The Neural Modeling for the Assessment of Hazardous Hydro Meteorological Phenomena Including the Case of the Providing a Sustainable Work (Reliability) on Transport

Haritonova, Larisa

doi:10.1007/978-3-319-70987-1_74

Cited by 6 publications

(4 citation statements)

References 10 publications

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“…The effectiveness of a decision support system or a policymaking tool [86][87][88][89][90] Other possible factors that could impact the performance of sectoral mobility practices, including aspects such as organizational innovation, that may not be commonly considered or well-known…”

Section: Displayed Phenomena Reviewed Articlesmentioning

confidence: 99%

Perspectives on Modeling Energy and Mobility Transitions for Stakeholders: A Dutch Case

Choi

Pessôa

Bonnema

2023

WEVJ

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We address the value of engaging stakeholders in energy and mobility transitions by using models. As a communication medium, models can facilitate the collaborative exploration of a future between modeling researchers and stakeholders. Developing models to engage stakeholders requires an understanding of state-of-the-art models and the usability of models from the stakeholder perspective. We employ mixed methods in our research. We present the overview of models that have been proposed to make sense of the transitions in the scientific literature through a systematic literature mapping (n = 105). We interviewed 10 stakeholders based in The Netherlands to elaborate on use cases in which models can benefit stakeholders in practice and the characteristics of usable models. We conclude our research by elaborating on two challenges of model design that modeling research can consider to engage stakeholders. First, we argue that understanding the epistemic requirements of both modeling researchers and stakeholders that models can simultaneously meet is crucial (e.g., questions addressed using models and assumptions). Second, we seek technical solutions for producing models in a time-wise manner and developing interfaces that allow models distant in formalism and represented phenomena to communicate in tandem. Our research creates awareness of the model design aspect by considering its usability.

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Section: Displayed Phenomena Reviewed Articlesmentioning

confidence: 99%

Perspectives on Modeling Energy and Mobility Transitions for Stakeholders: A Dutch Case

Choi

Pessôa

Bonnema

2023

WEVJ

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“…Today, the various techniques of simulating the processes are very common [7][8][9][10][11][12]. The analysis of the publications did not allow to reveal the dependences of the moment magnitude generalizing the experimental results obtained (using including the neural simulation method).…”

Section: Introductionmentioning

confidence: 99%

On the Issue of Neural Modeling of Some Dynamic Parameters of Earthquake

Haritonova¹

2018

IJET

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The author has attempted to refine the methods for modeling seismic effects. It is shown that applying the neural modeling and Artificial Neural Networks (ANN) are very prospective for analyzing such dynamic parameter earthquake foci as the moment magnitude. The further two input signals have been utilized: the power mode as well as the quantity of quakes. The author performed the analysis of regression for the predicted results and the target outputs. The article presents the equations of the regression (empirical dependences) for the outputs and target as well as the correlation factors for learning, assessment, checking, and the overall for the newly developed structure ANN for the moment magnitude. The use of the outcome obtained in this paper for the seismic designing and constructing structures and buildings will provide the conservation from possible consequences of earthquakes, reduce negative consequences for industry, the economy as a whole and human life.

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“…It has to be out of these charts that the results received explain the processes under examination wholly satisfactory. Having investigated the obtained data, it has been revealed that the optimum results are acquired when using the following algorithms: used as the learning function of adaption-the function of training for the gradient descent with the momentum, in the capacity of the transfer function-the hyperbolic tangent, as the performance function-Mean Squared Error (MSE) [20]. When using the above-mentioned algorithms and applying as the training function with the quasi-Newton technique BFGS (Figs.…”

Section: Introductionmentioning

confidence: 99%

“…The Applied Software Packages, The Results of the Research Let us make use of the Neural Network[1,[16][17][18][19][20] from MATLAB R2017. As a rule, neural network architecture (structure) consists of neurons (nodes) and layers.…”

mentioning

confidence: 99%

Neural Modeling of the Energy Efficiency Factor for Recuperators (Heat Exchangers) Using Impinging Jets for the Metallurgical Productions and Machine Building

Haritonova

2018

Proceedings of the 4th International Conference on Industrial Engineering

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The given work contains a complete application analysis for neural networks of the common logarithm of the energy factor for heat exchangers (recuperators) to heat the air from the heat exchange surface onto which the systems of impact plane-parallel jets are delivered in heating and thermal furnaces in machine building and at the metallurgical plants. The following input signals have been provided: the width of the slot nozzle, the jet axial length, the nondimensional length from the heat transfer surface to the nozzle cut (related to the width of the slot nozzle); the specific (per unit area of the heat transfer) consumption of air. The matching of the target records of the common logarithm of the energy efficiency factor with the output values was carried out (obtained using the artificial neural network in case of the network learning applying a quasi-Newton technique, BFGS, and the method of random increments) for the network structure 4-9-9-9-1. The analysis of regression for the obtained data and target outputs was implemented, and the correlation factors were given. The optimal results with the lesser values of Mean Squared Error and the closest to one of the values of the correlation coefficients were obtained when using the following algorithms: used as the learning function of adaption of the training function for the descent of a gradient with the momentum, as the transfer function-the hyperbolic tangent and the network learning using the quasi-Newton technique, BFGS. The results obtained can be applied in order to optimize or to develop the calculation techniques for the new highly efficient heat exchange devices exploiting the systems of plane-parallel impingement jets as well as for a wider use of the impinging jets technology in various industrial branches such as design and manufacturing for different new technologies including mechanical facilities.

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The Neural Modeling for the Assessment of Hazardous Hydro Meteorological Phenomena Including the Case of the Providing a Sustainable Work (Reliability) on Transport

Cited by 6 publications

References 10 publications

Perspectives on Modeling Energy and Mobility Transitions for Stakeholders: A Dutch Case

Perspectives on Modeling Energy and Mobility Transitions for Stakeholders: A Dutch Case

On the Issue of Neural Modeling of Some Dynamic Parameters of Earthquake

Neural Modeling of the Energy Efficiency Factor for Recuperators (Heat Exchangers) Using Impinging Jets for the Metallurgical Productions and Machine Building

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