered Light Particle Size Counting Analysis: Influence of Shape and Structure." In Optical Particle Sizing. Springer US, 1988. http://dx.doi.org/10.1007/978-1-4757-1983-3_29.

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Borner, Thoma, and LIdong Zhan. "LDV-Signal-Analysis for Particle Velocity and Size Detection Using Geometrical Optics." In Optical Particle Sizing. Springer US, 1988. http://dx.doi.org/10.1007/978-1-4757-1983-3_15.

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Killinger, R. T., and R. H. Zerull. "Effects of Shape and Orientation to be Considered for Optical Particle Sizing." In Optical Particle Sizing. Springer US, 1988. http://dx.doi.org/10.1007/978-1-4757-1983-3_34.

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Conference papers on the topic "ANN sizing"

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Westwood, Stephen, and Phil Hopkins. "Smart Pigs and Defect Assessment Codes: Completing the Circle." In CORROSION 2004. NACE International, 2004. https://doi.org/10.5006/c2004-04156.

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Abstract Smart pigs are used extensively as part of integrity management plans for oil and gas pipelines to detect metal loss defects, with magnetic flux leakage (MFL) technology being the most-widely used. The MFL signal gives an inferred defect size, not a direct measurement: when the signal is translated into a defect size, it has associated sizing tolerances and confidence levels. The complexity of signal analysis means that these sizing tolerances and confidence levels are difficult to determine and apply in practice. They have a major effect when assessing the significance of the defect, and when calculating corrosion growth rates from the results of multiple inspections over time. This paper describes how sizing algorithms are constructed and how the quoted tolerances are derived. Probability theory can be used to estimate the likelihood that a defect is smaller or deeper than the reported value. Finally, the effect of defect sizing tolerances and their confidence levels on corrosion growth projections is illustrated, and how they must be taken into account in any defect assessment is emphasised.
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Hochhaus, Thorben, Johannes Wloch, Marcus Gr�newald, and Julia Riese. "A Data-Driven Conceptual Approach to Heat Pump Sizing in Chemical Processes with Fluctuating Heat Supply and Demand." In The 35th European Symposium on Computer Aided Process Engineering. PSE Press, 2025. https://doi.org/10.69997/sct.196662.

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Heat pumps play a crucial role in decarbonizing the chemical industry. The integration and sizing of heat pumps in chemical processes is a challenging task in multi-product chemical processes due to the fluctuating waste heat supply and heat demand. Integrating heat pumps may require a retrofit of the utility system. Mathematical optimization is a useful tool to tackle this challenge by enabling the analysis of correlation between relevant system parameters and equipment sizing. This study demonstrates the utilization of mathematical optimization and parameter studies for utility system equipment sizing addressing fluctuating heat supply and demand profiles.
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Thompson, Ryan, and Bernard Bekker. "Improved Methodology for Microgrid Unit Sizing." In 2024 IEEE International Conference on Environment and Electrical Engineering and 2024 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe). IEEE, 2024. http://dx.doi.org/10.1109/eeeic/icpseurope61470.2024.10751504.

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Kobayashi, Masakazu, and Yuki Ogawa. "Efficient Sizing Optimization using ANN Instead of FEM." In CAD'22. CAD Solutions LLC, 2022. http://dx.doi.org/10.14733/cadconfp.2022.277-281.

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Domingues, Joao, Antonio Gusmao, Nuno Horta, Nuno Lourenco, and Ricardo Martins. "Accelerating Voltage-Controlled Oscillator Sizing Optimizations with ANN-based Convergence Classifiers and Frequency Guess Predictors." In 2022 18th International Conference on Synthesis, Modeling, Analysis and Simulation Methods and Applications to Circuit Design (SMACD). IEEE, 2022. http://dx.doi.org/10.1109/smacd55068.2022.9816265.

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Spang, Bruce, Brady Walsh, Te-Yuan Huang, Tom Rusnock, Joe Lawrence, and Nick McKeown. "Buffer sizing and Video QoE Measurements at Netflix." In BS '19: 2019 Workshop on Buffer Sizing. ACM, 2019. http://dx.doi.org/10.1145/3375235.3375241.

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Pun Chan, Ah, Wai Ching Chu, Kwan Yu Lo, and Kai Yuen Cheong. "Improving the Apparel Virtual Size Fitting Prediction under Psychographic Characteristics and 3D Body Measurements Using Artificial Neural Network." In 13th International Conference on Applied Human Factors and Ergonomics (AHFE 2022). AHFE International, 2022. http://dx.doi.org/10.54941/ahfe1001543.

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Background3D virtual simulation prototyping software combined with computer-aided manufacturing systems are widely used and are becoming essential in the fashion industry in the earlier stages of the product development process for apparel design. These technologies streamline the garment product fitting procedures, as well as improve the supply chain environmentally, socially, and economically by eliminating large volumes of redundant samples. Buyers can easily evaluate virtual samples that are showcased with full rotation views and visual draping effects without relying on physical prototypes before confirming orders. The approved designs can be transferred to the production line immediately, which shortens the communication, development, and production lead time between suppliers and buyers. Issues of non-standardized selection on garment sizing, ease allowance, and size of 3D avatar for creating 3D garments have been addressed by many researchers. Understanding the relationship between body dimensions, ease allowance, and apparel sizes before adopting virtual garment simulation is fundamental for satisfying high customer demands in the apparel industry. However, designers find difficulties providing the appropriate garment fit for customers without fully understanding the motivation and emotions of customers’ fitting preferences in a virtual world.A statement of objective The main purpose of this study is to investigate apparel sizes for virtual fitting, particularly looking at garment ease with consideration to body dimensions and the psychographic characteristics of subjects.SignificanceThe quantitative relationship between the pattern measurements, psychological characteristics, and 3D body measurements contributes to improving virtual fit predictions for implementing mass customization in the apparel industry. This new approach and the proposed method of virtual garment fitting model prediction on garment sizes using an Artificial Neural Network (ANN) is significant in prediction accuracy. The results of this project provide sustainable value in providing an ideal communication tool between manufacturers, retailers, and consumers by offering “perfect fit” products to customers. The project will also achieve the concept of mass customization and customer orientation, and generate new size fitting data that could bring a new level of end-user satisfaction.MethodsThe study proposes to develop a virtual garment fitting prediction model using an ANN for improving virtual garment design in terms of its fitting and sizing. The project investigated apparel sizes for virtual fitting with consideration of body dimensions and psychographic characteristics of subjects on garment ease for improving the size prediction of 3D garments. We recruited 50 subjects between the ages 18-35 years old to conduct 3D body scans and a questionnaire survey for physical and psychological segmentation, as well as fitting preferences evaluation through co-design operations on virtual garment simulation using a commercial software called Optitex. Discussion of resultsThe ease preferences from subjects were significantly different from the preset values on the software. The results from the study demonstrate that ANN is effective in modeling the non-linear relationship between pattern measurements, psychological characteristics, and body measurements. The pattern parameters predicted by the ANN model were accurate. The squared correlation coefficient (R2) increased from 0.96 to 0.99 after considering different segmentations of psychographic characteristics. The ANN prediction model is proven to be an effective method for garment pattern drafting, which can achieve an individual fit and is useful for implementing the virtual fitting model.
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Seshadri, Lakshminarayanan, and Pramod Kumar. "Vaneless Diffuser Modelling for Real Gas Supercritical Carbon Dioxide Flows- Need for a Data Driven Approach." In ASME Turbo Expo 2024: Turbomachinery Technical Conference and Exposition. American Society of Mechanical Engineers, 2024. http://dx.doi.org/10.1115/gt2024-126308.

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Abstract In this work, a real gas-based Vaneless diffuser (VLD) differential equation model is presented. The model requires the specification of the skin friction coefficient as input. However, the use of standard VLD friction coefficient estimation expressions require a re-examination for sCO2 flows. To establish the skin friction coefficient for real gas sCO2 flows, CFD data is generated using Latin Hypercube Sampling (LHS), with boundary conditions spanning the typical operating conditions of sCO2 centrifugal compressors in the kW to MW scale of power generation. The CFD computations are carried out using ANSYS® CFX software. The corresponding VLD friction coefficient for which the VLD stagnation pressure loss predicted by the 1D differential equation model matches with the 3D CFD result is back calculated for all the LHS designs. This is carried out using a root finding function in MATLAB® software. The existing empirical relation that characterizes the VLD skin friction coefficient using the inlet Reynolds number alone shows a poor correlation (R2 = 0.26), when compared to the CFD data. It is evident that a data driven approach is required to model the sCO2 VLD real gas flow for accurate results. Using the LHS data, the efficacy of an Artificial Neural Network (ANN)-based VLD model is demonstrated. A two hidden layer ANN is developed, which accurately predicts the skin friction coefficient for sCO2 real gas flows (R2 = 0.87). This proposed ANN based VLD model can be easily integrated into existing 1D codes for real gas sCO2 centrifugal compressor rating and sizing.
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Beck, Douglas Stephen. "Optimization of Regenerated Gas Turbines." In ASME 1994 International Gas Turbine and Aeroengine Congress and Exposition. American Society of Mechanical Engineers, 1994. http://dx.doi.org/10.1115/94-gt-231.

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An algorithm for the optimization of regenerated gas turbines is given. For sets of inputs that are typical for automotive applications, the optimum cycle pressure ratio and a set of optimized regenerator parameters that maximize thermal efficiency are given. A second algorithm, an algorithm for sizing regenerators based on outputs of the optimization algorithm, is given. With this sizing algorithm, unique regenerator designs can be determined for many applications based on the presented optimization data. Results of example sizings are given. The data indicate that one core (instead of two cores) should be used to maximize thermal efficiency. The data also indicate that thermal efficiencies of over 50% should be achievable for automotive applications if ceramic turbines are used.
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Yin Dik, Nga, Wai Kei Tsang, Ah Pun Chan, Kwan Yu Lo, and Wai Ching Chu. "Predicting Virtual Garment Fitting Size with Psychographic Characteristics and 3D Body Measurements Using Artificial Neural Network and Visualizing Fitted Bodies Using Generative Adversarial Network." In 14th International Conference on Applied Human Factors and Ergonomics (AHFE 2023). AHFE International, 2023. http://dx.doi.org/10.54941/ahfe1003635.

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3D virtual garment simulation technology is widely used in apparel industry nowadays with computer-aided manufacturing systems for the earlier stages of apparel design and product development process. The technological advances have brought convenience in garment product fitting procedures with virtual fitting environment, and eventually enhance the supply chain in the aspects of social, economic, and environmental aspects. Many studies have addressed the matters related to non-standardized selection on garment sizing, ease allowance for different selected groups, and use of 3D avatars for virtual fitting in the design and pre-production stages. Nevertheless, the current practice for designers is difficult for them to recognize the customers’ motivation and emotions towards their preferred fit in the virtual environment, leading to a hard time for the designers to determine the appropriate ease allowances for the end users. The present study is to investigate the variations on the ease preferences for the apparel sizes according to the body dimensions and psychological orientation of the subjects by developing a virtual garment fitting prediction model using artificial neural network (ANN). One hundred and twenty adult subjects were recruited to conduct 3D body scans and questionnaire survey for retrieving their body dimensions and psychographic characteristics. Segmentations were performed and each cluster was asked to evaluate the fitting preferences in a co-design interview on virtual garment simulation with a commercial software called Optitex. The results demonstrated that the ANN model is effective in predicting ease preferences from the body measurements and the psychological orientation of the subjects with high correlation coefficients, showing that a non-linear relationship is modelled among pattern parameters, body dimensions and psychographic characteristics. The results were visualized using generative adversarial network (GAN) to generate 3D samples. This new approach is significant to predict the garment sizes and pattern parameters with a highly accurate ANN model. Visualization of the predicted size with the implementation of GAN model is valuable to envision the garment details from 2D to 3D. The project has achieved the conception of mass customization and customer orientation by providing the perfect fit to the end users. Eventually, new size fitting data is generated for improved ease preference charts and augments end-user satisfaction in garment fit.
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Reports on the topic "ANN sizing"

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Grisso, Robert, Shawn D. Askew, and David McCall. Nozzles: Selection and Sizing. Virginia Cooperative Extension, 2019. http://dx.doi.org/10.21061/442-032_bse-262p.

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Belliveau, A., R. Tunuguntla, and A. Noy. Carbon nanotube sizing and quantification. Office of Scientific and Technical Information (OSTI), 2014. http://dx.doi.org/10.2172/1132015.

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Malinowski, Owen. PR-335-203810-R01 Review of Xray Computed Tomography Performance. Pipeline Research Council International, Inc. (PRCI), 2021. http://dx.doi.org/10.55274/r0012020.

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X-Ray Computed Tomography (XRCT) has been utilized for decades in medical and industrial imaging applications. The technology uses penetrating X-ray radiation to image the internal structure of an object by measuring attenuation along multiple transmission paths through the object. XRCT is a promising technology for application in imaging and sizing of flaws in oil and gas transmission pipelines and has been used in such applications in the past. However, the performance of the technology in this specific application to flaw sizing in oil and gas pipelines has not been fully evaluated. The purpose of this report is to provide a complete statistical analysis of the flaw sizing error of XRCT by consolidating flaw sizing information from past projects where both XRCT data and cross-sectional micrographs were available for comparison. Sizing error data were evaluated as a whole and as segments in order to determine overall sizing performance and per-flaw-type/per-measurement-type sizing performance, respectively
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Dennis, Jr, Wolkowicz J. E., and H. Sizing and Least Change Secant Methods. Defense Technical Information Center, 1990. http://dx.doi.org/10.21236/ada455266.

