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Bankruptcy Prediction through Soft Computing based Deep Learning Technique / / by Arindam Chaudhuri, Soumya K Ghosh
Bankruptcy Prediction through Soft Computing based Deep Learning Technique / / by Arindam Chaudhuri, Soumya K Ghosh
Autore Chaudhuri Arindam
Edizione [1st ed. 2017.]
Pubbl/distr/stampa Singapore : , : Springer Singapore : , : Imprint : Springer, , 2017
Descrizione fisica 1 online resource (XVII, 102 p. 59 illus.)
Disciplina 005.437
4.019
Soggetto topico User interfaces (Computer systems)
Artificial intelligence
Computer simulation
Management information systems
Computer science
Banks and banking
Statistics 
User Interfaces and Human Computer Interaction
Artificial Intelligence
Simulation and Modeling
Management of Computing and Information Systems
Banking
Statistics for Business, Management, Economics, Finance, Insurance
ISBN 981-10-6683-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Introduction -- Need of this Research -- Literature Review -- Bankruptcy Prediction Methodology -- Need for Risk Classification -- Experimental Framework: Bankruptcy Prediction using Soft Computing based Deep Learning Technique.- Datasets Used -- Experimental Results -- Conclusion .
Record Nr. UNINA-9910254843703321
Chaudhuri Arindam  
Singapore : , : Springer Singapore : , : Imprint : Springer, , 2017
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Decision making algorithms for hydro-power plant location / / Mrinmoy Majumder and Soumya Ghosh
Decision making algorithms for hydro-power plant location / / Mrinmoy Majumder and Soumya Ghosh
Autore Majumder Mrinmoy
Edizione [1st ed. 2013.]
Pubbl/distr/stampa New York, : Springer, 2013
Descrizione fisica 1 online resource (vi, 73 pages) : illustrations (some color), color maps
Disciplina 333.9140151
621.319
Altri autori (Persone) GhoshSoumya K
Collana Springer briefs in energy
Soggetto topico Water-power
Power-plants
ISBN 981-4451-63-0
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Introduction -- Hydro-Power Plants -- Decision Making Procedures -- Nature Based Algorithms -- Case Studies -- Conclusions.
Record Nr. UNINA-9910739474303321
Majumder Mrinmoy  
New York, : Springer, 2013
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Enhanced Bayesian Network Models for Spatial Time Series Prediction : Recent Research Trend in Data-Driven Predictive Analytics / / by Monidipa Das, Soumya K. Ghosh
Enhanced Bayesian Network Models for Spatial Time Series Prediction : Recent Research Trend in Data-Driven Predictive Analytics / / by Monidipa Das, Soumya K. Ghosh
Autore Das Monidipa
Edizione [1st ed. 2020.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020
Descrizione fisica 1 online resource (xxiii, 149 pages) : illustrations
Disciplina 519.542
519.55 (edition:23)
Collana Studies in Computational Intelligence
Soggetto topico Computational intelligence
Engineering—Data processing
Computational complexity
Engineering mathematics
Computational Intelligence
Data Engineering
Complexity
Engineering Mathematics
ISBN 3-030-27749-6
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Introduction -- Standard Bayesian Network Models for Spatial Time Series Prediction -- Bayesian Network with added Residual Correction Mechanism -- Spatial Bayesian Network -- Semantic Bayesian Network -- Advanced Bayesian Network Models with Fuzzy Extension -- Comparative Study of Parameter Learning Complexity -- Spatial Time Series Prediction using Advanced BN Models— An Application Perspective -- Summary and Future Research.
Record Nr. UNINA-9910485008003321
Das Monidipa  
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Quantitative Modeling of Operational Risk in Finance and Banking Using Possibility Theory / / by Arindam Chaudhuri, Soumya K. Ghosh
Quantitative Modeling of Operational Risk in Finance and Banking Using Possibility Theory / / by Arindam Chaudhuri, Soumya K. Ghosh
Autore Chaudhuri Arindam
Edizione [1st ed. 2016.]
Pubbl/distr/stampa Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016
Descrizione fisica 1 online resource (XVI, 190 p. 65 illus., 53 illus. in color.)
Disciplina 658.155
Collana Studies in Fuzziness and Soft Computing
Soggetto topico Computational complexity
Statistics 
Operations research
Decision making
Economics, Mathematical 
Complexity
Statistics for Business, Management, Economics, Finance, Insurance
Operations Research/Decision Theory
Quantitative Finance
ISBN 3-319-26039-1
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910254185603321
Chaudhuri Arindam  
Cham : , : Springer International Publishing : , : Imprint : Springer, , 2016
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Statistical and Machine Learning Models for Remote Sensing Data Mining - Recent Advancements
Statistical and Machine Learning Models for Remote Sensing Data Mining - Recent Advancements
Autore Das Monidipa
Pubbl/distr/stampa Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022
Descrizione fisica 1 electronic resource (112 p.)
Soggetto topico Research & information: general
Environmental economics
Soggetto non controllato scene classification
teacher-student
noisy labels
knowledge distillation
remote sensing images
LightGBM
spatiotemporal weight interpolation
AOD recovery
East Asia
polarized SAR
optical image
random forest
conditional random fields
feature-level fusion
Dirichlet process
infinite mixture models
Gamma distribution
variational inference
online setting
oil spill detection
synthetic aperture radar images
GNSS-R
CYGNSS
high wind speed inversion
SVR
PCA-SVR
CNN
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Record Nr. UNINA-9910585940903321
Das Monidipa  
Basel, : MDPI - Multidisciplinary Digital Publishing Institute, 2022
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui