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Biblioteca

MARC Lista (tabellare)
AI Applications to Power Systems
AI Applications to Power Systems
Autore Tjing Lie Tek
Pubbl/distr/stampa Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022
Descrizione fisica 1 online resource (156 p.)
Soggetto topico History of engineering & technology
Technology: general issues
Soggetto non controllato artificial neural networks
automatic P2P energy trading
cellular computational networks
change detection
contingency
data analytics
data mining
deep Q-network
deep reinforcement learning
dynamic mode decomposition
event detection
feature extraction
filtering
fuzzy system
inter-area oscillations
load flow prediction
long short-term delayed reward
machine learning
machine-learning
manta ray foraging optimization algorithm
Markov decision process
modal analysis
multi-objective function
n/a
optimal power flow
optimization
optimization techniques
power quality
radial networks
reduced order modeling
self-healing grid
signal processing
situation awareness
steady-state security assessment
total variation smoothing
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910566478903321
Tjing Lie Tek  
Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Data Science and Knowledge Discovery
Data Science and Knowledge Discovery
Autore Portela Filipe
Pubbl/distr/stampa Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022
Descrizione fisica 1 online resource (254 p.)
Soggetto topico Computer science
Information technology industries
Soggetto non controllato activity recognition
adaptation process
ArcGIS
artificial intelligence
attribution
authorship
automation
big data
Big Data
box-counting framework
chatbots
classification
content base image retrieval
COVID-19
crisis reporting
customer relationship management (CRM)
dashboard
data analysis
data analytics
data augmentation
data mining
data science
databases
decision systems
deep features
deep learning
digital humanities
digital infrastructures
distracted driving
driving behavior
driving operation area
e-commerce
economic determinants of open data
ESP32 microcontroller
feature extraction
forensic intelligence
fractal dimension
geoinformation technology
governance and social institutions
humanities
ICT
information systems
interdisciplinary research
internet of things
ioCOVID19
journalists
linked open data
LoRaWAN
machine learning
media analytics
media criticism
multimedia document retrieval
n/a
neural networks
news media
open government data
prediction by partial matching
public health
rough sets
rule based systems
SARS-CoV-2
script Python
semantic information retrieval
smart homes
social sciences
spatio-temporal
territorial road network
text mining
textbook research
The Things Network
Web Intelligence
WebGIS
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910576878103321
Portela Filipe  
Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Data Science for IoT Engineers : A Systems Analytics Approach
Data Science for IoT Engineers : A Systems Analytics Approach
Autore Madhavan P. G
Pubbl/distr/stampa Bloomfield : , : Mercury Learning & Information, , 2021
Descrizione fisica 1 online resource (170 pages)
Disciplina 006.312024004678
Soggetto topico COMPUTERS / Desktop Applications / Presentation Software
Soggetto non controllato IOT
MATLAB
computer science
data analytics
engineering
mathematics
physics
ISBN 1-68392-640-4
1-68392-641-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Frontmatter -- Contents -- Preface -- About the Author -- PART I Machine Learning from Multiple Perspectives -- CHAPTER 1 Overview of Data Science -- CHAPTER 2 Introduction to Machine Learning -- CHAPTER 3 Systems Theory, Linear Algebra, and Analytics Basics -- CHAPTER 4 “Modern” Machine Learning -- PART II Systems Analytics -- CHAPTER 5 Systems Theory Foundations of Machine Learning -- CHAPTER 6 State Space Model and Bayes Filter -- CHAPTER 7 The Kalman Filter for Adaptive Machine Learning -- CHAPTER 8 The Need for Dynamical Machine Learning: The Bayesian Exact Recursive Estimation -- CHAPTER 9 Digital Twins -- Epilogue A New Random Field Theory -- Index
Record Nr. UNINA-9910795555703321
Madhavan P. G  
Bloomfield : , : Mercury Learning & Information, , 2021
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Data Science for IoT Engineers : A Systems Analytics Approach
Data Science for IoT Engineers : A Systems Analytics Approach
Autore Madhavan P. G
Pubbl/distr/stampa Bloomfield : , : Mercury Learning & Information, , 2021
Descrizione fisica 1 online resource (170 pages)
Disciplina 006.312024004678
Soggetto topico COMPUTERS / Desktop Applications / Presentation Software
Soggetto non controllato IOT
MATLAB
computer science
data analytics
engineering
mathematics
physics
ISBN 1-68392-640-4
