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Advances in Computational Intelligence Applications in the Mining Industry
| Advances in Computational Intelligence Applications in the Mining Industry |
| Autore | Ganguli Rajive |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 online resource (324 p.) |
| Soggetto topico |
History of engineering & technology
Technology: general issues |
| Soggetto non controllato |
accidents
artificial intelligence ball mill throughput Bayesian network Bayesian Network Structure Learning (BNSL) bitumen extraction bitumen processability blast impact bluetooth beacon classification and regression tree coal convolutional neural networks damage risk analysis data analytics in mining decision trees digital twin dimensionality reduction discrete event simulation empirical model epithermal gold fragmentation fragmentation size analysis gaussian naïve bayes geological uncertainty geostatistics grinding circuits health and safety management hyperspectral imaging image analysis k-nearest neighbors knowledge discovery macerals machine learning masonry buildings measurement while drilling mine optimization mine safety and health mine worker fatigue mine-to-mill mineral prospectivity mapping minerals processing mining mining equipment uncertainties mining exploitation mining geology modes of operation multispectral imaging multivariate statistics n/a Naive Bayes narratives natural language processing neighbourhood component analysis non-additivity oil sands operational data ore control orebody uncertainty partial least squares regression petrographic analysis point cloud scaling Q-learning random forest random forest algorithm random forest classification random forest model rock type semantic segmentation stockpiles structure from motion support vector machine tactical geometallurgy transport route transport time truck dispatching underground mine unstructured data variable importance |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557613103321 |
Ganguli Rajive
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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AI and Financial Markets
| AI and Financial Markets |
| Autore | Hamori Shigeyuki |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 |
| Descrizione fisica | 1 online resource (230 p.) |
| Soggetto topico | Economics, Finance, Business and Management |
| Soggetto non controllato |
agent based simulation
algorithmic trading Artificial Intelligence artificial market asset allocation ATR autoencoder blockchain BlockCloud CAR regulation CfD community finances consensus algorithms contract for difference deep learning deep reinforcement learning economic policy exchange rates financial market simulation fiscal flexibility fundamentals hidden markov model individualized financial arrangements interpretability long short-term memory LSTM machine learning neural network neural networks portfolio prediction price momentum Q-learning random forest reinforcement learning RL simulation Stop Loss support vector machine sustainable financial services term structure of interest rates text mining topic model Turtle uncertainty yield curve |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557584903321 |
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Hamori Shigeyuki
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| Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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DNA Computing Based Genetic Algorithm : Applications in Industrial Process Modeling and Control / Jili Tao, Ridong Zhang, Yong Zhu
| DNA Computing Based Genetic Algorithm : Applications in Industrial Process Modeling and Control / Jili Tao, Ridong Zhang, Yong Zhu |
| Autore | Tao, Jili |
| Pubbl/distr/stampa | Singapore, : Springer, 2020 |
| Descrizione fisica | ix, 274 p. : ill. ; 24 cm |
| Altri autori (Persone) |
Zhang, Ridong
Zhu, Yong |
| Soggetto topico |
90-XX - Operations research, mathematical programming [MSC 2020]
93-XX - Systems theory; control [MSC 2020] 90C59 - Approximation methods and heuristics in mathematical programming [MSC 2020] 93C95 - Application models in control theory [MSC 2020] |
| Soggetto non controllato |
Distributed parameter modeling
Fuzzy control Genetic algorithm Model Predictive Control Multi-objective optimization Neural network Nonlinear modeling Principle component analysis Q-learning |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0250115 |
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Tao, Jili
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| Singapore, : Springer, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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DNA Computing Based Genetic Algorithm : Applications in Industrial Process Modeling and Control / Jili Tao, Ridong Zhang, Yong Zhu
| DNA Computing Based Genetic Algorithm : Applications in Industrial Process Modeling and Control / Jili Tao, Ridong Zhang, Yong Zhu |
| Autore | Tao, Jili |
| Pubbl/distr/stampa | Singapore, : Springer, 2020 |
| Descrizione fisica | ix, 274 p. : ill. ; 24 cm |
| Altri autori (Persone) |
Zhang, Ridong
Zhu, Yong |
| Soggetto topico |
90-XX - Operations research, mathematical programming [MSC 2020]
90C59 - Approximation methods and heuristics in mathematical programming [MSC 2020] 93-XX - Systems theory; control [MSC 2020] 93C95 - Application models in control theory [MSC 2020] |
| Soggetto non controllato |
Distributed parameter modeling
Fuzzy control Genetic Algorithms Model Predictive Control Multi-objective optimization Neural network Nonlinear modeling Principle component analysis Q-learning |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN00250115 |
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Tao, Jili
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| Singapore, : Springer, 2020 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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Evolutionary Computation 2020
| Evolutionary Computation 2020 |
| Autore | Wang Gai-Ge |
| Pubbl/distr/stampa | Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021 |
| Descrizione fisica | 1 online resource (442 p.) |
| Soggetto topico | Technology: general issues |
| Soggetto non controllato |
0-1 knapsack problem
ant colony optimization assortative mating binary whale optimization algorithm bug detection bWOA-S bWOA-V citation classification coevolution constrained optimization cuckoo search algorithm decomposition-based multi-objective optimisation differential evolution dimensionality reduction discrete artificial bee colony algorithm diversity preservation dominance dynamic learning elephant herding optimization engineering optimization evolutionary algorithm evolutionary algorithms (EAs) evolutionary computation feature selection fuzzing fuzzy hybrid flow shop scheduling game feature game simulation game trees geoelectric model global optimization green shop scheduling grey wolf optimizer h-index iterated local search knapsack problem knowledge transfer krill herd magnetotelluric many-objective optimization memetic algorithm menu planning problem metaheuristic minimize makespan minimize total energy consumption multi-indicators multi-metric multi-objective optimization multi-resources multi-task evolutionary computation multi-task optimization mutation one-dimensional inversions opposite path opposition-based learning optimization problem Pareto optimality Pareto-front particle swarm optimization path discovery performance indicators playtesting playtesting metric premature convergence Q-learning quantum quantum computing ranking seed schedule self-adaptive step size simulated annealing single objective optimization single-objective optimization success-history swarm intelligence traveling salesman problems travelling salesman problem turning-based mutation unified search space universities ranking validation whale optimization algorithm WOA |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910557699203321 |
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Wang Gai-Ge
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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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Machine Learning in Sensors and Imaging
| Machine Learning in Sensors and Imaging |
| Autore | Nam Hyoungsik |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 online resource (302 p.) |
| Soggetto topico |
History of engineering & technology
Technology: general issues |
| Soggetto non controllato |
activity recognition
artificial neural network BLDC BP artificial neural network burr formation capacitive chaotic system color prior model compressive sensing computer vision coniferous plantations convex optimization convolutional neural network cut interruption deep learning display electric machine protection explainable artificial intelligence extrinsic camera calibration fiber laser forest growing stem volume fuzzy image classification image denoising image encryption imbalanced activities intelligent vehicles laser cutting machine learning machine learning-based classification marine maximum likelihood estimation mixed Poisson-Gaussian likelihood modulation transfer function Naïve bayes neural network noisy non-uniform foundation object detection obstacle avoidance on-shelf availability path planning piston error detection plaintext related plankton Q-learning quality monitoring random forest real-world red-edge band reinforcement learning risk assessment robot arm sampling methods segmented telescope semi-supervised semi-supervised learning SNR star image stochastic analysis structure from motion stylus target reaching temperature estimation texture feature touchscreen transmission-line corridors variable selection vehicle-pavement-foundation interaction wearable sensors wildfire YOLO algorithm |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910566484703321 |
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Nam Hyoungsik
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Modeling, Optimization and Design Method of Metal Manufacturing Processes
| Modeling, Optimization and Design Method of Metal Manufacturing Processes |
| Autore | Zhang Guoqing |
| Pubbl/distr/stampa | Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 |
| Descrizione fisica | 1 electronic resource (214 p.) |
| Soggetto topico |
Business strategy
Manufacturing industries |
| Soggetto non controllato |
machine learning
reinforcement learning Q-learning steelmaking process CAS-OB decision-support system optimisation algorithm 3D auxetic structures selective laser melting micro assembled structural surface layer model A380 alloy Ca AlFeSi phase refine micro-cutting grain size surface integrity cutting forces chip formation OFHC copper C102 amorphous alloys Fe-based amorphous alloys difficult-to-machine assisted machining high-frequency PCB drilling coating technology tool wear hot filament chemical vapor deposition PCBN tool gray cast iron surface quality temperature prediction weighted regularized extreme learning machine just-in-time learning sample similarities variable correlations tool edge preparation orthogonal cutting numerical simulation ANOVA temperature stress ECAP metallic materials processing parameters deformation mechanism |
| ISBN | 3-0365-6033-5 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910639996303321 |
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Zhang Guoqing
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| Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
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Reinforcement Learning From Scratch : Understanding Current Approaches - with Examples in Java and Greenfoot / Uwe Lorenz
| Reinforcement Learning From Scratch : Understanding Current Approaches - with Examples in Java and Greenfoot / Uwe Lorenz |
| Autore | Lorenz, Uwe |
| Pubbl/distr/stampa | Cham, : Springer, 2022 |
| Descrizione fisica | xiv, 184 p. : ill. ; 24 cm |
| Soggetto topico |
68-XX - Computer science [MSC 2020]
68Nxx - Theory of software [MSC 2020] 68Pxx - Theory of data [MSC 2020] |
| Soggetto non controllato |
Actor-Critic
Artificial Intelligence Deep reinforcement learning Greenfoot Java-Hamster Machine learning Policy Gadient Q-learning Reinforcement Learning SARSA |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Titolo uniforme | |
| Record Nr. | UNICAMPANIA-VAN0278101 |
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Lorenz, Uwe
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| Cham, : Springer, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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Reinforcement Learning From Scratch : Understanding Current Approaches- with Examples in Java and Greenfoot / Uwe Lorenz
| Reinforcement Learning From Scratch : Understanding Current Approaches- with Examples in Java and Greenfoot / Uwe Lorenz |
| Autore | Lorenz, Uwe |
| Pubbl/distr/stampa | Cham, : Springer, 2022 |
| Descrizione fisica | xiv, 184 p. : ill. ; 24 cm |
| Soggetto topico |
68-XX - Computer science [MSC 2020]
68Nxx - Theory of software [MSC 2020] 68Pxx - Theory of data [MSC 2020] |
| Soggetto non controllato |
Actor-Critic
Artificial Intelligence Deep reinforcement learning Greenfoot Java-Hamster Machine learning Policy Gadient Q-learning Reinforcement Learning SARSA |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNICAMPANIA-VAN00278101 |
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Lorenz, Uwe
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| Cham, : Springer, 2022 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Vanvitelli | ||
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