A robust and efficient NLP formulation using graph theoretic principles for synthesis of heat exchanger networks

Shivakumar, K.; Narasimhan, Shankar

doi:10.1016/s0098-1354(02)00089-3

Cited by 28 publications

(12 citation statements)

References 14 publications

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“…The principal contribution of the present work is to show that the Fokas method may also be applied to the more general configurations of rods described above. The heat equation on graphs is important in engineering applications such as building and analyzing heat exchanger networks [19,23] and "channelling" heat through materials of differing conductivity [3].…”

Section: Introductionmentioning

confidence: 99%

Heat equation on a network using the Fokas method

Sheils

Smith

2015

J. Phys. A: Math. Theor.

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The problem of heat conduction on networks of multiply connected rods is solved by providing an explicit solution of the one-dimensional heat equation in each domain. The size and connectivity of the rods is known, but neither temperature nor heat flux are prescribed at the interface. Instead, the physical assumptions of continuity at the interfaces are the only conditions imposed. This work generalizes that of Deconinck, Pelloni, and Sheils [5] for heat conduction on a series of one-dimensional rods connected end-to-end to the case of general configurations.

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Section: Introductionmentioning

confidence: 99%

Heat equation on a network using the Fokas method

Sheils

Smith

2015

J. Phys. A: Math. Theor.

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“…Due to the technical limitations, patient information materials shelved in hospital rooms are not utilized very well. This issue may get some help from our study and the method we establish for NLP [8][9][10][11].…”

Section: Discussionmentioning

confidence: 99%

Extracting clinical information from free-text of pathology and operation notes via Chinese natural language processing

Zeng

Zhang

et al. 2010

2010 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)

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Many of surgical records containing the clinical information are in electronic forms, but a lot of them are still in free-text format in China. In this paper, we have an attempt to extract information with the Nature Language Processing (NLP) approach. The procedure of NLP is made up of three steps. First, given 36 free-text of operation notes, a physician manually annotates the information which he is interested in. Second, we extract the features of the annotated information. Third, several logistic regression models are built. Totally, 14 clinical data are extracted. The NLP tool was tested 364 operation notes. The accuracy of extraction is between 67.3%-96.7%. Our results indicate that the performance of the features we used to build the machine learningis good in extracting useful information from free-text Chinese operation notes for liver cancer. In the future, these features would explored on more broader clinical settings.

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“…Process operations problems such as scheduling have to account for the network structure of the underlying process; hence graphs serve as a suitable representation scheme. − Further, graph theory has been classically applied to flow network problems. In these, associated with each directed edge e m is a non-negative capacity c m as well as a flow f m .…”

Section: Graph Representation Of Scheduling Problemsmentioning

confidence: 99%

Large-Scale Refinery Crude Oil Scheduling by Integrating Graph Representation and Genetic Algorithm

Ramteke

2012

Ind. Eng. Chem. Res.

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Scheduling is widely studied in process systems engineering and is typically solved using mathematical programming. Although popular for many other optimization problems, evolutionary algorithms have not found wide applicability in such combinatorial optimization problems with large numbers of variables and constraints. Here we demonstrate that scheduling problems that involve a process network of units and streams have a graph structure which can be exploited to offer a sparse problem representation that enables efficient stochastic optimization. In the proposed structure adapted genetic algorithm, SAGA, only the subgraph of the process network that is active in any period is explicitly represented in the chromosome. This leads to a significant reduction in the representation, but additionally, most constraints can be enforced without the need for a penalty function. The resulting benefits in terms of improved search quality and computational performance are established by studying 24 different crude oil operations scheduling problems from the literature.

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A robust and efficient NLP formulation using graph theoretic principles for synthesis of heat exchanger networks

Cited by 28 publications

References 14 publications

Heat equation on a network using the Fokas method

Heat equation on a network using the Fokas method

Extracting clinical information from free-text of pathology and operation notes via Chinese natural language processing

Large-Scale Refinery Crude Oil Scheduling by Integrating Graph Representation and Genetic Algorithm

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