1-68392-641-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Frontmatter -- Contents -- Preface -- About the Author -- PART I Machine Learning from Multiple Perspectives -- CHAPTER 1 Overview of Data Science -- CHAPTER 2 Introduction to Machine Learning -- CHAPTER 3 Systems Theory, Linear Algebra, and Analytics Basics -- CHAPTER 4 “Modern” Machine Learning -- PART II Systems Analytics -- CHAPTER 5 Systems Theory Foundations of Machine Learning -- CHAPTER 6 State Space Model and Bayes Filter -- CHAPTER 7 The Kalman Filter for Adaptive Machine Learning -- CHAPTER 8 The Need for Dynamical Machine Learning: The Bayesian Exact Recursive Estimation -- CHAPTER 9 Digital Twins -- Epilogue A New Random Field Theory -- Index
Record Nr. UNINA-9910810050903321
Madhavan P. G  
Bloomfield : , : Mercury Learning & Information, , 2021
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Dealing with Data Pocket Primer
Dealing with Data Pocket Primer
Autore Campesato Oswald
Pubbl/distr/stampa Bloomfield : , : Mercury Learning & Information, , 2022
Descrizione fisica 1 online resource (246 pages)
Disciplina 001.42
Collana Computing
Soggetto topico Quantitative research - Reliability
Quantitative research - Data processing
Soggetto non controllato NLP
Pandas
RDBMS
SQL
computer science
data analytics
data cleaning
data visualization
programming
python
statistics
ISBN 1-5231-4740-7
1-68392-818-0
1-68392-819-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Frontmatter -- Contents -- Preface -- Chapter 1: Introduction to Probability and Statistics -- Chapter 2: Working with Data -- Chapter 3: Introduction to Pandas -- Chapter 4: Introduction to RDBMS and SQL -- Chapter 5: Working with SQL and MySQL -- Chapter 6: NLP and Data Cleaning -- Chapter 7: Data Visualization -- Index
Record Nr. UNINA-9910795724303321
Campesato Oswald  
Bloomfield : , : Mercury Learning & Information, , 2022
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Dealing with Data Pocket Primer
Dealing with Data Pocket Primer
Autore Campesato Oswald
Pubbl/distr/stampa Bloomfield : , : Mercury Learning & Information, , 2022
Descrizione fisica 1 online resource (246 pages)
Disciplina 001.42
Collana Computing
Soggetto topico Quantitative research - Reliability
Quantitative research - Data processing
Soggetto non controllato NLP
Pandas
RDBMS
SQL
computer science
data analytics
data cleaning
data visualization
programming
python
statistics
ISBN 1-5231-4740-7
1-68392-818-0
1-68392-819-9
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Frontmatter -- Contents -- Preface -- Chapter 1: Introduction to Probability and Statistics -- Chapter 2: Working with Data -- Chapter 3: Introduction to Pandas -- Chapter 4: Introduction to RDBMS and SQL -- Chapter 5: Working with SQL and MySQL -- Chapter 6: NLP and Data Cleaning -- Chapter 7: Data Visualization -- Index
Record Nr. UNINA-9910823375903321
Campesato Oswald  
Bloomfield : , : Mercury Learning & Information, , 2022
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Industrial Applications: New Solutions for the New Era
Industrial Applications: New Solutions for the New Era
Autore de Sales Guerra Tsuzuki Marcos
Pubbl/distr/stampa Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022
Descrizione fisica 1 online resource (270 p.)
Soggetto topico History of engineering & technology
Technology: general issues
Soggetto non controllato artificial intelligence
asset administration shell
benchmarking
big data and analytics
computer vision
control strategy
convolutional neural networks
coordinate metrology
COVID-19
data analytics
data models
database
depth image
digital manufacturing
digital twin
electrical machines
electrical maintenance
ensemble learning
exoskeletons
fault detection
fever
frequency inverter
fuzzy
goal-oriented requirements engineering
image classification
induction machines
industry
Industry 4.0
integrated inspection system
intelligent systems
IoT
machine learning
microgrid model-based systems engineering
MLOps
noise reduction
operation and maintenance
optical scanning
Petri net
photovoltaics
PID controller
prediction
propagation velocity
renewable energy
ROS
safety instrumented system
service systems
SVPWM modulation
synthetic data
test bench
thermography
UAV
ultrasound
uncertainty
vector control
ventricular assist device Bayesian network
warehouse management
water content
water-in-crude oil emulsion
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Altri titoli varianti Industrial Applications
Record Nr. UNINA-9910566468403321
de Sales Guerra Tsuzuki Marcos  
Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Knowledge Graphs and Big Data Processing [[electronic resource] /] / edited by Valentina Janev, Damien Graux, Hajira Jabeen, Emanuel Sallinger
Knowledge Graphs and Big Data Processing [[electronic resource] /] / edited by Valentina Janev, Damien Graux, Hajira Jabeen, Emanuel Sallinger
Autore Janev Valentina
Edizione [1st ed. 2020.]
Pubbl/distr/stampa Springer Nature, 2020
Descrizione fisica 1 online resource (XI, 209 p. 39 illus., 32 illus. in color.)
