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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 electronic resource (324 p.) |
| Soggetto topico |
Technology: general issues
History of engineering & technology |
| Soggetto non controllato |
truck dispatching
mining equipment uncertainties orebody uncertainty discrete event simulation Q-learning grinding circuits minerals processing random forest decision trees machine learning knowledge discovery variable importance mineral prospectivity mapping random forest algorithm epithermal gold unstructured data blast impact empirical model mining fragmentation mine worker fatigue random forest model health and safety management stockpiles operational data mine-to-mill geostatistics ore control mine optimization digital twin modes of operation geological uncertainty multivariate statistics partial least squares regression oil sands bitumen extraction bitumen processability mine safety and health accidents narratives natural language processing random forest classification hyperspectral imaging multispectral imaging dimensionality reduction neighbourhood component analysis artificial intelligence mining exploitation masonry buildings damage risk analysis Bayesian network Naive Bayes Bayesian Network Structure Learning (BNSL) rock type mining geology bluetooth beacon classification and regression tree gaussian naïve bayes k-nearest neighbors support vector machine transport route transport time underground mine tactical geometallurgy data analytics in mining ball mill throughput measurement while drilling non-additivity coal petrographic analysis macerals image analysis semantic segmentation convolutional neural networks point cloud scaling fragmentation size analysis structure from motion |
| 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 electronic resource (230 p.) |
| Soggetto topico | Economics, finance, business & management |
| Soggetto non controllato |
algorithmic trading
Stop Loss Turtle ATR community finances fiscal flexibility individualized financial arrangements sustainable financial services price momentum hidden markov model asset allocation blockchain BlockCloud Artificial Intelligence consensus algorithms exchange rates fundamentals prediction random forest support vector machine neural network deep reinforcement learning financial market simulation agent based simulation artificial market simulation CAR regulation portfolio contract for difference CfD reinforcement learning RL neural networks long short-term memory LSTM Q-learning deep learning uncertainty economic policy text mining topic model yield curve term structure of interest rates machine learning autoencoder interpretability |
| 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 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-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 electronic resource (442 p.) |
| Soggetto topico | Technology: general issues |
| Soggetto non controllato |
global optimization
cuckoo search algorithm Q-learning mutation self-adaptive step size evolutionary computation playtesting game feature game simulation game trees playtesting metric validation Pareto optimality h-index ranking dominance Pareto-front multi-indicators multi-metric multi-resources citation universities ranking swarm intelligence simulated annealing krill herd particle swarm optimization quantum elephant herding optimization engineering optimization metaheuristic constrained optimization multi-objective optimization single objective optimization differential evolution success-history premature convergence turning-based mutation opposition-based learning ant colony optimization opposite path traveling salesman problems whale optimization algorithm WOA binary whale optimization algorithm bWOA-S bWOA-V feature selection classification dimensionality reduction menu planning problem evolutionary algorithm decomposition-based multi-objective optimisation memetic algorithm iterated local search diversity preservation single-objective optimization knapsack problem travelling salesman problem seed schedule many-objective optimization fuzzing bug detection path discovery evolutionary algorithms (EAs) coevolution dynamic learning performance indicators magnetotelluric one-dimensional inversions geoelectric model optimization problem multi-task optimization multi-task evolutionary computation knowledge transfer assortative mating unified search space quantum computing grey wolf optimizer 0-1 knapsack problem green shop scheduling fuzzy hybrid flow shop scheduling discrete artificial bee colony algorithm minimize makespan minimize total energy consumption |
| 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 electronic resource (302 p.) |
| Soggetto topico |
Technology: general issues
History of engineering & technology |
| Soggetto non controllato |
star image
image denoising reinforcement learning maximum likelihood estimation mixed Poisson–Gaussian likelihood machine learning-based classification non-uniform foundation stochastic analysis vehicle–pavement–foundation interaction forest growing stem volume coniferous plantations variable selection texture feature random forest red-edge band on-shelf availability semi-supervised learning deep learning image classification machine learning explainable artificial intelligence wildfire risk assessment Naïve bayes transmission-line corridors image encryption compressive sensing plaintext related chaotic system convolutional neural network color prior model object detection piston error detection segmented telescope BP artificial neural network modulation transfer function computer vision intelligent vehicles extrinsic camera calibration structure from motion convex optimization temperature estimation BLDC electric machine protection touchscreen capacitive display SNR stylus laser cutting quality monitoring artificial neural network burr formation cut interruption fiber laser semi-supervised fuzzy noisy real-world plankton marine activity recognition wearable sensors imbalanced activities sampling methods path planning Q-learning neural network YOLO algorithm robot arm target reaching obstacle avoidance |
| 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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