Relevant bibliographies by topics / GAS Algorithm

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'GAS Algorithm'

Author: Grafiati
Published: 4 June 2025
Last updated: 1 August 2025

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Journal articles on the topic "GAS Algorithm"

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Xu, Yonghui, Xi Zhao, Yinsheng Chen, and Zixuan Yang. "Research on a Mixed Gas Classification Algorithm Based on Extreme Random Tree." Applied Sciences 9, no. 9 (2019): 1728. http://dx.doi.org/10.3390/app9091728.

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Because of the low accuracy of the current machine olfactory algorithms in detecting two mixed gases, this study proposes a hybrid gas detection algorithm based on an extreme random tree to greatly improve the classification accuracy and time efficiency. The method mainly uses the dynamic time warping algorithm (DTW) to perform data pre-processing and then extracts the gas characteristics from gas signals at different concentrations by applying a principal component analysis (PCA). Finally, the model is established by using a new extreme random tree algorithm to achieve the target gas classifi
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Xu, Yonghui, Ruotong Meng, and Xi Zhao. "Research on a Gas Concentration Prediction Algorithm Based on Stacking." Sensors 21, no. 5 (2021): 1597. http://dx.doi.org/10.3390/s21051597.

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Machine learning algorithms play an important role in the detection of toxic, flammable and explosive gases, and they are extremely important for the study of mixed gas classification and concentration prediction methods. To solve the problem of low prediction accuracy of gas concentration regression prediction algorithms, a gas concentration prediction algorithm based on a stacking model is proposed in the current research. In this paper, the stochastic forest, extreme random regression tree and gradient boosting decision tree (GBDT) regression algorithms are selected as the base learning dev
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Wang, Zhijian, Yuchen He, Tian Luan, and Yong Long. "An Improved GAS Algorithm." Entropy 27, no. 3 (2025): 240. https://doi.org/10.3390/e27030240.

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This paper introduces an improved Grover Adaptive Search (GAS) algorithm. The GAS algorithm has been prove to achieve quadratic acceleration in the Constrained Polynomial Binary Optimization (CPBO) problem. Nevertheless, the acceleration effect of the GAS algorithm can be decreased by the poor threshold selection. This article uses the Quantum Approximate Optimization Algorithm (QAOA) to improve the initial threshold selection, thereby accelerating the convergence speed of the original GAS algorithm. The acceleration effect of the improved GAS algorithm is presented by the Max-Cut problem and
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Liu, Qing Feng. "An Improved Two-Phase GAI Particle Swarm Optimization Data Clustering Algorithm." Advanced Materials Research 490-495 (March 2012): 1431–35. http://dx.doi.org/10.4028/www.scientific.net/amr.490-495.1431.

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The well-known k-means algorithm that has been successfully applied to many practical clustering problems, suffers from several drawbacks due to its choice of initializations. In order to overcome k-means shortcomings, hybrid algorithms involving evolutionary algorithms are a good option for boosting the clustering performance. In this study, a hybrid two-phase algorithm for data clustering is proposed. In the first phase we utilize the new genetically improved PSO algorithm (GAI-PSO) which combines the standard velocity and position update rules of PSOs with the ideas of selection, mutation a
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Xia, Zhiyu, Zhengyi Xu, Dan Li, and Jianming Wei. "A Novel Method for Source Tracking of Chemical Gas Leakage: Outlier Mutation Optimization Algorithm." Sensors 22, no. 1 (2021): 71. http://dx.doi.org/10.3390/s22010071.

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Chemical industrial parks, which act as critical infrastructures in many cities, need to be responsive to chemical gas leakage accidents. Once a chemical gas leakage accident occurs, risks of poisoning, fire, and explosion will follow. In order to meet the primary emergency response demands in chemical gas leakage accidents, source tracking technology of chemical gas leakage has been proposed and evolved. This paper proposes a novel method, Outlier Mutation Optimization (OMO) algorithm, aimed to quickly and accurately track the source of chemical gas leakage. The OMO algorithm introduces a ran
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G P, Sanjana. "Natural Gas Price Prediction Using Machine Learning." International Journal for Research in Applied Science and Engineering Technology 9, no. VIII (2021): 126–34. http://dx.doi.org/10.22214/ijraset.2021.37291.

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Natural gas varies with season. In addition, natural gas supply, demand, storage, and imports are important indicators related to natural gas price. There are plenty of methods for analyzing and forecasting natural gas prices and machine learning is increasingly used. Machine learning algorithms can learn from historical relationships and trends in the data and make data-driven predictions or decisions. Here a new model for predicting price for natural gas by using Machine Learning concepts. Here some algorithms have been used to build the proposed model: Random Forest Regression, Linear Regre
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Dirgová Luptáková, Iveta, Marek Šimon, Ladislav Huraj, and Jiří Pospíchal. "Neural Gas Clustering Adapted for Given Size of Clusters." Mathematical Problems in Engineering 2016 (2016): 1–7. http://dx.doi.org/10.1155/2016/9324793.

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Clustering algorithms belong to major topics in big data analysis. Their main goal is to separate an unlabelled dataset into several subsets, with each subset ideally characterized by some unique characteristic of its data structure. Common clustering approaches cannot impose constraints on sizes of clusters. However, in many applications, sizes of clusters are bounded or known in advance. One of the more recent robust clustering algorithms is called neural gas which is popular, for example, for data compression and vector quantization used in speech recognition and signal processing. In this
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Rasna, Rasna, Moh Rahmat Irjii Matdoan, Nurlaela Kumala Dewi, Afferdhy Ariffien, and Seno Lamsir. "Implementation of Dijkstra and Ant Colony Algorithms for Web-based Shortest Route Search for LPG Gas Distribution." International Journal of Engineering, Science and Information Technology 5, no. 2 (2025): 175–81. https://doi.org/10.52088/ijesty.v5i2.805.

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National energy needs and efforts to fulfill them are currently vital issues to be discussed and resolved. One type of energy that still has various problems is fuel gas, especially LPG (Liquid Petroleum Gas). The gas scarcity in each region differs; not all regions experience gas shortages, and some areas have excess LPG gas stocks. The problem of the scarcity of 3 kilogram (Kg) LPG gas is not the first time this has happened. In recent months, people in some regions have complained about the scarcity of subsidized 3-kilogram (kg) LPG gas. This situation certainly makes it difficult for the c
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Yu, Hua Ping, and Mei Guo. "Data Prediction Algorithm in Wireless Sensor Networks for Oil and Gas Pipeline Monitoring." Applied Mechanics and Materials 721 (December 2014): 434–37. http://dx.doi.org/10.4028/www.scientific.net/amm.721.434.

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Energy efficient problem of wireless sensor networks for oil and gas pipeline systems is a fundamental problem, and furthermore, data prediction algorithm can effectively reduce the communication energy consumption of WSNs. This paper firstly analyzes existing common data prediction algorithms and the data characteristics of oil and gas pipelines monitoring data. And then introduces the three-layer architecture of WSNs. Lastly, the adaptability analysis of various prediction algorithms are proposed, the analysis result shows that the accuracy of data prediction algorithm can meet requirements
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Nabil, Emad, Amr Badr, and Ibrahim Farag. "An Immuno-Genetic Hybrid Algorithm." International Journal of Computers Communications & Control 4, no. 4 (2009): 374. http://dx.doi.org/10.15837/ijccc.2009.4.2454.

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The construction of artificial systems by drawing inspiration from natural systems is not a new idea. The Artificial Neural Network (ANN) and Genetic Algorithms (GAs) are good examples of successful applications of the biological metaphor to the solution of computational problems. The study of artificial immune systems is a relatively new field that tries to exploit the mechanisms of the natural immune system (NIS) in order to develop problem- solving techniques. In this research, we have combined the artificial immune system with the genetic algorithms in one hybrid algorithm. We proposed a m
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Dissertations / Theses on the topic "GAS Algorithm"

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Lovelady, April. "Development of a control algorithm for a dynamic gas mixing system." Texas A&M University, 2005. http://hdl.handle.net/1969.1/3775.

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An algorithm was developed to control the partial pressures of N2, O2, and CO2 in a gas mixing tank. The gases were premixed before being introduced into the low pressure Mars Dome. As an attempt to reduce the effects of pressure, the number of moles of the component gases was calculated and used to determine when gases needed to be added to the system or when gas concentrations needed to be diluted. There were two trial runs during each of the two experiments carried out. The total pressures in both the mixing tank and the Mars Dome remained within their limits of constraint during both trial
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Sampath, Suresh. "Fault diagnostics for advanced cycle marine gas turbine using genetic algorithm." Thesis, Cranfield University, 2003. http://dspace.lib.cranfield.ac.uk/handle/1826/10204.

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The major challenges faced by the gas turbine industry, for both the users and the manufacturers, is the reduction in life cycle costs , as well as the safe and efficient running of gas turbines. In view of the above, it would be advantageous to have a diagnostics system capable of reliably detecting component faults (even though limited to gas path components) in a quantitative marmer. V This thesis presents the development an integrated fault diagnostics model for identifying shifts in component performance and sensor faults using advanced concepts in genetic algorithm. The diagnostics model
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Maciel, Lucas da Silva. "A novel swarm-based algorithm for phase unwrapping." reponame:Repositório Institucional da UFSC, 2014. https://repositorio.ufsc.br/xmlui/handle/123456789/129595.

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Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Engenharia Mecânica, Florianópolis, 2014.<br>Made available in DSpace on 2015-02-05T21:16:46Z (GMT). No. of bitstreams: 1 331656.pdf: 3739147 bytes, checksum: 4434e631824c3243a2eb1e0e7148fe81 (MD5) Previous issue date: 2014<br>O correto funcionamento de tubulações subterrâneas para o transporte de gás e petróleo depende de um monitoramento frequente e correto dos estados de tensões. Avanços recentes na medição de tensões residuais têm aplicado métodos ópticos em conjunto com o al
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Smith, Nancy T. "Evolving Credible Facial Expressions with Interactive GAs." NSUWorks, 2012. http://nsuworks.nova.edu/gscis_etd/310.

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A major focus of research in computer graphics is the modeling and animation of realistic human faces. Modeling and animation of facial expressions is a very difficult task, requiring extensive manual manipulation by computer artists. Our primary hypothesis was that the use of machine learning techniques could reduce the manual labor by providing some automation to the process. The goal of this dissertation was to determine the effectiveness of using an interactive genetic algorithm (IGA) to generate realistic variations in facial expressions. An IGA's effectiveness is measured by satisfaction
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Thanawalla, Rutang Kirit. "Valuation of gas swing options using an extended least squares Monte Carlo algorithm." Thesis, Heriot-Watt University, 2006. http://hdl.handle.net/10399/144.

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Vick, Andrew W. "Genetic Fuzzy Controller for a Gas Turbine Fuel System." University of Cincinnati / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1291053513.

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Posinasetti, Praveen. "Process modelling and control of pulse gas metal arc welding of aluminum." Thesis, Queensland University of Technology, 2007. https://eprints.qut.edu.au/16530/1/Praveen_Posinasetti_Thesis.pdf.

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Recent developments in materials and material joining [specifically Aluminum and Pulse Gas Metal Arc Welding (GMAW-P) technology] have increased the scope and extent of their areas of application. However, stern market demand for the improved weld quality necessitates the need for automation of the welding processes. As a result, improvements in the process parameter feedback, sensing and control, are necessary to successfully develop the automated control technology for the welding processes. Hence, several aspects of the GMAW-P process have been investigated in this study in order to improve
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Posinasetti, Praveen. "Process modelling and control of pulse gas metal arc welding of aluminum." Queensland University of Technology, 2007. http://eprints.qut.edu.au/16530/.

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Recent developments in materials and material joining [specifically Aluminum and Pulse Gas Metal Arc Welding (GMAW-P) technology] have increased the scope and extent of their areas of application. However, stern market demand for the improved weld quality necessitates the need for automation of the welding processes. As a result, improvements in the process parameter feedback, sensing and control, are necessary to successfully develop the automated control technology for the welding processes. Hence, several aspects of the GMAW-P process have been investigated in this study in order to improve
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Jang, Won-Hyouk. "Novel cost allocation framework for natural gas processes: methodology and application to plan economic optimization." Diss., Texas A&M University, 2004. http://hdl.handle.net/1969.1/368.