Disciplina 005.74
Collana Information Systems and Applications, incl. Internet/Web, and HCI
Soggetto topico Database management
Application software
Artificial intelligence
Computer logic
Management information systems
Database Management
Information Systems Applications (incl. Internet)
Logic in AI
Computer Appl. in Administrative Data Processing
Business Information Systems
Soggetto non controllato Database Management
Information Systems Applications (incl. Internet)
Logic in AI
Computer Appl. in Administrative Data Processing
Business Information Systems
Computer and Information Systems Applications
Computer Application in Administrative Data Processing
artificial intelligence
big data
data analytics
data handling
data integration
data mining
databases
digital storage
domain knowledge
graph theory
information management
information technology
integrated data
internet
knowledge management
knowledge-based system
ontologies
semantics
Databases
Database programming
Information retrieval
Internet searching
Artificial intelligence
Public administration
Information technology: general issues
Business mathematics & systems
ISBN 3-030-53199-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Foundations -- Chapter 1. Ecosystem of Big Data -- Chapter 2. Knowledge Graphs: The Layered Perspective -- Chapter 3. Big Data Outlook, Tools, and Architectures -- Architecture -- Chapter 4. Creation of Knowledge Graphs -- Chapter 5. Federated Query Processing -- Chapter 6. Reasoning in Knowledge Graphs: An Embeddings Spotlight -- Methods and Solutions -- Chapter 7. Scalable Knowledge Graph Processing using SANSA -- Chapter 8. Context-Based Entity Matching for Big Data -- Applications -- Chapter 9. Survey on Big Data Applications -- Chapter 10. Case Study from the Energy Domain.
Record Nr. UNISA-996418289903316
Janev Valentina  
Springer Nature, 2020
Materiale a stampa
Lo trovi qui: Univ. di Salerno
Opac: Controlla la disponibilità qui
Open Data and Energy Analytics
Open Data and Energy Analytics
Autore Nastasi Benedetto
Pubbl/distr/stampa Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020
Descrizione fisica 1 online resource (218 p.)
Soggetto topico Research and information: general
Soggetto non controllato artificial neural network
big data
building dataset
building performance simulation
building stock
buildings
classification
clustering
collaborative work
data analytics
data envelopment analysis
data mining
data pre- and post-processing
data-aware planning
data-handling
decision tree
district heating
domestic hot water
electrification modelling
energy
energy consumption
energy data
energy efficiency
energy management
energy mapping
energy modelling
energy performance certificate
energy planning
energy potential mapping
energy-consuming activities
EU28
factor analysis
forecasting
heat density map
heat map
heating
heating energy demand
integrated assessment modelling
kNN
Kohonen self-organizing maps
machine learning
Malawi
market assessment
MESSAGEix
model calibration
multiple regression
OnSSET
ontology
open data
open data analytics
open energy governance
open modelling and data
parametric modelling
Passive House
pattern recognition
polygeneration
random forest
regression
reproducibility
smart cities
social media
space heating
spatial analysis
spatial planning
support vector machine
urban database
urban energy atlas
urban energy transition
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910557116603321
Nastasi Benedetto  
Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2020
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Smart Urban Water Networks
Smart Urban Water Networks
Autore Creaco Enrico
Pubbl/distr/stampa Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
Descrizione fisica 1 online resource (358 p.)
Soggetto topico Technology: general issues
Soggetto non controllato agent-based modeling
blind sources separation
chaotic time series
cluster analysis
clustering
comparative analysis
cross-correlation
cyber wellness
cyber-attack detection
cyber-physical attacks
cyber-physical security
cyber-security
data analytics
data resolution
data science
data spatial aggregation
decentralized water supply
DEMATEL
district metered area
dual reticulation
entropy
error correction
FastICA
fault identification
finite population effect
flooding detection
framework
hybrid model
hydraulic measure
hydraulic modelling
hydraulic transient
Internet of Things
inverse transient analysis (ITA)
leakage
least square support vector machine
machine learning
metering
multi-criteria decision analysis (MCDA)
multi-criteria decision-making
n/a
network sectorization
nitrate
nitrite
optimal sensor placement
optimization approach
pressure control valve
pressure management
rainwater harvesting
reliability index
remote real-time control
sample mean
sampling design
sensitivity
smart city
smart meter
smart stormwater
smart water system
smart water systems
smartness
standard error
stochastic analysis
stochastic consumption
topological centrality
uncertainty
urban water consumption
urban water management
water data accessibility
water demand data
water demand forecasting
water demand peak factor
water distribution monitoring
water distribution network
water distribution network (WDN)
water distribution networks
water distribution system
water distribution systems
water network partitioning
water quality monitoring
water trading
water treatment plant
wireless sensor networks
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910557333303321
Creaco Enrico  
Basel, Switzerland, : MDPI - Multidisciplinary Digital Publishing Institute, 2021
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui