Energy efficiency, carbon emissions, and measures towards their improvement in the food and beverage sector for six European countries

Meyers, Steven P.; Schmitt, Bastian; Chester-Jones, Mae; Sturm, Barbara

doi:10.1016/j.energy.2016.03.117

Cited by 67 publications

(35 citation statements)

References 34 publications

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“…To optimize the hyperparameters of each modelling paradigm, the cross validation is adopted with the cross-validation root mean square error (CVMSE) as the performance metric [41]. The optimal number of nearestneighbour columns of KNN impute algorithm is selected in the range of [1,5]. For RF algorithm, the number of trees in the forest considered ranges from 100 to 500 with the interval of 100.…”

Section: ) Compared Algorithmsmentioning

confidence: 99%

“…O VER the last decade, various issues associated to the global warming due the substantial anthropological consumption of fossil fuels have become the global concern [1]. As a consequence, the UK government has committed to reduce its greenhouse gas/carbon dioxide emission (GHG) by 80% by 2050 (compared to the 1990's level) which is a huge leap from the current emissions levels in the past three decades [2].…”

Section: Introductionmentioning

confidence: 99%

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Missing Data Imputation With OLS-Based Autoencoder for Intelligent Manufacturing

Wang

Gan

et al. 2019

IEEE Trans. on Ind. Applicat.

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Section: ) Compared Algorithmsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Missing Data Imputation With OLS-Based Autoencoder for Intelligent Manufacturing

Wang

Gan

et al. 2019

IEEE Trans. on Ind. Applicat.

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“…The issue of improving quality of the finished product, energy intensity, environmental-friendliness of production [1][2][3], is a relevant task for food producers.…”

Section: A G a V R I L O Vmentioning

confidence: 99%

Studying the operation of innovative equipment for thermomechanical treatment and dehydration of food raw materials

Burdo¹,

Bezbakh²,

Kepin³

et al. 2019

EEJET

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“…O VER recent years, the issues associated with global warming and the limitation of energy resource have been of worldwide concern [1]. Consequently, the UK government has committed to reduce its greenhouse gas/carbon dioxide emissions (GHG) by 80% by 2050 (compared to the 1990's level) which is a huge leap from the current emissions level [2].…”

Section: Introductionmentioning

confidence: 99%

Data Augmentation for Intelligent Manufacturing with Generative Adversarial Framework

Wang

Gan

et al. 2019

2019 1st International Conference on Industrial Artificial Intelligence (IAI)

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Motivated by the global economy greatly shaped by the manufacturing technology, more research on the intelligent manufacturing is studied. This paper firstly introduces an energy monitoring and data acquisition system namely the Point Energy Technology, which has been developed by the team and installed in a local bakery. While there is always lack of data because of various reasons, such as measurement or transmission mistakes during data collection. To solve this problem, we introduce a generative adversarial framework which is based on a game theory for data augmentation. This framework consists of two multi-layer perceptron networks-generator and discriminator. The upgrade framework with Q-net that extracts the latent variables from real data is proposed. To control the number of parameters, Q-net shares the structure with discriminator except the last layer. In addition, the two optimization methods, mini-batch gradient descent and adaptive moment estimation are adopted to tune the parameters. To evaluate the performance of these algorithms, the collected data from baking process is used in the experiment. Considering the reality, the missing data is processed into the state of missing completely at random (non-time series missing data). The experimental results illustrate that the latent generative adversarial framework with adaptive moment estimation could generated samples of good quality for non-time series missing data.

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Energy efficiency, carbon emissions, and measures towards their improvement in the food and beverage sector for six European countries

Cited by 67 publications

References 34 publications

Missing Data Imputation With OLS-Based Autoencoder for Intelligent Manufacturing

Missing Data Imputation With OLS-Based Autoencoder for Intelligent Manufacturing

Studying the operation of innovative equipment for thermomechanical treatment and dehydration of food raw materials

Data Augmentation for Intelligent Manufacturing with Generative Adversarial Framework

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