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Natural gas plants can have multiple owners for raw natural gas streams and processing facilities as well as for multiple products. Therefore, a proper cost allocation method is necessary for taxation of the profits from natural gas and crude oil as well as for cost sharing among gas producers. However, cost allocation methods most often used in accounting, such as the sales value method and the physical units method, may produce unacceptable or even illogical results when applied to natural gas processes. Wright and Hall (1998) proposed a new approach called the design benefit method (DBM),
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Kvam, Asgeir. "Detection of Stiction in Control Valves : an Algorithm for the Offshore Oil and Gas Industry." Thesis, Norwegian University of Science and Technology, Department of Engineering Cybernetics, 2009. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-8973.

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<p>Valve stiction is one of the largest stand-alone reasons for oscillatory behavior in process industry. It is reported by Siemens Oil and Gas that valve stiction is a problem that is hard and time consuming to detect at offshore production plants for oil and gas. As a result, Siemens Oil and Gas wants to develop an algorithm that detects stiction. The algorithm is thought to be a feature of the logging system of Siemens in the future. To better understand the problem and scope of stiction at a offshore oil and gas production plant, the effects of stiction is studied on a model of such a pl
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Books on the topic "GAS Algorithm"

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United States. Environmental Protection Agency. Office of Transportation and Air Quality. Assessment and Standards Division. MOVES2010 fuel adjustment and air toxic emission calculation algorithm: Development and results. Assessment and Standards Division, Office of Transportation and Air Quality, U.S. Environmental Protection Agency, 2011.

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Gnoffo, Peter A. An upwind-biased, point-implicit relaxation algorithm for viscous, compressible perfect-gas flows. National Aeronautics and Space Administration, Office of Management, Scientific and Technical Information Division, 1990.

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Gnoffo, Peter A. An upwind-biased, point-implicit relaxation algorithm for viscous, compressible perfect-gas flows. Langley Research Center, 1990.

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Gnoffo, Peter A. An upwind-biased, point-implicit relaxation algorithm for viscous, compressible perfect-gas flows. National Aeronautics and Space Administration, Office of Management, Scientific and Technical Information Division, 1990.

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Müller-Hannemann, Matthias, and Stefan Schirra. Algorithm engineering: Bridging the gap between algorithm theory and practice. Springer, 2010.

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United States. National Aeronautics and Space Administration., ed. Shock capturing schemes for multidimensional flow: Final report. National Aeronautics and Space Administration, 1992.

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Stephen, Richter, Davis Lawrence D, and United States. National Aeronautics and Space Administration., eds. A homotopy algorithm for digital optimal projection control, GASD-HADOC. Harris Corp., Government Aerospace System Division, 1993.

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Collins, E. A homotopy algorithm for digital optimal projection control, GASD-HADOC. Harris Corp., Government Aerospace System Division, 1993.

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McClain, C. R. An analysis of GAC sampling algorithms: A case study. National Aeronautics and Space Administration, Goddard Space Flight Center, 1992.

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Chang, I.-Lok. Data processing algorithms for inferring stratospheric gas concentrations from balloon-based solar occultation data. U.S. Dept. of Commerce, National Oceanic and Atmospheric Administration, National Environmental Satellite, Data, and Information Service, 1987.

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Book chapters on the topic "GAS Algorithm"

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Kishor Yadav, Nand, and Mukesh Saraswat. "Chaotic Henry Gas Solubility Optimization Algorithm." In Intelligent Learning for Computer Vision. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4582-9_20.

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Ye-hang, Zhu, Li Yan-ling, and Yang Xian-wen. "An Improved Document Clustering Algorithm Based on Neural Gas Algorithm." In Recent Advances in Computer Science and Information Engineering. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-25781-0_28.

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Stecchi, Ugo, Gaetano Abbatantuono, and Massimo La Scala. "Optimal Gas Flow Algorithm for Natural Gas Distribution Systems in Urban Environment." In From Smart Grids to Smart Cities. John Wiley & Sons, Inc., 2017. http://dx.doi.org/10.1002/9781119116080.ch6.

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Satizábal, Héctor F., Andres Pérez-Uribe, and Marco Tomassini. "Prototype Proliferation in the Growing Neural Gas Algorithm." In Artificial Neural Networks - ICANN 2008. Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-87559-8_82.

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Saavedra, Carolina, Sebastián Moreno, Rodrigo Salas, and Héctor Allende. "Robustness Analysis of the Neural Gas Learning Algorithm." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11892755_58.

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Haratsu, Takumi, Motoki Sakaue, Haruka Matsukura, Patrick P. Neumann, and Hiroshi Ishida. "Simulating a Gas Source Localization Algorithm with Gas Dispersion Produced by Recorded Outdoor Wind." In ROBOT2022: Fifth Iberian Robotics Conference. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-21062-4_9.

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Shyue, Keh-Ming. "An Eulerian Interface-Sharpening Algorithm for Compressible Gas Dynamics." In Modeling, Simulation and Optimization of Complex Processes - HPSC 2012. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-09063-4_18.

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Faigl, Jan, and Miloš Prágr. "Incremental Traversability Assessment Learning Using Growing Neural Gas Algorithm." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-19642-4_17.

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Glover, David M., Nelson M. Frew, Scott J. Mccue, and Erik J. Bock. "A Multi-Year Time Series of Global Gas Transfer Velocity from the TOPEX Dual Frequency, Normalized Radar Backscatter Algorithm." In Gas Transfer at Water Surfaces. American Geophysical Union, 2013. http://dx.doi.org/10.1029/gm127p0325.

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Zhou, Daiyong. "Research on Natural Gas Pipeline Leak Detection Algorithm and Simulation." In Proceedings of the 2015 Chinese Intelligent Automation Conference. Springer Berlin Heidelberg, 2015. http://dx.doi.org/10.1007/978-3-662-46463-2_36.

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Conference papers on the topic "GAS Algorithm"

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Gao, Lin, Binfei Zhu, Haipeng Min, and Ke Zhang. "Research on forecasting of daily gas consumption of city gate stations of natural gas pipeline network based on deep learning." In 4th International Conference on Automation Control. Algorithm and Intelligent Bionics, edited by Jing Na and Shuping He. SPIE, 2024. http://dx.doi.org/10.1117/12.3039332.

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Biondo, Elliott, Vladimir Sobes, Andrew Holcomb, Steven Hamilton, and Thomas Evans. "Algorithm for Free Gas Elastic Scattering Without Rejection Sampling." In Mathematics and Computation 2021. American Nuclear Society, 2021. https://doi.org/10.13182/xyz-33659.

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Mohanty, Prases K., and Dayal R. Parhi. "A New Real Time Path Planning for Mobile Robot Navigation Using Invasive Weed Optimization Algorithm." In ASME 2014 Gas Turbine India Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/gtindia2014-8166.

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In this article a new optimal path planner for mobile robot navigation based on invasive weed optimization (IWO) algorithm has been addressed. This ecologically inspired algorithm is based on the colonizing property of weeds and distribution. A new fitness function has been formed between robot to goal and obstacles, which satisfied the conditions of both obstacle avoidance and target seeking behavior in robot present in the environment. Depending on the fitness function value of each weed in the colony the robot that avoids obstacles and navigating towards goal. The optimal path is generated
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Gallis, M. A., J. R. Torczynski, D. J. Rader, G. A. Bird, and Takashi Abe. "An Improved-Accuracy DSMC Algorithm." In RARIFIED GAS DYNAMICS: Proceedings of the 26th International Symposium on Rarified Gas Dynamics. AIP, 2008. http://dx.doi.org/10.1063/1.3076490.

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Garg, Ankit, Aman Sharma, Saurabh Rajvanshi, et al. "Optimization of Gas Injection Network Using Genetic Algorithm: A Solution for Intermittent Gas Lift Wells." In SPE Canadian Energy Technology Conference and Exhibition. SPE, 2024. http://dx.doi.org/10.2118/218028-ms.

