tag :: learning, Machine data

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1Energy Efficiency and Sustainability Analytics for Reducing Carbon Emissions in Oil Refineries
G. Sinha. INTERNATIONAL JOURNAL OF TREND IN SCIENTIFIC RESEARCH AND DEVELOPMENT, 8 (3): 1008-1015 (июня 2024)
3 месяцев назад , @ijtsrd
Energy,
analytics,
carbon
data
efficiency,
emissions,
environmental
gas
greenhouse
learning,
machine
modeling,
oil
optimization,
performance
predictive
process
reduction,
refineries,
sustainability
Energy,analytics,carbondataefficiency,emissions,environmentalgasgreenhouselearning,machinemodeling,oiloptimization,performancepredictiveprocessreduction,refineries,sustainability
(0)
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1Revolutionizing Medical Coding in Clinical Trials with AI
D. Gayathri. INTERNATIONAL JOURNAL OF TREND IN SCIENTIFIC RESEARCH AND DEVELOPMENT, 8 (2): 191-196 (апреля 2024)
4 месяцев назад , @ijtsrd
Artificialintelligence
accuracy,
clinical
coding,
compliance
cost-effectiveness,
data
efficiency,
intelligence,
language
learning,
machine
medical
natural
privacy,
processing,
regulatory
scalability,
trials,
Artificialintelligenceaccuracy,clinicalcoding,compliancecost-effectiveness,dataefficiency,intelligence,languagelearning,machinemedicalnaturalprivacy,processing,regulatoryscalability,trials,
(0)
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1Streamlining Data Collection eCRF Design and Machine Learning
D. Kannareddy. INTERNATIONAL JOURNAL OF TREND IN SCIENTIFIC RESEARCH AND DEVELOPMENT, 8 (1): 830-834 (февраля 2024)
8 месяцев назад , @ijtsrd
Case
Electronic
Forms,
Report
adaptability,
anomaly
clinical
collection
collection,
data
design,
detection,
eCRF
learning,
machine
quality,
real-time
streamlined
trials,
validation,
CaseElectronicForms,Reportadaptability,anomalyclinicalcollectioncollection,datadesign,detection,eCRFlearning,machinequality,real-timestreamlinedtrials,validation,
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1A framework for understanding data science
M. Brodie. ArXiv, (2024)
8 месяцев назад , @mlbrodie
Data
artificial
deep
discovery
intelligence,
knowledge
learning,
machine
problem-solving,
science,
Dataartificialdeepdiscoveryintelligence,knowledgelearning,machineproblem-solving,science,
(0)
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1Data Analytics for Population Health Management Strategies
R. Solanki. INTERNATIONAL JOURNAL OF TREND IN SCIENTIFIC RESEARCH AND DEVELOPMENT, 7 (6): 40-46 (декабря 2023)
10 месяцев назад , @ijtsrd
IoT
analytics,
data
data,
delivery,
devices,
electronic
health
healthcare
learning,
machine
management,
mining
modeling,
patient
population
predictive
privacy,
records,
wearables,
IoTanalytics,datadata,delivery,devices,electronichealthhealthcarelearning,machinemanagement,miningmodeling,patientpopulationpredictiveprivacy,records,wearables,
(0)
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1Design and Development of Return Analysis System Between Purchase and Rental of Game Equipment
N. Han. INTERNATIONAL JOURNAL OF TREND IN SCIENTIFIC RESEARCH AND DEVELOPMENT, 7 (5): 838-848 (октября 2023)
10 месяцев назад , @ijtsrd
analysis,
data
design,
equipment,
games
learning,
machine
system
testing
yield
analysis,datadesign,equipment,gameslearning,machinesystemtestingyield
(0)
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1HEART DISEASE DIAGNOSIS WITH TREE STRUCTURAL NAÏVE BAYES
H. marid Alzamili | Ali Hasan Ali. CENTRAL ASIAN JOURNAL OF MATHEMATICAL THEORY AND COMPUTER SCIENCES, 4 (5): 134-143 (мая 2023)
год назад , @centralasian_20
Heart
bayes,
data
disease,
learning,
machine
mining
naïve
Heartbayes,datadisease,learning,machineminingnaïve
(0)
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1Natural Language Processing Based Disaster Management Framework
G. |. CENTRAL ASIAN JOURNAL OF MEDICAL AND NATURAL SCIENCE, 4 (1): 72-96 (января 2023)
год назад , @centralasian_20
Analysis,
Big
Data
Language
Learning,
Machine
Natural
ProcessingData
Sentiment
Analysis,BigDataLanguageLearning,MachineNaturalProcessingDataSentiment
(0)
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3Private traits and attributes are predictable from digital records of human behavior
M. Kosinski, D. Stillwell, и T. Graepel. Proceedings of the National Academy of Sciences, (марта 2013)
8 лет назад , @yourwelcome
Big
data
data,
humans,
learning,
machine
mining,
networks
psychology,
social
Bigdatadata,humans,learning,machinemining,networkspsychology,social
(0)
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1Data-intensive science: a new paradigm for biodiversity studies
S. Kelling, W. Hochachka, D. Fink, M. Riedewald, R. Caruana, G. Ballard, и G. Hooker. BioScience, 59 (7): 613--620 (июля 2009)
