2017
DOI: 10.1016/j.ijheatmasstransfer.2017.02.001
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A double decentralized fuzzy inference method for estimating the time and space-dependent thermal boundary condition

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Cited by 32 publications
(4 citation statements)
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“…e agreement level includes agreement mechanism, issuance mechanism, and incentive mechanism. Its main function is to ensure data consistency and reliability between distributed nodes in the blockchain [21,22].…”
Section: Blockchainmentioning
confidence: 99%
“…e agreement level includes agreement mechanism, issuance mechanism, and incentive mechanism. Its main function is to ensure data consistency and reliability between distributed nodes in the blockchain [21,22].…”
Section: Blockchainmentioning
confidence: 99%
“…Related studies have shown that the fuzzy inference method has good calculation efficiency and robustness [13]. Compared with the low computational efficiency of genetic algorithms and the need for huge data to train of neural networks, the fuzzy inversion method has a brighter application prospect for solving the inverse geothermal heat sources problem [14].…”
Section: Introductionmentioning
confidence: 99%
“…A variety of fuzzy control and recognition problems have been solved by using FIM. Wang et al [36,37] proposed a decentralized FIM (DFIM) to reconstruct the surface heat flux and boundary shape of heat transfer system. Retrieval results indicated that the DFIM was more robust than other inverse methodologies such as CGM, GA, and dynamic matrix control (DMC).…”
Section: Introductionmentioning
confidence: 99%