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Abstract Multiple intermittent gas lift (IGL) wells are typically connected to a centralized high-pressure gas source, which can result in significant fluctuations in gas injection header pressure and subsequent liquid surges in the well fluid header when gas injection is initiated simultaneously in multiple wells. To address the challenge of gas injection interference among intermittent gas lift wells, we propose a mathematical model that utilizes genetic algorithm to optimize the staggering of time cycles, with the goal of achieving minimal interference. Genetic algorithms approach provides
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Karthikeyan, Ganesh Ram Ramanujam, Akshan Paresh Mehta, Karthikeyan Ramanujam, and Kalaichelvi Venkatesan. "Design Optimization of Wind Turbine Using Fluid Structural Interaction Analysis and Genetic Algorithm." In ASME 2014 Gas Turbine India Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/gtindia2014-8296.

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Aerodynamics of wind turbine blade is an important field of research. In the present study, a multi stage optimization process has been evaluated on a baseline wind turbine blade. Genetic Algorithms (GAs) are applied as a generative and search procedure to look for optimized design solutions in terms of aerodynamic performance of the airfoil selected for the study. The MatLab Genetic Algorithm toolbox interfaced with Xfoil, an interactive program for the design and analysis of airfoils, was implemented for the profile design optimisation. To analyse the performance of the optimized profile, th
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Khan, Abdul Muqtadir, Abdullah BinZiad, and Abdullah Al Subaii. "Boosting Algorithm Choice in Predictive Machine Learning Models for Fracturing Applications." In SPE/IATMI Asia Pacific Oil & Gas Conference and Exhibition. SPE, 2021. http://dx.doi.org/10.2118/205642-ms.

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Abstract With the advancement in machine learning (ML) applications, some recent research has been conducted to optimize fracturing treatments. There are a variety of models available using various objective functions for optimization and different mathematical techniques. There is a need to extend the ML techniques to optimize the choice of algorithm. For fracturing treatment design, the literature for comparative algorithm performance is sparse. The research predominantly shows that compared to the most commonly used regressors and classifiers, some sort of boosting technique consistently ou
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Lian, Y. Y., K. C. Tseng, Y. S. Chen, et al. "An Improved Parallelized Hybrid DSMC-NS Algorithm." In RARIFIED GAS DYNAMICS: Proceedings of the 26th International Symposium on Rarified Gas Dynamics. AIP, 2008. http://dx.doi.org/10.1063/1.3076499.

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Ai, Xinbo, and Qinfang Ji. "Research on Gas User Clustering Algorithm." In ICCIR 2022: 2022 2nd International Conference on Control and Intelligent Robot. ACM, 2022. http://dx.doi.org/10.1145/3548608.3559307.

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Alexander, Francis J. "Algorithm Refinement for Stochastic Partial Differential Equations." In RAREFIED GAS DYNAMICS: 23rd International Symposium. AIP, 2003. http://dx.doi.org/10.1063/1.1581638.

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Reports on the topic "GAS Algorithm"

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Kelner, E., Darren George, Marybeth Nored, and Russell C. Burkey. NMCQ4YK Development of a Low Cost Inferential Natural Gas Energy Flow Rate Prototype Retrofit Module. Pipeline Research Council International, Inc. (PRCI), 2008. http://dx.doi.org/10.55274/r0011158.

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In 1998, a multi-year project to develop a working prototype instrument module for natural gas energy measurement was initiated. The module will be used to retrofit a natural gas custody transfer flow meter for energy measurement, at a cost an order of magnitude lower than a gas chromatograph. Development and evaluation of the prototype energy meter in 2002-2003 included: (1) refinement of the algorithm used to infer properties of the natural gas stream, such as heating value; (2) evaluation of potential sensing technologies for nitrogen content, improvements in carbon dioxide measurements, an
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Milora, S. L., S. K. Combs, M. J. Gouge, and R. W. Kincaid. QUICKGUN: An algorithm for estimating the performance of two-stage light gas guns. Office of Scientific and Technical Information (OSTI), 1990. http://dx.doi.org/10.2172/6428575.

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Gattoni and Olsen. PR-179-10211-R01 Advanced Control Techniques and Sensors for Gas Engines with NSCR. Pipeline Research Council International, Inc. (PRCI), 2012. http://dx.doi.org/10.55274/r0010987.