8 лет назад , @yourwelcome
Learning,
Machine
biodiversity,
birds,
citizen
data
estimator
mining,
nonparametric
science,
Learning,Machinebiodiversity,birds,citizendataestimatormining,nonparametricscience,
(0)
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1Evolutionary inference for function-valued traits: Gaussian process regression on phylogenies
N. Jones, и J. Moriarty. arXiv:1004.4668, (апреля 2010)Journal of the Royal Society Interface vol. 10 no. 78 20120616 (2013).
8 лет назад , @yourwelcome
-
Analysis,
Biology
Data
Learning
Learning,
Machine
Methods,
Physics
Probability,
Quantitative
Statistics
and
-Analysis,BiologyDataLearningLearning,MachineMethods,PhysicsProbability,QuantitativeStatisticsand
(0)
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1Machine learning methods without tears: a primer for ecologists.
J. Olden, J. Lawler, и N. Poff. The Quarterly Review of biology, 83 (2): 171--193 (2008)
8 лет назад , @yourwelcome
Animals,
Artificial
Decision
Ecosystem,
Fishes:
Genetic,
Intelligence,
Learning,
Machine
Software,
Species
Specificity,
Trees,
\&
algorithms,
biology,
classification,
computational
data
ecology,
fish,
freshwater,
networks,
neural
numerical
statistics
Animals,ArtificialDecisionEcosystem,Fishes:Genetic,Intelligence,Learning,MachineSoftware,SpeciesSpecificity,Trees,\&algorithms,biology,classification,computationaldataecology,fish,freshwater,networks,neuralnumericalstatistics
(0)
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1Correlated Topic Model for Web Services Ranking
Z. Mustapha AZNAG Mohamed QUAFAFOU. International Journal of Advanced Computer Science and Applications(IJACSA), (2013)
11 лет назад , @thesaiorg
Data
Discovery,
Learning,
Machine
Models,Web
Ranking,
Representation,
Topic
service
DataDiscovery,Learning,MachineModels,WebRanking,Representation,Topicservice
(0)
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1Online modelling based on Genetic Programming
S. Winkler, H. Efendic, L. Del Re, M. Affenzeller, и S. Wagner. International Journal of Intelligent Systems Technologies and Applications, 2 (2/3): 255--270 (19 February 2007)
17 лет назад , @brazovayeye
GP,
algorithms,
automatic
data
diagnosis,
driven
fault
genetic
identification,
learning,
machine
model
modelling,
online
programming,
real
self-adaption,
time
GP,algorithms,automaticdatadiagnosis,drivenfaultgeneticidentification,learning,machinemodelmodelling,onlineprogramming,realself-adaption,time
(0)
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2Applying Online Gradient Descent Search to Genetic Programming for Object Recognition
W. Smart, и M. Zhang. CRPIT '04: Proceedings of the second workshop on Australasian information security, Data Mining and Web Intelligence, and Software Internationalisation, 32 no. 7, стр. 133--138. Dunedin, New Zealand, Australian Computer Society, Inc., (января 2004)
17 лет назад , @brazovayeye
algorithms,
classification
data
genetic
learning,
machine
mining,
object
programming,
algorithms,classificationdatageneticlearning,machinemining,objectprogramming,
(0)
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2Genetic Programming for Mining DNA Chip data from Cancer Patients
W. Langdon, и B. Buxton. Genetic Programming and Evolvable Machines, 5 (3): 251--257 (сентября 2004)
17 лет назад , @brazovayeye
DNA
algorithms,
attribute
cancer
chip
classification,
cross
data
evolutionary
expression,
fold
gene
genetic
learning,
leave
machine
mining,
one
out
predicting
programming,
selection,
validation,
DNAalgorithms,attributecancerchipclassification,crossdataevolutionaryexpression,foldgenegeneticlearning,leavemachinemining,oneoutpredictingprogramming,selection,validation,
(0)
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2Using Data Structures within Genetic Programming
W. Langdon. Genetic Programming 1996: Proceedings of the First Annual Conference, стр. 141--148. Stanford University, CA, USA, MIT Press, (28--31 July 1996)
17 лет назад , @brazovayeye
(ADF),
Artificial
Automatic
Automatically
CFG,
Data
Defined
Demes
Dyck
Evolution,
Expressions,
Functions
Learning,
Machine
Object
Oriented
Pareto
Polish
Programming,
Push
Reverse
Stack,
Structures,
algorithms,
automatic
brackets,
code
context
down
fitness,
free
generation,
genetic
grammar
induction,
language
language,
matched
programming,
(ADF),ArtificialAutomaticAutomaticallyCFG,DataDefinedDemesDyckEvolution,Expressions,FunctionsLearning,MachineObjectOrientedParetoPolishProgramming,PushReverseStack,Structures,algorithms,automaticbrackets,codecontextdownfitness,freegeneration,geneticgrammarinduction,languagelanguage,matchedprogramming,
(0)
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2Using Data Structures within Genetic Programming
W. Langdon. Research Note, RN/96/1. UCL, Gower Street, London, WC1E 6BT, UK, (января 1996)
