Fitness-distance balance (FDB): A new selection method for meta-heuristic search algorithms

Knowledge-Based Systems, Journal Year: 2019, Volume and Issue: 190, P. 105169 - 105169

Published: Nov. 6, 2019

Language: Английский

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A systematic literature review on intelligent automation: Aligning concepts from theory, practice, and future perspectives

Advanced Engineering Informatics, Journal Year: 2021, Volume and Issue: 47, P. 101246 - 101246

Published: Jan. 1, 2021

Language: Английский

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Artificial intelligence in the field of nanofluids: A review on applications and potential future directions

Powder Technology, Journal Year: 2019, Volume and Issue: 353, P. 276 - 301

Published: May 15, 2019

Language: Английский

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Smart robotic mobile fulfillment system with dynamic conflict-free strategies considering cyber-physical integration

Advanced Engineering Informatics, Journal Year: 2019, Volume and Issue: 42, P. 100998 - 100998

Published: Oct. 1, 2019

Language: Английский

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Prioritizing and Evaluating Risks of Ordering and Prescribing in the Chemotherapy Process Using an Extended SWARA and MOORA under Fuzzy Z-numbers

Journal of Operations Intelligence, Journal Year: 2023, Volume and Issue: 1(1), P. 44 - 66

Published: Nov. 23, 2023

Assessing and prioritizing risks in the chemotherapy ordering prescribing processes is crucial to improving their safety quality. While FMEA commonly used for this purpose, it has some limitations. To overcome these limitations, a three-stage approach was proposed study enhance method. The first stage involved using identify assign values RPN parameters. In second stage, fuzzy SWARA method expert opinions were calculate weights of three factors. Finally, third prioritized Z-MOORA approach, which provides more accurate results due its consideration different factor weights, uncertainty, use Z-number theory reliability.

Language: Английский

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Short-term multi-step-ahead sector-based traffic flow prediction based on the attention-enhanced graph convolutional LSTM network (AGC-LSTM)

Neural Computing and Applications, Journal Year: 2024, Volume and Issue: unknown

Published: May 7, 2024

Abstract Accurate sector-based air traffic flow predictions are essential for ensuring the safety and efficiency of management (ATM) system. However, due to inherent spatial temporal dependencies flow, it is still a challenging problem. To solve this problem, some methods proposed considering relationship between sectors, while complicated spatiotemporal dynamics interdependencies route segments related sector not taken into account. address challenge, attention-enhanced graph convolutional long short-term memory network (AGC-LSTM) model applied improve prediction, in which structures considered first time. Specifically, networks (GCN)-LSTM was employed capture flight data, attention mechanism designed concentrate on informative features from key nodes at each layer AGC-LSTM model. The evaluated through case study typical enroute central–southern region China. prediction results show that MAE reduces by 14.4% compared best performing GCN-LSTM among other five models. Furthermore, involves comparative analyses assess influence segment range, input output sequence lengths, time granularities performance. This helps managers predict situations more accurately avoid implementing overly conservative or excessively aggressive measures sectors.

Language: Английский

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The design of an IoT-based route optimization system: A smart product-service system (SPSS) approach

Advanced Engineering Informatics, Journal Year: 2019, Volume and Issue: 42, P. 101006 - 101006

Published: Oct. 1, 2019

Language: Английский

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Optimizing Energy Consumption in Transportation: Literature Review, Insights, and Research Opportunities

Energies, Journal Year: 2020, Volume and Issue: 13(5), P. 1115 - 1115

Published: March 2, 2020

From airplanes to electric vehicles and trains, modern transportation systems require large quantities of energy. These vast amounts energy have be produced somewhere—ideally by using sustainable sources—and then brought the system. Energy is a scarce costly resource, which cannot always from renewable sources. Therefore, it critical consume as efficiently possible, that is, activities need carried out with an optimal intake energetic means. This paper reviews existing work on optimization consumption in area transportation, including road freight, passenger rail, maritime, air modes. The also analyzes how methods—of both exact approximate nature—have been used deal these energy-optimization problems. Finally, provides insights discusses open research opportunities regarding use new intelligent algorithms—combining metaheuristics simulation machine learning—to improve efficiency transportation.

Language: Английский

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A two-stage robust optimisation for terminal traffic flow problem

Applied Soft Computing, Journal Year: 2020, Volume and Issue: 89, P. 106048 - 106048

Published: Jan. 14, 2020

Language: Английский

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A novel comparative investigation of the effect of the number of neurons on the predictive performance of the artificial neural network: An experimental study on the thermal conductivity of ZrO ₂ nanofluid

International Journal of Energy Research, Journal Year: 2021, Volume and Issue: 45(13), P. 18944 - 18956

Published: June 26, 2021

In this study, the effect of number neurons on predictive performance artificial neural networks (ANN) has been investigated using experimental data. For purpose, 6 different ANN have developed by a total 60 data ZrO2/water nanofluid obtained from literature. with 5, 10, 15, 20, 25, and 30 neurons, all other parameters kept constant, only prediction investigated. The each calculated separately then their analyzed comparing them other. As consequence it seen that model most ideal 5 an average error rate 0.001%, highest margin 15 had 0.026%. light data, concluded are generally high tools, is not possible to reach standard correlation regulate be used in optimization ANN.

Language: Английский

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