Spectral Quantitative Analysis Model with Combining Wavelength Selection and Topology Structure Optimization

Cai, Boyan; Yu, Yonghong; Cao, Hui

doi:10.1155/2016/5616503

Cited by 2 publications

(2 citation statements)

References 33 publications

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“…Genetic algorithms, a class of biologically-inspired, evolutionary algorithms have found many applications engineering, biomedicine, chemometrics, genomics, and spectroscopy due to their ability in solving complex, nonlinear optimisation problems. Many variations and different implementation of this method can be found in the literature [49][50][51][52][53][54][55] .…”

Section: Heuristic Global Optimisation Search Methods a Different Apmentioning

confidence: 99%

Comparison of wavelength selection methods for in-vitro estimation of lactate: a new unconstrained, genetic algorithm-based wavelength selection

Mamouei

Budidha

Baishya

et al. 2020

Sci Rep

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Biochemical and medical literature establish lactate as a fundamental biomarker that can shed light on the energy consumption dynamics of the body at cellular and physiological levels. It is therefore, not surprising that it has been linked to many critical conditions ranging from the morbidity and mortality of critically ill patients to the diagnosis and prognosis of acute ischemic stroke, septic shock, lung injuries, insulin resistance in diabetic patients, and cancer. Currently, the gold standard for the measurement of lactate requires blood sampling. The invasive and costly nature of this procedure severely limits its application outside intensive care units. Optical sensors can provide a non-invasive, inexpensive, easy-to-use, continuous alternative to blood sampling. Previous efforts to achieve this have shown significant potential, but have been inconclusive. A measure that has been previously overlooked in this context, is the use of variable selection methods to identify regions of the optical spectrum that are most sensitive to and representative of the concentration of lactate. In this study, several wavelength selection methods are investigated and a new genetic algorithm-based wavelength selection method is proposed. This study shows that the development of more accurate and parsimonious models for optical estimation of lactate is possible. Unlike many existing methods, the proposed method does not impose additional locality constraints on the spectral features and therefore helps provide a much more granular interpretation of wavelength importance.

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Section: Heuristic Global Optimisation Search Methods a Different Apmentioning

confidence: 99%

Comparison of wavelength selection methods for in-vitro estimation of lactate: a new unconstrained, genetic algorithm-based wavelength selection

Mamouei

Budidha

Baishya

et al. 2020

Sci Rep

View full text Add to dashboard Cite

show abstract

“…Identification object can be done by pattern recognition ( [5], [6]), system learning ( [7]- [12]) and fuzzy logic ( [13], [14]). System learning is better then pattern recognition and fuzzy logic because system learning competent to adaptation and learning better in case environment change.…”

Section: Introductionmentioning

confidence: 99%

Development of a Gemstone Type Identification System Based on HSV Space Colour Using an Artificial Neural Network Back Propagation Algorithm

Maula¹,

Amrizal²,

Setianingrum³

et al. 2018

Proceedings of the International Conference on Science and Technology (ICOSAT 2017)

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A gemstone is a mineral stone that be formed from the result of geological processes and has a hardness above 7 Mohs. Nowadays, gemstones have become famous in Indonesian society. Many facts concerning the business of gemstone rings, including encouragement by the the central government for the gemstone souvenirs that are given to State guests by the President of Indonesia, gemstone contests and gemstone exhibitions have all contributed to pique the interest of researchers in the subject. This current research is undertaken to create a system that is able to identify three kinds of gemstone, namely, Ruby, Sapphire and Emerald using the Hue Saturation Value (HSV) colour space, image processing techniques and an Artificial Neural Network (ANN) back propagation algorithm by learning from examples. The hue from the HSV colour space of a gemstone will be used by the system for training. In the image processing, the system will crop, resize, convert from RGB to HSV, obtain a Hue colour and extract the colour as a 30x3 matrix. The extracted result will be used to train an ANN consisting of three input layers, three hidden layers and one output layer with targets that have been pre-determined. The results of the tests showed a degree of accuracy of 90.66% with 5 times of training and 25 times of testing on any type of gemstone. The result shows that using Artificial Neural Network Back Propagation in identification gemstone types is success, because the accuracy system has a highest percentage.

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Spectral Quantitative Analysis Model with Combining Wavelength Selection and Topology Structure Optimization

Cited by 2 publications

References 33 publications

Comparison of wavelength selection methods for in-vitro estimation of lactate: a new unconstrained, genetic algorithm-based wavelength selection

Comparison of wavelength selection methods for in-vitro estimation of lactate: a new unconstrained, genetic algorithm-based wavelength selection

Development of a Gemstone Type Identification System Based on HSV Space Colour Using an Artificial Neural Network Back Propagation Algorithm

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