17 лет назад , @brazovayeye
(ADF),
Artificial
Automatic
Automatically
Data
Defined
Demes
Evolution,
Expressions,
Functions
Learning,
Machine
Object
Oriented
Pareto
Polish
Programming,
Push
Reverse
Stack,
Structures,
algorithms,
automatic
code
context
down
fitness,
free
generation,
genetic
induction,
language
programming,
(ADF),ArtificialAutomaticAutomaticallyDataDefinedDemesEvolution,Expressions,FunctionsLearning,MachineObjectOrientedParetoPolishProgramming,PushReverseStack,Structures,algorithms,automaticcodecontextdownfitness,freegeneration,geneticinduction,languageprogramming,
(0)
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2Evolving Data Structures Using Genetic Programming
W. Langdon. Genetic Algorithms: Proceedings of the Sixth International Conference (ICGA95), стр. 295--302. Pittsburgh, PA, USA, Morgan Kaufmann, (15-19 July 1995)
17 лет назад , @brazovayeye
(ADF),
(FIFO)
Artificial
Automatic
Automatically
Data
Defined
Demes
Evolution,
First-in
Functions
Learning,
Machine
Object
Oriented
Pareto
Programming,
Push
Queue,
Stack,
Structures,
algorithms,
down
first-out
fitness,
genetic
programming,
(ADF),(FIFO)ArtificialAutomaticAutomaticallyDataDefinedDemesEvolution,First-inFunctionsLearning,MachineObjectOrientedParetoProgramming,PushQueue,Stack,Structures,algorithms,downfirst-outfitness,geneticprogramming,
(0)
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2Evolving Data Structures Using Genetic Programming
W. Langdon. Research Note, RN/95/1. UCL, Gower Street, London, WC1E 6BT, UK, (января 1995)
17 лет назад , @brazovayeye
(ADF),
(FIFO)
Artificial
Automatic
Automatically
Data
Defined
Demes
Evolution,
First-in
Functions
Learning,
Machine
Object
Oriented
Pareto
Programming,
Push
Queue,
Stack,
Structures,
algorithms,
down
first-out
fitness,
genetic
programming,
(ADF),(FIFO)ArtificialAutomaticAutomaticallyDataDefinedDemesEvolution,First-inFunctionsLearning,MachineObjectOrientedParetoProgramming,PushQueue,Stack,Structures,algorithms,downfirst-outfitness,geneticprogramming,
(0)
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1Knowledge-intensive genetic discovery in foreign exchange markets
S. Bhattacharyya, O. Pictet, и G. Zumbach. IEEE Transactions on Evolutionary Computation, 6 (2): 169--181 (апреля 2002)
17 лет назад , @brazovayeye
(artificial
algorithms,
arithmetic
comparison
criteria,
data
decision
discovery,
domain-related
exchange
financial
fitness
foreign
genetic
high-frequency
indicator
intelligence),
knowledge
knowledge-intensive
learning
learning,
logical
machine
markets,
mathematical
measure,
mining,
model
operators,
optimisation
performance,
processing,
programming,
properties,
representation,
restrictions,
return
risk-adjusted
robust
semantic
specification
structuring,
symmetry
symmetry,
trading
trading,
types,
(artificialalgorithms,arithmeticcomparisoncriteria,datadecisiondiscovery,domain-relatedexchangefinancialfitnessforeigngenetichigh-frequencyindicatorintelligence),knowledgeknowledge-intensivelearninglearning,logicalmachinemarkets,mathematicalmeasure,mining,modeloperators,optimisationperformance,processing,programming,properties,representation,restrictions,returnrisk-adjustedrobustsemanticspecificationstructuring,symmetrysymmetry,tradingtrading,types,
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1Energy Efficiency and Sustainability Analytics for Reducing Carbon Emissions in Oil Refineries

1Revolutionizing Medical Coding in Clinical Trials with AI

1Streamlining Data Collection eCRF Design and Machine Learning

1A framework for understanding data science

1Data Analytics for Population Health Management Strategies

1Design and Development of Return Analysis System Between Purchase and Rental of Game Equipment

1HEART DISEASE DIAGNOSIS WITH TREE STRUCTURAL NAÏVE BAYES

1Natural Language Processing Based Disaster Management Framework

3Private traits and attributes are predictable from digital records of human behavior

1Data-intensive science: a new paradigm for biodiversity studies

1Evolutionary inference for function-valued traits: Gaussian process regression on phylogenies

1Machine learning methods without tears: a primer for ecologists.

1Correlated Topic Model for Web Services Ranking

1Online modelling based on Genetic Programming

2Applying Online Gradient Descent Search to Genetic Programming for Object Recognition

2Genetic Programming for Mining DNA Chip data from Cancer Patients

2Using Data Structures within Genetic Programming

2Using Data Structures within Genetic Programming

2Evolving Data Structures Using Genetic Programming

2Evolving Data Structures Using Genetic Programming

1Knowledge-intensive genetic discovery in foreign exchange markets

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