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DeAnnuntis, Christopher. Transit Extraboard Management-Optimum Sizing and Strategies. University of South Florida, 2007. http://dx.doi.org/10.5038/cutr-nctr-rr-2006-01.

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Koduru, Smitha. PR-244-193800-R01 Quantification of ILI Sizing for Severe Anomalies. Pipeline Research Council International, Inc. (PRCI), 2020. http://dx.doi.org/10.55274/r0011682.

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PRCI research project, EC-4-6 Improving Corrosion ILI Sizing Models for Long Complex Corrosion Anomalies (Koduru 2018), performed by C-FER Technologies (1999) Inc. ("C-FER"), involved collecting in-ditch high-resolution laser scan records, identifying complex corrosion anomalies, and conducting a burst pressure assessment considering inline inspection (ILI) sizing errors and the effect of interaction rules. A methodology for classifying complex corrosion using high-resolution laser scans was developed in that project. In addition, a secure database was developed to store the anonymized high-resolution laser scan data collected during the project. The project described in this report expanded the database with more than 100 high-resolution laser scans and associated ILI data. Severity criteria based on the corrosion cluster attributes that represent the corrosion morphology were developed using the expanded dataset. Exploratory data analysis was conducted to identify the relationship between ILI sizing errors and corrosion cluster attributes. Sizing errors were defined as a function of cluster dimensions, and sizing correction models were developed to estimate the actual maximum depth and length from the ILI maximum depth and length. The correction models were validated against matched pairs of laser scan and ILI severe corrosion clusters. Applying sizing corrections to severe clusters is shown to reduce the error in the estimated burst pressure capacity.
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John Beesley and Romeo S. Jurani. LAYOUT AND SIZING OF ESF ALCOVES AND REFUGE CHAMBERS. Office of Scientific and Technical Information (OSTI), 1995. http://dx.doi.org/10.2172/875341.

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Cazenave, Pablo, Katina Jimenez, Samarth Tandon, and Ravi Krishnamurthy. PR-328-203803-R01 Improve ILI Sizing Accuracy. Pipeline Research Council International, Inc. (PRCI), 2023. http://dx.doi.org/10.55274/r0000026.

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This multi-phased PHMSA/PRCI project aims to conduct a collaborative study (pipeline operators, ILI Technology Providers (TPs), subject matter experts, and consultants) to quantitatively measure and improve the detection and sizing capabilities of current corrosion ILI systems. A data-driven approach was used which identified problematic corrosion profiles based on the review of recent Root-Cause-Analysis reports of corrosion-related failures to design and construct an ILI corrosion test string containing features having similar profiles. All such profiles were then documented using the best possible NDE techniques. Three participating ILI TPs proposed appropriate inspection tools based on limited knowledge of the integrity conditions in the test string. A series of blind pull-through tests of the ILI systems were carried out, where the TPs delivered standard ILI reports for performance evaluation. The ILI TPs receive detailed feedback identifying the detection and sizing gaps. They are given a limited sample of detailed anomaly profile data to identify potential sources of detection and sizing improvement. A second series of ILI tests are performed and the changes in detection and sizing are analyzed and quantified for each problematic corrosion profile, identifying the improvements and the remaining gaps. The results and findings of this 3.5-year long project are presented in this Report. This research was funded in part under the Department of Transportation, Pipeline and Hazardous Materials Safety Administration's Pipeline Safety Research and Development Program. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Pipeline and Hazardous Materials Safety Administration, or the U.S. Government.
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McLendon, Debra, and Cynthia Istook. An Investigation of Sizing and Fit of Commercial Sewing Patterns. Iowa State University, Digital Repository, 2013. http://dx.doi.org/10.31274/itaa_proceedings-180814-864.

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Dipasquale, Chiara, Roberto Fedrizzi, Valeria Palomba, Alex Thür, and Dagmar Jähnig. Technical report on system sizing and optimised control strategies. IEA SHC Task 53, 2019. http://dx.doi.org/10.18777/ieashc-task53-2019-0007.

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