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Advances in Condition Monitoring, Optimization and Control for Complex Industrial Processes
| Advances in Condition Monitoring, Optimization and Control for Complex Industrial Processes |
| Autore | Gao Zhiwei |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 online resource (514 p.) |
| Soggetto topico | Technology: general issues |
| Soggetto non controllato |
acetonitrile
additive white Gaussian noises (AWGN) association matrix behavior transfer belief statistic cascading failures CFSFDP algorithm close distance coal seams coarse model complex network theory condition monitoring constitutive model control chart control problem cumulative distribution function data-driven methods dead time deep deterministic policy gradient deep reinforcement learning deviation control distributed generation (DG) distributed model predictive control drilling machine energy conversion systems event-based EWT failure criterion fast Fourier transform (FFT) Fast-Newman algorithm fault classification fault diagnosis fault prognosis flexible flow shop flexible flow shop scheduling flotation process full-heat integration fuzzy logic gamma distribution goaf gob-side entry retaining by roof cutting graph theory hardware experiment Holmquist-Johnson-Cook constitutive model of briquette Hopfield neural network Hybrid Attack Graph improved compact genetic algorithm in-situ monitoring incomplete data INSGA-II Level-of-Resilience limited buffer link-addition strategy load identification local scheduling loop design memetic salp swarm algorithm microalgae MIMO temperature control in heating process system multi-input and multi-output system multi-input multi-output (MIMO) temperature system multi-linear principal component analysis (MPCA) multi-objective optimization multi-queue limited buffers multiscale fuzzy entropy n/a neutrosophic statistic non-pillar nonlinear adaptive backstepping controller disturbance observer numerical simulation oil and gas optimal nonlinear adaptive control parameter acquisition parameter uncertainties perturbation observer PID PNN pole-zero cancelation potential crowding distance power systems pressure swing distillation probability density function of the Gaussian distribution process control public buffer raceway reactive power optimization reagent dosage refrigeration reinforcement learning resilient control roadway supporting self-learning semiconductor bonding equipment-grouping method separation simulated annealing algorithm slow-mode-based control split Hopkinson pressure bar experiment stability state-action chains static and dynamic planning steam power plant steam/water loop stress distribution temperature difference temperature differences time series froth image topology transfer bees optimizer transient response tunnel boring machine uncorrelated multi-linear principal component analysis (UMPCA) variable geometry turbocharger voltage source converter water wind turbine wind turbine systems |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557338303321 |
Gao Zhiwei
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Stability Analysis of Neural Networks / Grienggrai Rajchakit, Praveen Agarwal, Sriraman Ramalingam
| Stability Analysis of Neural Networks / Grienggrai Rajchakit, Praveen Agarwal, Sriraman Ramalingam |
| Autore | Rajchakit, Grienggrai |
| Pubbl/distr/stampa | Singapore, : Springer, 2021 |
| Descrizione fisica | xxvi, 404 p. : ill. ; 24 cm |
| Altri autori (Persone) |
Agarwal, Praveen
Ramalingam, Sriraman |
| Soggetto topico |
93-XX - Systems theory; control [MSC 2020]
93D05 - Lyapunov and other classical stabilities (Lagrange, Poisson, $L^p, l^p$, etc.) [MSC 2020] 93B70 - Networked control [MSC 2020] 93C43 - Delay control/observation systems [MSC 2020] |
| Soggetto non controllato |
Asymptotic stability
Bidirectional associative memory Cellular neural network Cohen-Grossberg neural network Exponential stability Gene regulatory network Hopfield neural network Lyapunov-Krasovskii functional Markovian jumping Neural networks Robust stability Stability |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN0275520 |
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Rajchakit, Grienggrai
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| Singapore, : Springer, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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Stability Analysis of Neural Networks / Grienggrai Rajchakit, Praveen Agarwal, Sriraman Ramalingam
| Stability Analysis of Neural Networks / Grienggrai Rajchakit, Praveen Agarwal, Sriraman Ramalingam |
| Autore | Rajchakit, Grienggrai |
| Pubbl/distr/stampa | Singapore, : Springer, 2021 |
| Descrizione fisica | xxvi, 404 p. : ill. ; 24 cm |
| Altri autori (Persone) |
Agarwal, Praveen
Ramalingam, Sriraman |
| Soggetto topico |
93-XX - Systems theory; control [MSC 2020]
93B70 - Networked control [MSC 2020] 93C43 - Delay control/observation systems [MSC 2020] 93D05 - Lyapunov and other classical stabilities (Lagrange, Poisson, $L^p, l^p$, etc.) [MSC 2020] |
| Soggetto non controllato |
Asymptotic stability
Bidirectional associative memory Cellular neural network Cohen-Grossberg neural network Exponential stability Gene regulatory network Hopfield neural network Lyapunov-Krasovskii functional Markovian jumping Neural networks Robust stability Stability |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN00275520 |
|
Rajchakit, Grienggrai
|
||
| Singapore, : Springer, 2021 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
| ||