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High exhaust emissions reduction efficiencies from a spark ignited (SI) internal combustion engine utilizing an NSCR catalyst system requires complex fuel control strategies. The allowable equivalence ratio operating range is very narrow where NSCR systems achieve high exhaust emissions reduction efficiencies of multiple species. Current fuel control technologies utilizing lambda sensor feedback are reported to be unable to sustain these demands for extended operation periods and when transients are introduced. Lambda sensor accuracy is the critical issue with current fuel controllers. The goa
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Berns, David M., and T. P. Orlando. Implementation Schemes for the Factorized Quantum Lattice-Gas Algorithm for the One Dimensional Diffusion Equation using Persistent-Current Qubits. Defense Technical Information Center, 2005. http://dx.doi.org/10.21236/ada496010.

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Takada, Yogo, Toshimasa Kotani, Kazuma Ito, Sang-kyu Kim, and Tomoyuki Wakisaka. Application of a Genetic Algorithm to the Numerical Analysis of Thermo-Fluid Flow and Catalytic Reaction in an Exhaust Gas Three-Way Catalyzer. SAE International, 2005. http://dx.doi.org/10.4271/2005-08-0487.

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Morkun, Vladimir S., Natalia V. Morkun, and Andrey V. Pikilnyak. Augmented reality as a tool for visualization of ultrasound propagation in heterogeneous media based on the k-space method. [б. в.], 2020. http://dx.doi.org/10.31812/123456789/3757.

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For programming the AR tools, interactive objects and creating the markers, the method of fiber spaces (k-space) for modeling of ultrasonic wave propagation in an inhomogeneous medium using coarse grids, with maintaining the required accuracy was used. The algorithm and tools of augmented reality were introduced into the adaptive control system of the pulp gas phase in the iron ore flotation process using a control action on the basis of high-energy ultrasound dynamic effects generated by ultrasonic phased arrays. The tools of augmented reality based on k-space methods allow to facilitate wide
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Borgwardt, Stefan, Walter Forkel, and Alisa Kovtunova. Finding New Diamonds: Temporal Minimal-World Query Answering over Sparse ABoxes. Technische Universität Dresden, 2019. http://dx.doi.org/10.25368/2023.223.

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Lightweight temporal ontology languages have become a very active field of research in recent years. Many real-world applications, like processing electronic health records (EHRs), inherently contain a temporal dimension, and require efficient reasoning algorithms. Moreover, since medical data is not recorded on a regular basis, reasoners must deal with sparse data with potentially large temporal gaps. In this paper, we introduce a temporal extension of the tractable language ELH⊥, which features a new class of convex diamond operators that can be used to bridge temporal gaps. We develop a com
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de Luis, Mercedes, Emilio Rodríguez, and Diego Torres. Machine learning applied to active fixed-income portfolio management: a Lasso logit approach. Banco de España, 2023. http://dx.doi.org/10.53479/33560.

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The use of quantitative methods constitutes a standard component of the institutional investors’ portfolio management toolkit. In the last decade, several empirical studies have employed probabilistic or classification models to predict stock market excess returns, model bond ratings and default probabilities, as well as to forecast yield curves. To the authors’ knowledge, little research exists into their application to active fixed-income management. This paper contributes to filling this gap by comparing a machine learning algorithm, the Lasso logit regression, with a passive (buy-and-hold)
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Yepez, Jeffrey. Quantum Algorithms for Computational Physics: Volume 3 of Lattice Gas Dynamics. Defense Technical Information Center, 2007. http://dx.doi.org/10.21236/ada474659.

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Pound, B. G. GRI-99-0000 Gap Analysis of the GRI Research Program on Internal Corrosion. Pipeline Research Council International, Inc. (PRCI), 1999. http://dx.doi.org/10.55274/r0010720.

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Extensive information on the corrosion of steel in aqueous CO2 systems is now available from this program and numerous other sources. This information was reviewed to identify what research has been performed and what research remains to be undertaken to develop a expert system/risk management program. Four areas were examined: corrosion mechanisms, mitigation strategies, monitoring techniques, and models/risk assessment. There were five gaps in mechanisms (two for bacteria and one each for flow rate/chloride concentration, hydrocarbons, and organic acids) and four gaps in mitigation (antibiof
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